INVESTIGATION OF MAJOR
HISTOCOMPATIBILITY
COMPLEX (MHC) ASSOCIATIONS
IN SPORADIC INCLUSION BODY
MYOSITIS
By
Adrian Phillip Scott, BSc (Hons)
This thesis is presented for the degree of Doctor of
Philosophy of the University of Western Australia
2008
School of Pathology and Laboratory Medicine
University of Western Australia
Perth, Western Australia
ii
DECLARATION
I declare that this thesis is my own account of my research (unless
otherwise stated), and contains as its main context work that has
not previously been submitted for a degree at any tertiary
education institution.
Adrian Phillip Scott
March 2009
iii
ABSTRACT
Sporadic inclusion body myositis (sIBM) is a chronic inflammatory disease that is the
most common myopathy in individuals above the age of 50 in the Caucasian population.
sIBM is characterised by cytotoxic immune infiltration of skeletal muscle, consisting
primarily of CD8+ T-cells and macrophages, as well as a degenerative process, with
muscle fibre vacuolation and intracellular filamentous inclusions. The pathogenesis of
sIBM is likely to involve a complex interaction between genetic and environmental
factors.
Whilst the physiological and pathological characteristics of sIBM have been clearly
identified, the exact origin and genetic basis of the disease remains unknown. A number
of studies show that sIBM is associated with alleles of the major histocompatibility
complex (MHC) on chromosome 6p21.3 and specifically with two ancestral haplotypes
(AH) in Caucasians – the 8.1AH, defined by HLA-B*0801, HLA-DRB1*0301 and the
35.2AH, defined by HLA-B*3501, HLA-DRB1*0101. Mapping studies subsequently
showed that sIBM susceptibility likely originates from a 389kb region of the MHC,
spanning from centromeric of PBX2 to telomeric of HLA-DRB1.
The central hypothesis of this thesis was that susceptibility to sIBM is conferred by a
single allele found within a region defined using the 8.1AH, which is also carried by
other haplotypes associated with sIBM. Three patient cohorts from Australia, the U.S.A
and Japan were studied. The 8.1AH and individual alleles that define the 8.1AH (HLA-
B*0801 and HLA-DRB1*0301) were increased in Caucasian cohorts as reported in
previous studies. Allele and haplotype frequencies also suggested that the 7.2AH, rather
than the 35.2AH, was associated with sIBM in Caucasians. High-density SNP typing
subsequently showed that the 35.2AH and 7.2AH are nearly identical in the region
between PBX2 and HLA-DRA, suggesting that the observed susceptibility may originate
from a region identical to both haplotypes. A strong association with sIBM was found
with the 52.1AH in the Japanese, defined by HLA-B*5201, HLA-DRB1*1502. This is
the first statistically significant association found within Japanese sIBM patients.
To determine whether the sIBM-associated AHs share a common susceptibility allele,
all exonic and promoter region alleles typical of the 8.1AH were characterised in the
8.1AH, 7.2AH, 35.2AH, 52.1AH, and multiple other AHs. Of the 32 alleles genotyped,
iv
none were found in all susceptibility haplotypes and one was common, but not unique,
to the 8.1AH, 7.2AH and 52.1AH. Five SNPs were also found in two of the three
haplotypes, although none were specific to the sIBM susceptibility haplotypes. These
data suggest that the 8.1AH is likely to carry an sIBM susceptibility allele independent
of the 35.2AH, 7.2AH and 52.1AH.
Based on the possible mechanism of action in cellular differentiation and its location
within the 8.1AH-defined sIBM susceptibility region reported in 2004, NOTCH4 was a
strong candidate for conferring sIBM susceptibility. NOTCH4 coding region
polymorphisms were thus investigated in a Caucasian patient cohort to assess any
possible role in sIBM susceptibility. While the frequency of some alleles were increased
in sIBM patients, the strong linkage disequilibrium throughout the MHC prevented
confirmation of any alleles as playing a direct role in sIBM.
The 8.1AH-derived sIBM susceptibility region was further refined using recombination
mapping. This approach used markers characterised against multiple haplotypes to
genotype patients carrying part of the 8.1AH to locate a common, overlapping
susceptibility region. Recombination mapping of patients revealed a common
overlapping region of the 8.1AH, extending from BTNL2 to HLA-DRB3. The results of
the study indicate that 8.1AH-derived susceptibility for sIBM is likely to originate from
a 172kb region encompassing HLA-DRA, HLA-DRB3 and part of BTNL2. These genes
warrant further investigation in future studies.
v
TABLE OF CONTENTS
DECLARATION .......................................................................... ii
ABSTRACT ................................................................................. iii
LIST OF TABLES ...................................................................... xi
LIST OF FIGURES .................................................................. xiv
ABBREVIATIONS ................................................................... xvi
ACKNOWLEGEMENTS ....................................................... xvii
1 LITERATURE REVIEW ..................................................... 1
1.1 The inflammatory myopathies .......................................................................... 2
1.2 Dermatomyositis ............................................................................................... 2
1.3 Polymyositis ...................................................................................................... 4
1.4 Inclusion body myositis .................................................................................... 5
1.4.1 Onset and frequency of sIBM ................................................................... 6
1.4.2 Clinical and pathological features of sIBM .............................................. 6
1.4.3 Diagnosis of sIBM .................................................................................... 8
1.4.4 Differential diagnosis .............................................................................. 10
1.4.5 Progression of sIBM ............................................................................... 11
1.4.6 Treatment of sIBM .................................................................................. 12
1.4.7 sIBM and comorbid diseases .................................................................. 13
1.5 Hereditary inclusion body myopathies............................................................ 14
1.6 The Pathogenesis of sIBM .............................................................................. 17
1.6.1 Viral Infection ......................................................................................... 18
1.6.2 Autoimmunity ......................................................................................... 19
1.6.3 -Amyloid accumulation ........................................................................ 21
1.6.4 Genetic susceptibility .............................................................................. 25
1.7 The major histocompatibility complex ........................................................... 27
1.7.1 Gene density and gene clustering ............................................................ 29
vi
1.7.2 Linkage disequilibrium ........................................................................... 29
1.7.3 Polymorphism ......................................................................................... 31
1.7.4 Disease association.................................................................................. 31
1.7.5 Locating MHC-related disease susceptibility alleles .............................. 33
1.7.6 HLA Allele Typing .................................................................................. 35
1.8 sIBM-associated HLA alleles ......................................................................... 36
1.9 The sIBM susceptibility region ....................................................................... 39
1.10 Aims and Hypotheses. ..................................................................................... 41
2 METHODS ........................................................................... 43
2.1 Patients and cell lines ...................................................................................... 44
2.1.1 Australian cohort ..................................................................................... 44
2.1.2 American cohort ...................................................................................... 44
2.1.3 German cohort ......................................................................................... 44
2.1.4 Japanese cohort ....................................................................................... 44
2.1.5 Cell lines ................................................................................................. 45
2.2 Experimental procedures ................................................................................. 47
2.2.1 Lymphocyte DNA extraction .................................................................. 47
2.2.2 Whole genome amplification .................................................................. 48
2.2.3 Gel electrophoresis .................................................................................. 48
2.2.4 DNA amplification/PCR ......................................................................... 48
2.2.5 Restriction fragment length polymorphism (RFLP) analysis ................. 53
2.2.6 Sequencing .............................................................................................. 54
2.2.7 Genescan ................................................................................................. 55
2.2.8 HLA allele typing .................................................................................... 56
2.2.9 Single strand conformation polymorphism ............................................. 56
2.3 Analytial Methods ........................................................................................... 56
2.3.1 Sequence analysis.................................................................................... 56
2.3.2 Microsatellite typing ............................................................................... 56
2.3.3 Statistics .................................................................................................. 57
3 ALIGNMENT OF HAPLOTYPE SEQUENCES WITHIN
THE SIBM SUSCEPTIBILITY REGION .............................. 58
3.1 Abstract ........................................................................................................... 59
3.2 Introduction ..................................................................................................... 59
vii
3.3 Results ............................................................................................................. 61
3.3.1 Sequence alignment of the sIBM region ................................................. 61
3.3.2 Identification of polymorphisms ............................................................. 62
3.4 Discussion ....................................................................................................... 66
3.4.1 Summary ................................................................................................. 66
3.4.2 Previous work ......................................................................................... 66
3.4.3 Future studies .......................................................................................... 66
4 INVESTIGATION OF NOTCH4 CODING REGION
POLYMORPHISMS IN SIBM PATIENTS ........................... 67
4.1 Abstract ........................................................................................................... 68
4.2 Introduction ..................................................................................................... 68
4.3 Results ............................................................................................................. 71
4.3.1 Selection of polymorphisms .................................................................... 71
4.3.2 Allele genotyping .................................................................................... 72
4.3.3 NOTCH4 SNPs in the Australian cohort ................................................. 76
4.3.4 NOTCH4 SNPs in the American cohort ................................................. 76
4.3.5 The rs9281675 microsatellite .................................................................. 76
4.3.6 Carriage of all investigated 8.1AH alleles .............................................. 77
4.4 Discussion ....................................................................................................... 78
4.4.1 Summary ................................................................................................. 78
4.4.2 Comparison of the Australian and American cohorts ............................. 78
4.4.3 Linkage disequilibrium ........................................................................... 79
4.4.4 The dilution of alleles by non-sIBM associated AHs ............................. 80
4.4.5 Possible allele function ........................................................................... 81
4.4.6 Future studies .......................................................................................... 82
5 HLA ALLELE AND ANCESTRAL HAPLOTYPE
ASSOCIATIONS IN THE AUSTRALIAN, AMERICAN
AND JAPANESE COHORTS .................................................. 85
5.1 Abstract ........................................................................................................... 86
5.2 Introduction ..................................................................................................... 86
5.3 Results ............................................................................................................. 88
5.3.1 DNA samples .......................................................................................... 88
viii
5.3.2 HLA typing and analysis ......................................................................... 88
5.3.3 Australian cohort ..................................................................................... 90
5.3.4 American cohort ...................................................................................... 93
5.3.5 Japanese Cohort ...................................................................................... 97
5.4 Discussion ..................................................................................................... 104
5.4.1 The 8.1AH ............................................................................................. 104
5.4.2 Protective alleles within the Caucasian cohorts .................................... 104
5.4.3 Assignment of AHs ............................................................................... 105
5.4.4 The 7.2AH and 35.2AH ........................................................................ 105
5.4.5 Other Caucasian AH associations ......................................................... 107
5.4.6 The Japanese 52.1AH............................................................................ 107
5.4.7 HLA-DRB1*0901 in the Japanese cohort............................................. 108
5.4.8 The 7.2AH in the Australian and Japanese cohorts .............................. 108
5.4.9 Past disease associations with sIBM susceptibility haplotypes ............ 109
5.4.10 Future studies ........................................................................................ 109
6 CHARACTERISATION OF SIBM -ASSOCIATED
HAPLOTYPES IN THE 8.1AH-DEFINED
SUSCEPTIBILITY REGION ................................................. 111
6.1 Abstract ......................................................................................................... 112
6.2 Introduction ................................................................................................... 112
6.3 Results ........................................................................................................... 114
6.3.1 Selection of polymorphisms .................................................................. 114
6.3.2 Analysis of sIBM susceptibility haplotypes .......................................... 114
6.3.3 Analysis of multiple ancestral haplotypes............................................. 117
6.3.4 Analysis of rs2050189 .......................................................................... 119
6.4 Discussion ..................................................................................................... 125
6.4.1 Alleles common to multiple susceptibility haplotypes ......................... 125
6.4.2 Alleles in the HLA-DRA promoter region ............................................. 125
6.4.3 The rs2050189 minor allele .................................................................. 126
6.4.4 Alleles common to the 7.2AH, 35.2AH and 52.1AH ........................... 127
6.4.5 Alleles outside of the exonic or promoter regions ................................ 127
6.4.6 Independently acquired susceptibility alleles........................................ 128
6.4.7 NOTCH4 ............................................................................................... 128
ix
6.4.8 Conclusion ............................................................................................ 129
7 IDENTIFICATION AND CHARACTERISATION OF
MHC POLYMORPHISMS FOR RECOMBINATION
MAPPING ................................................................................. 131
7.1 Abstract ......................................................................................................... 132
7.2 Introduction ................................................................................................... 132
7.3 Results ........................................................................................................... 135
7.3.1 Selection of alleles ................................................................................ 135
7.3.2 Characterisation of alleles ..................................................................... 135
7.4 Discussion ..................................................................................................... 140
7.4.1 Summary ............................................................................................... 140
7.4.2 Commonly inherited alleles .................................................................. 140
7.4.3 Variations within and between defined haplotypes .............................. 141
7.4.4 Conclusion ............................................................................................ 142
8 RECOMBINATION MAPPING OF SIBM
SUSCEPTIBILITY ON THE 8.1AH ..................................... 144
8.1 Abstract ......................................................................................................... 145
8.2 Introduction ................................................................................................... 145
8.3 Results ........................................................................................................... 147
8.3.1 Selection of Patients .............................................................................. 147
8.3.2 Selection of polymorphic markers for recombination mapping ........... 149
8.3.3 Patient Genotyping ................................................................................ 151
8.4 Discussion ..................................................................................................... 154
8.4.1 Summary ............................................................................................... 154
8.4.2 Previous recombination mapping studies ............................................. 154
8.4.3 Allele specificity in recombination mapping ........................................ 156
8.4.4 The candidate sIBM susceptibility genes .............................................. 157
8.4.5 The sIBM susceptibility genes and pathogenesis ................................. 159
8.4.6 mRNA expression of the sIBM susceptibility genes ............................ 160
8.4.7 Other susceptibility haplotypes ............................................................. 160
8.4.8 Genes outside the sIBM susceptibility region ....................................... 161
8.4.9 Conclusion ............................................................................................ 161
x
9 GENERAL DISCUSSION ................................................ 163
9.1 Current ‗state of play‘ of MHC disease association...................................... 164
9.2 Overview of the Study .................................................................................. 164
9.3 Considerations ............................................................................................... 166
9.3.1 The 7.2AH and the 35.2AH .................................................................. 166
9.3.2 sIBM in the Japanese, the 7.2AH and ‗sub-haplotypes‘ ....................... 168
9.3.3 The rs2050189 allele ............................................................................. 169
9.3.4 Recombination Mapping ....................................................................... 169
9.4 RNF5 and sIBM ............................................................................................ 171
9.5 sIBM susceptibility from multiple haplotypes .............................................. 172
9.5.1 A common susceptibility allele ............................................................. 173
9.5.2 Independent susceptibility alleles ......................................................... 174
9.5.3 Alleles specific to a sub-haplotype ....................................................... 174
9.6 Future work ................................................................................................... 175
9.6.1 Susceptibility genes outside the MHC region ....................................... 175
9.6.2 Investigation of other sIBM susceptibility AHs.................................... 177
9.7 The next logical step ..................................................................................... 178
REFERENCES ......................................................................... 179
APPENDICIES ........................................................................ 215
xi
LIST OF TABLES
1.1 Diagnostic criteria for sIBM, as defined by Needham and Mastaglia (2007). ...... 10
1.2 Pathological comparison between sIBM and hIBM. Adapted from Askanas
and Engel (1998). ................................................................................................... 17
1.3 Supporting evidence for an immunopathogenic disease mechanism for
sIBM, adapted from Dalakas (2006). ..................................................................... 21
1.4 A selection of diseases associated with the MHC region and some of the
genes with which they have been genetically associated. ...................................... 33
1.5 Past studies demonstrating HLA susceptibility alleles for sIBM. ......................... 36
2.1 10IHW and 4AOH cell lines used throughout the study. ...................................... 46
2.2 Primer sequences used in this study and their optimum conditions....................... 50
3.1 Composition, and location and density of variations overall, and variations
specific to each cell line, within the aligned region. .............................................. 64
4.1 Alleles from the NOTCH4 coding region that are found in the COX cell line
(8.1AH) but not PGF (7.1AH), QBL (18.2AH) or SSTO (44.1AH). .................... 71
4.2 NOTCH4 polymorphisms within the Australian cohort. ....................................... 73
4.3 NOTCH4 polymorphisms within the American cohort. ........................................ 74
4.4 Frequency of NOTCH4 polymorphism alleles and genotypes in the
Australian and American cohorts compared with a control population. ............... 75
4.5 Proportion of patients carrying at least one of the NOTCH4 minor alleles
(haplotypic of the 8.1AH). ..................................................................................... 77
xii
5.1 HLA allele genotyping of the Australian sIBM patient cohort. ............................. 89
5.2 HLA-B allele frequencies for sIBM patients from the Australian cohort and
a healthy population. .............................................................................................. 91
5.3 HLA-DR allele frequencies for sIBM patients from the Australian cohort
and a healthy population. ....................................................................................... 91
5.4 AH phenotype frequencies among patients and controls from the Australian
cohort...................................................................................................................... 92
5.5 HLA allele genotyping of the American sIBM patient cohort. .............................. 94
5.6 HLA-B allele frequencies for sIBM patients from the American cohort and a
healthy population. ................................................................................................. 95
5.7 HLA-DRB1 allele frequencies for sIBM patients from the American cohort
and a healthy population. ....................................................................................... 96
5.8 HLA allele genotyping for the Japanese sIBM patients. ........................................ 98
5.9 HLA-B allele frequencies for Japanese sIBM patients and a healthy
population. .............................................................................................................. 99
5.10 HLA-DRB1 allele frequencies for Japanese sIBM patients and a healthy
population. ............................................................................................................ 100
5.11 HLA-B / HLA-DRB1 haplotype frequencies for Japanese sIBM patients and a
healthy population. ............................................................................................... 101
5.12 HLA-DPB1 allele frequencies for Japanese sIBM patients and a healthy
population. ............................................................................................................ 103
6.1 Alleles in the coding and promoter regions of genes in the sIBM
susceptibility region, between the centromeric ends of PBX2 and HLA-DRA. ... 115
xiii
6.2 Genotyping to identify alleles common to the 8.1AH and the 7.2AH,
35.2AH, or 52.1AH. ............................................................................................. 116
6.3 Haplotypic distribution of 16 selected alleles between the centromeric ends
of PBX2 and HLA-DRA in twenty seven 10th Workshop cell lines. .................. 118
6.4 The total number of haplotypes investigated carrying each allele. ...................... 120
6.5 Occurence of the minor allele for rs2050189 in Australian patients. .................. 122
6.6 Occurence of the minor allele for rs2050189 in American patients. ................... 123
6.7 Frequency of rs2050189 alleles and genotypes in the Australian and
American cohorts compared with a control population. ...................................... 124
7.1 SNPs and microsatellites chosen for characterisation. ......................................... 137
7.2 Haplotypic distribution of 40 selected polymorphisms from telomeric of
RNF5 to HLA-DRA in 26 10IHW cell lines. ........................................................ 138
8.1 Characterisation of markers in 10IHW cell lines carrying defined AHs. ............ 150
8.2 Fine mapping of candidate sIBM patients for carriage of the 8.1AH between
PBX2 and HLA-DRB3. ......................................................................................... 152
8.3 Summary of the patients and markers used in previous recombination
mapping studies. ................................................................................................... 155
xiv
LIST OF FIGURES
1.1 Muscle wasting in the forearms of a patient with sIBM (Needham and
Mastaglia, 2007). ...................................................................................................... 7
1.2 Gene map for the classical and extended MHC region, along with several
HLA and non-HLA genes found throughout the region as adapted from
Horton et al., 2004. ................................................................................................. 27
1.3 Major polymorphic blocks on the MHC (Yunis et al., 2003). ............................... 30
1.4 The sIBM susceptibility region (shown in blue) in patients carrying the
8.1AH as defined by Price et al. (2004). ................................................................ 39
2.1 PCR Optimisation of the 35287_F_FAM / 35287_R_NIL primer pair. ................ 52
2.2 RFLP of rs422951 with the restriction enzyme HaeIII. ......................................... 54
3.1 The 270kb region of the MHC at which sequence data from the cell lines
COX, PGF, QBL and SSTO were aligned. ............................................................ 62
3.2 Incidence of polymorphisms within 270kb from AGER to HLA-DRA. ................. 65
4.1 Protein structure of NOTCH4. ............................................................................... 69
4.2 The diluting effect observed in alleles not specific to the disease-associated
haplotype. ............................................................................................................... 80
6.1 The 389kb sIBM susceptibility region between PBX2 and HLA-DRB1, as
found in the human MHC. ................................................................................... 113
7.1 Chromatograms for the 10IHW cell lines COX (8.1AH) and WT100BIS
(35.2AH). ............................................................................................................. 136
xv
8.1 Summary of full or partial 8.1AHs in 156 sIBM patients comprising the
combined Australian, American and German cohorts. ........................................ 148
8.2 Recombination mapping of the region spanning from PBX2 to HLA-DRB1....... 153
9.1 Three possible scenarios by which an AH can have developed an sIBM
susceptibility allele relative to other susceptibility haplotypes. ........................... 173
xvi
ABBREVIATIONS
4AOH 4th Asia-Oceania histocompatibility workshop
10IHW 10th international histocompatibility workshop
AGER Advanced glycation end product receptor
AH Ancestral haplotype
BHLHB3 Basic helix-loop-helix factor B3 gene
BTNL2 Butyrophilin-like 2
C6orf10 Chromosome 6 open reading frame 10
CK Creatine kinase
DM Dermatomyositis
DNA Deoxyribonucleic acid
fIBM Familial inclusion body myositis
GNE UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase
HCG23 HLA complex group 23
hIBM Hereditary inclusion body myositis
HLA Human leukocyte antigen
HSP70 Heat shock protein 70
IBMPFD Inclusion body myopathy with Paget disease and frontotemporal
dementia
MHC Major histocompatibility complex
MND Motor neuron diease
PBX2 Pre B-cell leukemia homeobox 2
PM Polymyositis
RFLP Restriction fragment length polymorphism
sIBM Sporadic inclusion body myositis
SNP Single nucleotide polymorphism
SSCP Single strand conformation polymorphism
TNFab Tumour necrosis factor
xvii
ACKNOWLEGEMENTS
A PhD Thesis is as much the manifestation of a three (or four) year learning process as
it is the product of an extended research project. Over the course of this work I‘ve
indeed learnt a great deal, not just in the practicalities of research, writing and critical
thinking, but also in honing my work ethic and my patience. Of course, I did have some
help along the way...
First and foremost I would like to thank my supervisors; Dr Richard Allcock, Professor
Nigel Laing and Professor Frank Mastaglia, for all their assistance, advice and
encouragement over these years.
The following people also deserve recognition;
Professor Patricia Price, for assistance early on in the project, and for being the catalyst
through which I found myself working on this PhD to start with.
Professors I. Nishino, I. Nonaka, H. Lochmeuller, M. Dalakas and Dr. M. Walter, for
their assistance in collecting samples for the Japanese, German and American cohorts.
Dr. Merrilee Needham, for the diagnosis and collection of blood samples.
Dr. Campbell Witt and Dr. Kimberly Strong and Nigel Laing‘s laboratory staff for
general help and discussions. Paula Fuller in particular deserves thanks, for her
assistance with completing the last of the laboratory work.
Tricia Singh and Linda Smallwood – the only other Masters/PhD students who
wandered the ground floor of M-Block with me.
Professor Frank Christiansen and the department of Clinical Immunology at Royal Perth
Hospital, for their HLA allele genotyping services.
The Lotterywest Biomedical Facility at Royal Perth Hospital, for the analysis of
covalently tagged microsatellites
Finally, I‘d like to thank my partner Rosalie and, of course, my family; Phillip, Gillian,
Byron Reece, Sean and Arianne, for the immense support and encouragement they
provided when I needed it most over these past years. It has been an intense ride at
times and I could not have survived it without you.
1
CHAPTER ONE
1 LITERATURE REVIEW
2
1.1 The inflammatory myopathies
The idiopathic inflammatory myopathies (IIM) are a heterogeneous group of acquired
muscle disorders primarily characterised by inflammation of the endomysium and
muscle fibre necrosis, leading to varying degrees of muscle weakness (Dalakas and
Hohlfeld, 2003; Mastaglia et al., 2003). IIMs range from focal conditions affecting a
single muscle or muscle group, to more pervasive entities that affect most of the skeletal
musculature. IIMs only rarely involve the facial and respiratory muscles and the
nervous system also remains unaffected, normal sensation in patients. Muscle weakness
is rarely acute, but rather develops over a period of weeks or years, depending on the
condition (Dalakas, 1991). While they can occur independently of other diseases, IIMs
are also often found in association with connective tissue diseases, autoimmune
disorders, retroviral infections and malignancies. IIMs are generally considered to be
immune-mediated conditions (Dalakas, 1991; Mastaglia and Walton, 1992; Ojeda and
Mastaglia, 1998; Mastaglia et al., 2003).
IIMs are subdivided pathologically and clinically into three distinct forms –
dermatomyositis, polymyositis and inclusion body myositis (Dalakas and Hohlfeld,
2003). While all three diseases exhibit muscle-specific inflammation, weakness and
wasting, each is typically defined by either a rash (dermatomyositis), intracellular
inclusions (inclusion body myositis) or neither (polymyositis). All three diseases also
exhibit different ages at onset, with DM occurring in both juvenile and adult forms,
polymyositis most often developing after the second decade of life and sporadic
inclusion body myositis rarely developing in individuals under the age of 50 (Dalakas
and Hohlfeld, 2003). However such a simplistic approach to defining each disease fails
to recognise the distinct clinical and pathological criteria that separate the three. In
reality, each disease can diverge considerably in characteristics such as age-at-onset,
pathogenesis, immune response, pattern of progression and response to treatment.
1.2 Dermatomyositis
Dermatomyositis (DM) is more common in women than men, and occurs in both
juvenile and adult forms, both of which are clinically identical aside from more frequent
secondary manifestations in juveniles than adults (Dalakas and Hohlfeld, 2003), which
include dysphagia (de Merieux et al., 1983), gastrointestinal ulcerations (Dalakas and
3
Hohlfeld, 2003), subcutaneous calcifications (Dalakas, 1995), and malignancies
(Sigurgeirsson et al., 1992).
DM is normally identified by a characteristic rash on the eyelids, face, upper trunk and
knuckles (Callen, 2000), which accompanies or often precedes the muscle weakness
(Dalakas, 1991; Callen, 2000). Muscle weakness develops symmetrically over a period
of weeks or months, starting with the proximal muscle groups and later developing in
the distal muscles such as those affecting fine motor movement, as well as the
pharyngeal and neck flexor muscles. The facial and respiratory muscles may also be
affected in rare cases (Dalakas, 1991). Serum levels of creatine kinase, an indicator of
an active myopathy, can be up to 10 times the normal level in patients with active DM,
although it can be normal in some cases. The levels of aspartate and alanine
aminotransferases, lactate dehydrogenase and aldolase are also increased (Dalakas and
Hohlfeld, 2003).
Inflammation of the skeletal muscle in DM is predominantly perifascicular or in the
interfascicular septae around, rather than within, the fascicles themselves (Dalakas,
1991). The muscle fibres undergo necrosis and phagocytosis, usually in groups and
involving the periphery of the fascicle which results in atrophy. This pattern of atrophy
is a key diagnostic feature of DM, even in the absence of inflammation (Dalakas, 1991).
DM can be difficult to distinguish from other diseases with similar clinical symptoms,
particularly subacute cutaneous lupus erythematosus, which is also characterised by a
rash and subacute calcification, although calcified lesions generally occur between the
knuckles as opposed to more bony prominences as is the case with DM (Callen, 2000).
One case report also showed a DM patient misdiagnosed with facioscapulohumeral
muscular dystrophy (Oya et al., 2001), which presents with asymmetric skeletal muscle
weakness in the face and scapular fixators, foot dorsiflexors and the hip girdles (Tawil
et al., 1998). A definite diagnosis of DM is not always possible if there is an absence of
distinctive features typical of DM, such as a rash or perifascicular atrophy. For instance,
DM patients that exhibit no skin involvement can be easily misdiagnosed with
polymyositis if the patient‘s histopathology is not clear (Amato and Griggs, 2003; van
der Meulen et al., 2003).
4
DM is considered an autoimmune disease. This is suggested by the occurrence of DM in
patients with other autoimmune disorders (Dalakas, 1988) and the genetic association
with immune-related genes in the major histocompatibility complex (O'Hanlon et al.,
2005). Autoimmunity in DM is also suggested by immune-mediated myocytoxicity, the
response to immunosuppressive or immunomodulating treatments (Miller et al., 1992;
Dalakas et al., 1993; Miller et al., 2002) and the presence of autoantibodies (Targoff,
2002).
The inflammatory infiltrates in the muscle lesions comprise B- and T-lymphocytes, with
the former predominating and a preponderance of CD4+ T-cells over CD8+ T-cells
(Arahata and Engel, 1984). The CD4+ T-cells are found in close proximity to the B-
cells and macrophages, which when combined with the absence of lymphocytic
invasion of the non-necrotic muscle fibres, suggests a mechanism mediated by humoral
processes (Arahata and Engel, 1984; Dalakas, 1991).
The autoimmune process in DM is mediated by the complement C5b-9 membranolytic
attack complex and directed against the endothelium of the endomysial capillaries and
the endomysial microvasculature (Whitaker and Engel, 1972; Carpenter et al., 1976;
Kissel et al., 1986; Emslie-Smith and Engel, 1990). This results in swollen endothelial
cells, capillary necrosis, ischemia, microinfarcts, perivascular inflammation,
endofascicular hypoperfusion and ultimately perifascicular atrophy (Dalakas, 1991).
1.3 Polymyositis
Polymyositis (PM) lacks any uniquely identifying characteristics such as the rash in DM
and is thus normally diagnosed by way of excluding other conditions (Dalakas, 1988;
Dalakas, 1991). The age at onset for PM is most often after the second decade of life
and it only very rarely occurs in children (Dalakas and Hohlfeld, 2003). PM is defined
as an inflammatory myopathy with a slow onset of weeks to months and an absence of
the following symptoms – a rash, involvement of the eye or facial muscles, a family
history of neuromuscular disease, exposure to myotoxic drugs, endocrinopathy,
neurogenic disease or any biochemical muscle disease or inclusion body myositis
(Dalakas, 1991).
Similar to DM, patients with PM show an early development of proximal muscle
weakness, with the muscles associated with fine motor movement being affected late in
5
the course of the disease (Dalakas, 1991). PM patients also exhibit increased levels of
serum creatine kinase, aspartate and alanine aminotransferases, lactate dehydrogenase
and aldolase (Dalakas and Hohlfeld, 2003).
Unlike DM, inflammation and the accompanying mononuclear cells in PM are mainly
found within the endomysium and the immune response is driven primarily by CD8+ T
lymphocytes with strong penetration of muscle fibres, as opposed to the peripheral
immune response by B-cells and CD4+ T-cells seen in DM (Arahata and Engel, 1984).
The CD8+ T-cells traverse the basal lamina to focally displace and eventually destroy
MHC-I-antigen expressing muscle fibres by perforin-induced cytotoxicity (Arahata and
Engel, 1984; Arahata and Engel, 1986; Hohlfeld and Engel, 1994). The end result is that
entire segments of muscle fibre are replaced by invading mononuclear cells.
Due to the lack of defining symptoms, PM remains an overdiagnosed disease and is
frequently misdiagnosed in patients with a wide variety of other conditions, including
DM, muscular dystrophies (congenital, facioscapulohumeral and limb-girdle) with
inflammation, connective tissue disorders and inclusion body myositis (Spuler and
Engel, 1998; Amato and Griggs, 2003; van der Meulen et al., 2003).
PM is considered to be an autoimmune disease for similar reasons to DM, particularly
the response to immunotherapies and the CD8+ T-cell driven immune response
(Dalakas, 1991).
1.4 Inclusion body myositis
Sporadic inclusion body myositis (sIBM) was initially reported as a chronic variant of
polymyositis in a case study by Chou (1967). At the time it was characterised by an age
at onset of over 40 years with a slowly progressive weakness of skeletal muscle,
specifically the quadriceps, accompanied by intracellular inclusions with microtubular
structures and transverse striations (Chou, 1967; Sato et al., 1971). In 1971, Yunis and
Samaha introduced the term ‗inclusion body myositis‘ and theorised that it could be a
disease entity distinct from PM (Yunis and Samaha, 1971). This was later confirmed
(Carpenter et al., 1978). Over the past thirty years, sIBM has been established as a
distinct disease entity.
6
1.4.1 Onset and frequency of sIBM
The age at onset for most patients diagnosed with sIBM is normally above 50 years and
it is the most common acquired muscle disease occurring in individuals of that age
group in Caucasians (Griggs et al., 1995; Tawil and Griggs, 2002; Oldfors and
Lindberg, 2005; Dalakas, 2006). sIBM is more prevalent in males than females by a
ratio of approximately 1.8:1, and is more prevalent in Caucasian populations such as
those in North America, Northern Europe and Australia than other ethnic groups
(Badrising et al., 2000; Phillips et al., 2000; Shamim et al., 2002; Needham and
Mastaglia, 2007).
The incidence of sIBM in the Netherlands was reported at 4.3 patients per million,
although this was considered to be an underestimation due to the difficulties in
diagnosing sIBM (Badrising et al., 2000). A study in Connecticut gave an incidence of
10.7 per million (Felice and North, 2001) while another in Western Australia gave a
similar incidence of 9.3 patients per million, increasing to 35.3 per million when only
considering patients and healthy individuals aged 50 years and over (Phillips et al.,
2000). The most recent survey gave a prevalence of sIBM in Western Australia of 13
patients per million, increasing to 39.5 per million for individuals over 50 years
(Needham and Mastaglia, 2007). While there appears to be an increase in incidence
over eight years, a proportion of the new cases since 1998 are likely to have been
previously misdiagnosed, probably as polymyositis (van der Meulen et al., 2003).
1.4.2 Clinical and pathological features of sIBM
The overt clinical symptoms of sIBM include a slowly progressive, selective and
usually painless chronic inflammation, muscular weakness and atrophy in the proximal
lower and distal upper limbs, specifically the quadriceps, forearm muscle compartment
and the wrist and finger flexors (Lotz et al., 1989; Dalakas, 1991). This makes it
difficult for the patient to ambulate safely. Muscle atrophy in patients can be symmetric
or asymmetric and is often visually striking with thin, atrophic quadriceps muscles and a
scooped out appearance of the medial aspect of the forearms (Dalakas, 1991; Tawil and
Griggs, 2002) (Figure 1.1). Weakness of the muscles involved in swallowing can occur
in up to 60% of patients, which can lead to dysphagia (Lotz et al., 1989; Felice and
North, 2001; Oldfors and Lindberg, 2005; Dalakas, 2006). The triceps generally remain
unaffected by the disease, as does non-skeletal muscle and nervous tissue (Dalakas,
1991; Tawil and Griggs, 2002).
7
Figure 1.1: Muscle wasting in the forearms of a patient with sIBM (Needham and
Mastaglia, 2007).
As a result of muscle weakness, patients report increasing difficulty with everyday tasks
requiring the use of the affected muscles. These include standing up from a sitting
position, climbing steps and lifting objects, as well as fine-motor movements such as
buttoning up a shirt or writing (Dalakas, 1991).
The characteristic pathological features of sIBM include multifocal invasion of non-
necrotic fibres primarily by CD8+ T-lymphocytes and macrophages along with
endomysial inflammation, which is believed to be driven by the muscle fibre expression
of MHC class I molecules (Arahata and Engel, 1984; Karpati et al., 1988; Dalakas,
1991; Askanas and Engel, 1998b; Dalakas, 2006). Muscle fibres contain irregular-sized
intracellular vacuoles with basophilic granules, which may exhibit a ‗rimmed‘
appearance (Chou, 1993; Askanas and Engel, 2001). Cytoplasmic collections of 6-10nm
amyloid-like filaments are also present, as well as cytoplasmic and intranuclear
tubulofilamentous inclusions 15-21nm in diameter, also referred to as paired helical
filaments (Chou, 1993; Askanas and Engel, 2001; Dalakas, 2006). The inclusions stain
positively for ubiquitin and contain multiple proteins, including alpha-1-
antichymotrypsin, apolipoprotein E, presenilin-1 and epitopes of beta-amyloid precursor
protein (APP) and either phosphorylated tau or -amyloid (Askanas and Engel, 1998b;
Askanas and Engel, 2003). Abnormal mitochondria, as demonstrated by ragged-red
8
muscle fibres and cytochrome-c-oxidase negative muscle fibres, are found at an
increased frequency in sIBM patients (Askanas and Engel, 2001; Dalakas, 2006).
1.4.3 Diagnosis of sIBM
Since the identification of sIBM as a distinct clinical entity (Yunis and Samaha, 1971;
Carpenter et al., 1978), multiple papers have been published on the clinical and
histological characteristics of the disease (Dalakas, 1991; Sayers et al., 1992; Sekul and
Dalakas, 1993). These observations were collated by Griggs et al. (1995) into a
comprehensive set of diagnostic criteria for identifying sIBM, which have mostly
remained consistent over time. Additions to the diagnostic criteria by subsequent
reviews have included the presentation of MHC Class I expression in muscle fibres
(Oldfors and Lindberg, 2005; Dalakas, 2006; Needham and Mastaglia, 2007) and the
consideration of other disorders associated with sIBM (Needham and Mastaglia, 2007).
The diagnostic criteria for sIBM are summarised in Table 1.1.
Individuals suspected of sIBM are most commonly over 50 years old, with an early
onset of muscle weakness in quadriceps femoris and finger flexors (Needham and
Mastaglia, 2007). Weakness in the wrist flexors, knee extensors and ankle dorsiflexors
usually occur early in sIBM – which is in contrast to the more proximal weakness found
in DM and most PM patients (Amato et al., 1996). Although elevated serum creatine
kinase can be an indicator of damage to muscle tissue (Kagen and Aram, 1987), levels
in sIBM patients may be normal to as much as 5-fold elevated (Dalakas, 1991; Tawil
and Griggs, 2002; Mastaglia et al., 2003).
9
Table 1.1: Diagnostic criteria for sIBM, as defined by Needham and Mastaglia (2007).
______________________________________________________________________
Characteristic features
Clinical features
Duration of illness >6 months
Age at onset >30 years
Slowly progressive muscle weakness and atrophy: selective pattern with early involvement
of quadriceps femoris and finger flexors, although can be asymmetric
• Dysphagia is common
Laboratory features
Serum creatine kinase concentration might be high but can be normal
Electromyography: myopathic or mixed pattern, with both short and long duration motor
unit potentials and spontaneous activity
Muscle biopsy
Myofibre necrosis and regeneration
Endomysial mononuclear cell infiltrate (of variable severity)
Mononuclear cell invasion of non-necrotic fibres: predominately CD8+ T cells
MHC class I expression in otherwise morphologically healthy muscle fibres
Vacuolated muscle fibres (rimmed vacuoles)
Ubiquitin-positive inclusions and amyloid deposits in muscle fibres
Nuclear and/or cytoplasmic 16–20nm filamentous inclusions on electron microscopy
COX-negative fibres (excessive for age)
Associated disorders
Inclusion body myositis usually occurs in isolation, but can be associated with:
Other autoimmune disorders or connective tissue diseases
Occasional: HIV, HTLV-I, and hepatitis C infection
Rare: toxoplasmosis, sarcoidosis, post-poliomyelitis, amyotrophic lateral sclerosis
Diagnostic categories
Definite inclusion body myositis
Characteristic clinical features, with biopsy confirmation: inflammatory myopathy with
autoaggressive T cells, rimmed vacuoles, COX-negative fibres, amyloid deposits or
filamentous inclusions and upregulation of MHC-I expression. The presence of other
laboratory features are not mandatory if the biopsy features are diagnostic
Atypical pattern of weakness and atrophy but with diagnostic biopsy features
Probable inclusion body myositis
Characteristic clinical and laboratory features but incomplete biopsy criteria – eg, features
of necrotising inflammatory myopathy with T cell invasion of muscle fibres but absence of
rimmed vacuoles, amyloid deposits, filamentous inclusions, and COX negative fibres
Possible inclusion body myositis
Atypical pattern of weakness and incomplete biopsy criteria
______________________________________________________________________
10
A definitive diagnosis of sIBM requires a muscle biopsy, by which the characteristic
features of sIBM can be identified. These features include intracellular vacuoles, the 15-
21nm tubulofilamentous inclusions with β-amyloid and phosphorylated tau, as well as
the invasion of non-necrotic muscle fibers by mononuclear cells.
Diagnosis of sIBM can be facilitated by Congo-red staining of the muscle biopsy
specimen, which causes the amyloid inclusions to fluoresce (Askanas et al., 1993b). The
monoclonal antibody SMI-31 can be used to identify the tubulofilamentous inclusions
with phosphorylated tau (Askanas et al., 1996a). Failing that, antibodies specific to
ubiquitin recognise the ubiquitinated tubulofilaments in sIBM-affected muscle fibres,
which will effectively differentiate sIBM from PM or DM (Askanas et al., 1992b). The
invasion of mononuclear cells and the presence of ragged-red fibres can be visualised
by Engel-Gomori trichrome staining (Engel and Cunningham, 1963; Askanas and
Engel, 2001). Immunohistochemical staining can also characterise the mononuclear cell
infiltration, as well as show MHC Class I expression in muscle fibres (Needham and
Mastaglia, 2007). Together, these techniques are able to effectively identify the most
characteristic features of sIBM muscle histology.
1.4.4 Differential diagnosis
Difficulty in diagnosing sIBM occurs when patients do not demonstrate the most
characteristic pathological features of sIBM (Chahin and Engel, 2008), specifically the
inflammatory myopathy with vacuolated muscle fibres, and tubulofilamentous
inclusions. The histological component of sIBM can be missed in some specimens,
particularly from biopsy sampling error due to the multifocal nature of the histological
abnormalities (Amato et al., 1996; Tawil and Griggs, 2002). Some of the muscle biopsy
features characteristic for sIBM may also appear later in some patients, preventing a
definite diagnosis and possibly making sIBM indistinguishable from other inflammatory
myopathies (Tawil and Griggs, 2002; Chahin and Engel, 2008). This can be minimised
by also considering clinical as well as pathological criteria in the diagnosis of sIBM
rather than relying on a muscle biopsy for initial diagnosis of a patient (Tawil and
Griggs, 2002).
sIBM can easily be misdiagnosed as PM, especially if out-dated diagnostic criteria are
used (van der Meulen et al., 2003). In particular the guidelines in the review published
by Bohan and Peter (1975) have been utilised by some for diagnosing PM and DM.
11
However the criteria give no consideration to sIBM (Bohan and Peter, 1975), which at
the time, was only just being accepted as a clinical entity distinct from PM (Yunis and
Samaha, 1971; Carpenter et al., 1978). In effect, an sIBM patient would thus be
misdiagnosed with PM if the criteria of Bohan and Peter (1975) are used exclusively for
diagnosis. The criteria of Bohan and Peter have nevertheless been used for diagnosing
patients with inflammatory myopathies as late as 2003 (Miller et al., 2003; van der
Meulen et al., 2003). Patients initially diagnosed with PM may be suspected of having
sIBM later if they fail to respond to treatment with corticosteroids and anti-
inflammatory drugs (Dalakas, 1991). In such cases, a second muscle biopsy may be
required to re-assess the patient‘s histology (Amato et al., 1996).
Patients with inclusion body myositis may also be misdiagnosed with motor neuron
disease (MND) – a group of neurodegenerative disorders. In one study, 9 out of 70
sIBM patients were initially diagnosed with MND before a muscle biopsy was
examined (Dabby et al., 2001). The clinical and electromyographic differences between
MND and sIBM are normally clear, but atypical features in some patients can cause
confusion. MND-like features sometimes seen in sIBM include dysphagia and
fasciculation. More critically, routine electromyographic studies in sIBM patients can
also show fibrillation potentials and positive sharp waves, consistent with a neurological
disorder (Lotz et al., 1989; Dabby et al., 2001). Patients initially misdiagnosed with
MND may be suspected of having sIBM if the disease progression is unusually slow
and if a disproportionate weakness of the finger flexor muscles is observed. In such
instances a muscle biopsy is necessary to confirm a diagnosis of sIBM (Dabby et al.,
2001).
1.4.5 Progression of sIBM
sIBM is a slowly progressing but relentless disease, with affected muscles deteriorating
over a period of years. The rate of progression is directly proportional to the patient‘s
age at disease onset, such that individuals with an earlier age at onset deteriorate more
slowly than those who develop the disease later on in life (Peng et al., 2000). As the
disease progresses, increased difficulty with ambulation, standing and walking forces
patients to rely on a cane, followed by a walker before they are eventually confined to a
wheelchair (Peng et al., 2000).
12
Patients with sIBM normally die of other causes associated with older age, although
fatalities from aspiration pneumonia, which is often related to dysphagia, may be
directly related to sIBM (Peng et al., 2000).
1.4.6 Treatment of sIBM
The progression of sIBM appears to be relentless, and there is no established treatment
that can consistently reverse, arrest, or even slow the disease progression for a
prolonged period (Griggs, 2006). Treatments involve addressing the inflammatory
component of the disease through the use of corticosteroids such as prednisone,
although there has been only limited evidence that such an approach is beneficial
(Griggs, 2006). One trial involving eight patients treated with prednisone showed that
all patients worsened in average muscle strength, in spite of a fall in creatine kinase
levels. Biopsies taken before and after treatment showed that the number of amyloid-
containing fibres actually increased, in spite of a reduction in T-cell levels coincident
with prednisone use (Barohn et al., 1995). Such an observation serves to highlight that
the level of creatine kinase, and thus an active myopathic process, is not an accurate
indicator of sIBM progression in patients. When a patient shows no response to
corticosteroids alone, cytotoxic drugs are often added to the treatment. The response to
most cytotoxic drugs has not been significant in the small numbers reported (Griggs,
2006).
Immune-modulating therapies such as total body irradiation and leukapheresis (Kelly et
al., 1986; Dau, 1987) have not proven successful. Trials with intravenous
immunoglobulin (IVIg), an effective immunomodulatory agent, initially showed
varying success in case studies (Soueidan and Dalakas, 1993; Amato et al., 1994).
Subsequent randomised controlled studies revealed modest improvements in clinical
symptoms for patients treated with IVIg, although the long term benefits and thus the
justification for such a high-cost treatment remain unclear (Dalakas et al., 1997b;
Walter et al., 2000; Raju and Dalakas, 2005).
Various studies and case reports have shown patients to stabilise or improve with
treatment, sometimes dramatically (Soueidan and Dalakas, 1993), yet in most cases the
results must be interpreted cautiously. sIBM may stabilise or improve for 6 months or
more in one third of patients (Rose et al., 2001) – an observation that can be mistaken
for a response to treatment. sIBM can also be associated with autoimmune diseases,
13
some of which respond to immune modulating and immunosuppressive treatments
(Dalakas and Illa, 1995; Koffman et al., 1998a; Tawil and Griggs, 2002; Badrising et
al., 2004; Hama et al., 2004). Care must therefore be taken to ensure that an
improvement in symptoms is not the result of inadvertently treating an associated
disease. As there is no definitive diagnostic test for sIBM, there is also the possibility
that the disease is heterogeneous, with patient subsets showing different responses to
treatment (Wenzel et al., 2001; Griggs, 2006).
Despite the difficulties in finding an effective treatment for sIBM, there have been a
number of studies that have shown some success. One trial involving the treatment of
19 patients with the steroid oxandrolone showed a ‗borderline significant‘ improvement
in whole-body muscle strength over a relatively short time frame of 12 weeks (Rutkove
et al., 2002). Treatment with anti-T-lymphocyte globulin has also shown some success,
with some improvement in muscle strength in sIBM patients (n=6) over 12 months,
compared to a drop in strength after treatment with methotrexate (n=5) (Lindberg et al.,
2003). Despite the limited patient numbers, these results do show some promise.
1.4.7 sIBM and comorbid diseases
sIBM can be associated with connective tissue diseases as well as cardiovascular
diseases and peripheral neuropathies (Lotz et al., 1989; Tawil and Griggs, 2002). sIBM
may present with other autoimmune disorders in up to 33% of patients (Koffman et al.,
1998a; Brouwer et al., 2001; Badrising et al., 2004), including systemic lupus
erythematosus, dermatomyositis, scleroderma, sarcoidosis, autoimmune thyroid disease,
rheumatoid arthritis, type I diabetes mellitus, Sjogren disease, pernicious anemia,
dermatitis herpetiformis, common variable immunodeficiency and psoriasis. sIBM
patients may also have elevated levels of non-disease specific autoantibodies (Koffman
et al., 1998a; Brouwer et al., 2001; Badrising et al., 2004; Hama et al., 2004).
Although sIBM is not generally considered as a precursor to malignancy, one study has
demonstrated an increased risk of malignancies in patients with sIBM similar to that of
polymyositis (Buchbinder et al., 2001).
14
1.5 Hereditary inclusion body myopathies
The hereditary inclusion body myopathies (hIBMs) are a group of muscle diseases with
both similar clinical and pathological features to sIBM, yet appear to have a different
pathogenesis. Unlike sIBM, the quadriceps in hIBM patients are spared from muscle
weakness (Askanas, 1997). There is normally no immune component in hIBM, with no
lymphocytic mononuclear cell infiltration present (Askanas, 1997; Askanas and Engel,
1998a). The age at onset for hIBM is normally the second or third decade of life, as
opposed to the sixth decade or later as observed with sIBM (Askanas and Engel, 1998a;
Tome and Fardeau, 1998). Table 1.2 provides a summary of the pathological similarities
and differences between sIBM and hIBM (Askanas and Engel, 1998a).
15
Table 1.2: Pathological comparison between sIBM and hIBM. Adapted from Askanas
and Engel (1998).
Pathological Features sIBM hIBM ___________________________________________________________________________________________
Similarities
Vacuolated muscle fibres + +
Ubiquitina + +
β-Amyloid precursor proteina + +
β- Amyloid precursor protein mRNA + +
Prion proteina + +
Prion protein mRNA + +
Neuronal nitric oxide synthasea + +
Inducible nitric oxide synthasea + +
Phosphorylated taua with antibodies
SMI-31 + +
AT8 + +
Differences
Inflammation + -
Ragged-red fibres + -
Cytochrome c oxidase-negative muscle fibres + -
Congo red staining + -
Phosphorylated taua with antibodies
SMI-310 + -
PHF-1 +b +
c
Apoliprotein Ea +
b +
c
Nitrotyrosinea +
b +
d
___________________________________________________________________________________________
‗+‘ indicates positive reaction or presence, ‗-‘ indicates negative reaction or absence.
a indicates immunoreactivity
b Defined inclusions
c Diffuse
d Multiple dots
16
Patients with hIBM can be subdivided according to their mode of inheritance, being
either autosomal recessive or autosomal dominant (Tome and Fardeau, 1998).
Autosomal recessive hIBM has a high incidence in Jews of Middle Eastern descent and
has been associated with mutations in the UDP-N-acetylglucosamine 2-epimerase/N-
acetylmannosamine kinase (GNE) gene on chromosome 9p12-13 (Tome and Fardeau,
1998; Eisenberg et al., 2001). GNE is a bifunctional enzyme that regulates and initiates
the biosynthesis of N-acetyl-neuramic acid, and is the rate-limiting enzyme in the sialic
acid biosynthetic pathway. Sialic acid modification of cell surface glycoproteins and
glycolipids is crucial for the normal functioning of processes such as cell adhesion and
signal transduction (Keppler et al., 1999).
Autosomal dominant hIBM has been found in multiple different ethnic groups (Neville
et al., 1992; Sivakumar and Dalakas, 1996; Darin et al., 1998; Rodolico et al., 2005).
The only genetic association found for autosomal dominant hIBM has been with a
missense mutation in the myosin heavy chain IIa gene (Martinsson et al., 2000),
although association with this locus is not common to all families with autosomal
dominant hIBM (Rodolico et al., 2005). The mutation itself is a non-synonymous
glutamine to lysine change located in the core of the myosin head, which results in a
dysfunctional myosin protein (Martinsson et al., 2000). The protein is the primary
myosin of type IIa muscle fibres, which are selectively involved in young autosomal
dominant hIBM patients, although all muscle fibre types are affected in adult,
progressive patients (Martinsson et al., 2000). The mechanism by which the myosin
heavy chain IIa mutation could cause hIBM remains unknown.
The dominant and recessive forms of hIBM follow different patterns of weakness, with
distal lower extremity weakness and a relative sparing of the quadriceps for autosomal
recessive hIBM, and a more variable pattern of weakness in autosomal dominant hIBM.
(Tome and Fardeau, 1998).
A similar condition to autosomal recessive hIBM has been observed in Japanese
patients, and labelled Nonaka myopathy. This disease is an autosomal recessive distal
myopathy that shows highly similar muscle pathology to autosomal recessive hIBM,
with the same spectrum of abnormal proteins within the vacuolated muscle fibres
(Murakami et al., 1995; Askanas, 1997). A genetic association for Nonaka myopathy
has been localised to the same gene as autosomal recessive hIBM, GNE, leading to the
17
understanding that the two diseases are associated with alleles from the same gene
(Nishino et al., 2002).
One other disease similar to hIBM is inclusion body myopathy with Paget disease and
frontotemporal dementia (IBMPFD) (Kimonis et al., 2008). Similar to other IBMs, the
disease is characterised by a progressive proximal muscle weakness, and rimmed
vacuoles and cytoplasmic inclusions can be seen histologically. However IBMPFD also
exhibits motor neuron degeneration, Paget disease in bones and the eventual onset of
dementia (Kimonis et al., 2008). IBMPFD is an autosomal dominant disease caused by
a mutation in the gene encoding the valosin-containing protein (Watts et al., 2004).
Despite some common mechanisms, sIBM, autosomal dominant hIBM, autosomal
recessive hIBM/Nonaka myopathy, and IBMPFD appear to be distinct conditions with
different mechanisms of pathogenesis. This is especially evident when considering the
genetically disparate susceptibility genes for the hIBMs and IBMPFD.
hIBM can be misdiagnosed as familial inclusion body myositis (fIBM). Unlike hIBM,
fIBM is clinically and histologically identical to sIBM and is differentiated from sIBM
by its presence in multiple members of the same family (Mizusawa, 2003). sIBM and
fIBM are considered the same disease, and are addressed in more detail in Section
1.6.4.1.
Aside from the varying pattern of muscle weakness and the absence of an autoimmune
component in hIBM, both fIBM and hIBM show a similar disease pathology and it has
thus been theorised that they may share a common downstream pathologic cascade,
initiated by different pathogenic mechanisms (Askanas and Engel, 1998a). However
unlike fIBM, neither autosomal dominant nor autosomal recessive hIBM show a
significant genetic association with the alleles of the immune-related human leukocyte
antigen (HLA) genes, specifically HLA-DRB1 and HLA-DQB1 (Koffman et al., 1998b).
1.6 The Pathogenesis of sIBM
The pathogenesis of sIBM is currently unknown, although several hypotheses have been
advanced and pursued. These include viral infection, autoimmunity, -amyloid
18
accumulation and genetic susceptibility mediated by alleles of genes in the human major
histocompatibility complex (MHC).
1.6.1 Viral Infection
When sIBM was initially identified, the tubulofilamentous inclusions were thought to
resemble an incomplete form of myxovirus (Chou, 1967). It was thus initially theorised
that the condition could be the result of a chronic viral infection and subsequently,
chronic mumps virus infection (Nishino et al., 1989). The failure to demonstrate
antibody binding to any mumps virus antigen from sIBM patient muscle or sera has cast
doubt on a disease pathogenesis driven by the mumps virus (Nishino et al., 1989).
There has been a consistent lack of evidence for viral components associated with
sIBM-affected muscle, with the only exception thus far being a strain of adenovirus type
2 identified in muscle biopsy specimens of a single sIBM patient (Mikol et al., 1982).
However, the theory of a chronic viral infection influencing sIBM pathogenesis is
supported by a number of observations. In several reports, sIBM has been associated
with human T-cell leukaemia/lymphoma virus type 1 (HTLV-1) infection, as well as
human immunodeficiency virus (HIV)-infection (Cupler et al., 1996; Ozden et al., 2001;
Littleton et al., 2002; Loutfy et al., 2003; Ozden et al., 2004; Warabi et al., 2004;
Dalakas et al., 2007). In all cases the patients demonstrated typical symptoms for sIBM.
However the age at onset for sIBM was often lower, with a mean of 44 years for sIBM
patients with HIV and 35 years for those with HTLV-1 (Dalakas et al., 2007).
Furthermore, in HIV-positive sIBM patients a subpopulation of autoinvasive CD8+ T-
cells specific for viral components are initially recruited in the muscle (Ozden et al.,
2004; Dalakas et al., 2007).
Neither HTLV-1 nor HIV has been detected within skeletal muscles of the sIBM
patients. Furthermore the CD8+ T-cells, regardless of whether they are virus specific,
are not clonally expanded within the muscle fibres (Lindberg et al., 1994; Cupler et al.,
1996). This led to the hypothesis of a virus-initiated autoimmune disease pathogenesis
for sIBM. In such an event, a retroviral infection would trigger CD8+ T-cells sensitised
against some cross-reacting component within the skeletal muscle. This could result in
an inflammatory response within the muscle that leads to disease initiation (Cupler et
al., 1996; Dalakas et al., 2007).
19
The earlier age at onset for retrovirus-infected sIBM patients suggests that a viral
component can influence the pathogenesis of sIBM in some individuals. The possibility
that a virus could trigger sIBM pathogenesis through interference with
immunoregulatory mechanisms, inducing cytokine release and antigen expression in
muscle, or through molecular mimicry cannot be excluded.
1.6.2 Autoimmunity
The possible influence of retroviruses is not the only evidence that supports an immune-
mediated disease pathogenesis for sIBM. As shown in Table 1.3, there are numerous
observations that support such a hypothesis.
Table 1.3: Supporting evidence for an immunopathogenic disease mechanism for sIBM,
adapted from Dalakas (2006). __________________________________________________________________________________________________________
1. Association with HIV and HTLV-1 retroviral infection (Cupler et al., 1996; Dalakas
et al., 2007).
2. Autoinvasive CD8+ T cells surrounding the MHC Class I expressing muscle fibres
(Arahata and Engel, 1984; Karpati et al., 1988).
3. Upregulation of cytokines and their receptors (De Bleecker et al., 2002; Figarella-
Branger et al., 2003; Raju et al., 2003).
4. Association with other autoantibodies and autoimmune disorders (Koffman et al.,
1998a; Badrising et al., 2004; Hama et al., 2004).
5. Increased incidence of paraproteinemias in sIBM patients – an indicator of disturbed
immunoregulation (Dalakas et al., 1997a).
6. Genetic association with HLA alleles on the major histocompatibility complex.
__________________________________________________________________________________________________________
Unlike normal muscle fibres, the fibres in sIBM patients ubiquitously over-express
MHC Class I antigen and the costimulatory molecules BB1, inducible co-stimulatory
molecule and CD40 (Karpati et al., 1988; Murata and Dalakas, 1999; Wiendl et al.,
2003; Schmidt et al., 2004). Together with the secretion of cytokines, this facilitates the
CD8+ T-cells and macrophages in focally surrounding and invading non-necrotic
muscle fibres, leading to necrosis via the perforin pathway (Arahata and Engel, 1984;
Arahata and Engel, 1986; De Bleecker et al., 2002; Figarella-Branger et al., 2003; Raju
et al., 2003; Schmidt et al., 2004). The muscle fibres therefore act as an active
20
modulator to T-cell invasion in the role of an antigen presenting cell, rather than as a
passive target (Dalakas, 2006).
The variable (Vβ) region of the T-cell receptor genes in sIBM patients exhibit a
restricted pattern of gene rearrangement, which suggests that activation is driven by a
specific antigen (Lindberg et al., 1994; Amemiya et al., 2000). In sIBM patients,
expansion of several Vβ subfamilies is restricted to T-cells in the muscle, suggesting an
in situ expansion (Dimitri et al., 2006; Dalakas et al., 2007; Salajegheh et al., 2007).
Furthermore, the degree of restriction is maintained over a period of years within the
affected muscles (Salajegheh et al., 2007), which suggests a consistent activation of the
immune response by an antigen located within the skeletal muscle. Given that the
antigenic targets of the adaptive immune system in sIBM patients are unknown,
antigen-specific approaches to neutralise the immune response have not been possible
(Steinman, 2006).
The association of sIBM with definitive autoimmune disorders suggests that a common
mechanism, possibly immune-related, may increase susceptibility to both. In addition,
the inflammatory profile of sIBM patients, dominated by CD8+ T-cells and
macrophages, is identical to that of PM, which is considered an immune mediated
disease (Arahata and Engel, 1984; Tawil and Griggs, 2002).
sIBM is associated with specific HLA alleles of the MHC on chromosome 6, in
particular the 8.1 ancestral haplotype (Garlepp et al., 1998; Koffman et al., 1998b;
Lampe et al., 2003; Badrising et al., 2004; Price et al., 2004), which is also associated
with a multitude of autoimmune diseases (Price et al., 1999).
All of the points in Table 1.3 support a model of autoimmune pathogenesis for sIBM.
However a complicating factor in such a hypothesis is the limited success in slowing the
progression of muscular degeneration in sIBM patients with immunomodulating and
immunosuppressive therapies. This suggests that the inflammatory component may play
a less critical role in the pathogenesis of the disease and acts in response to an as yet
unknown antigen, such as a viral protein or abnormal muscle protein (Askanas and
Engel, 2003). Nevertheless, some case studies do show positive responses to
immunosuppressive or immunomodulatory treatment (Joffe et al., 1993; Soueidan and
Dalakas, 1993; Naumann et al., 1996; Rutkove et al., 2002). Much like multiple
21
sclerosis, which has also been unresponsive to such treatments (Coles et al., 2006;
Confavreux and Vukusic, 2006; Metz et al., 2007), this does not disqualify the immune
system in playing a role in the pathogenesis of sIBM. Rather, it emphasises the
likelihood that other processes, possibly an unconventional immune response may play
an important part in either sIBM pathogenesis or the limited efficacy of current
therapies.
One other key observation in sIBM patients that complicates the theory of an immune-
mediated pathogenesis is that the muscle fibres invaded by T-cells are never vacuolated.
sIBM without the immune component is similar to hIBM, which exhibits much of the
degenerative characteristics, but none of the inflammation and mononuclear cell
infiltration found with sIBM. This implies the presence of two parallel and possibly
independent processes. The first is the immunopathological process, driven by CD8+ T
cells and macrophages responding to a specific antigen localised within the skeletal
muscle. The second is the degenerative process, evident by the vacuolated muscle fibres
and considered independent from the autoimmune process by its lack of interaction with
CD8+ T cells (Dalakas, 2004; Needham and Mastaglia, 2007).
1.6.3 -Amyloid accumulation
There is a considerable body of accumulated evidence about the degenerative process
within sIBM muscle, which is characterised by vacuolated muscle fibres and the
intracellular deposition of congo-red positive amyloid protein, -amyloid-related
proteins and oxidative stress proteins. A role for -amyloid in the pathology of sIBM
was first proposed in the early 1990s, when it was found that -amyloid, and the C-
terminal and N-terminal regions of -amyloid precursor protein (APP) were
abnormally accumulated in the muscle fibres of sIBM patients (Mendell et al., 1991;
Askanas et al., 1993a). -amyloid, is a 39-42 amino acid peptide formed by proteolytic
cleavage of APP (Selkoe, 1994). Before its discovery in sIBM patients, the
accumulation of -amyloid was thought to be unique to the brain and cerebral vessels
(Askanas et al., 1993a).
Later studies found that the muscle fibre pathology in sIBM is strikingly similar to
Alzheimer‘s disease pathology, the most common form of elderly dementia. In addition
to -amyloid and APP, both Alzheimer‘s disease and sIBM show an abnormal
22
accumulation of phosphorylated tau, a1-antichymotrypsin, apolipoprotein E, ubiquitin,
presenilin 1, and cellular prion protein (Askanas and Engel, 1998a; Askanas and Engel,
2006).
Of the accumulated proteins common to sIBM and Alzheimer‘s disease, it is -amyloid
and APP that have received the most attention. -amyloid is the primary component of
the senile plaques that are deposited extracellularly in Alzheimer‘s disease brain tissue,
and it appears to be the major causative element of the neurodegenerative process in
Alzheimer‘s disease (Masters et al., 1985; Hardy and Selkoe, 2002). This is supported
by the genetic association between Alzheimer‘s disease and presenilin 1, presenilin 2
and APP, all of which are closely involved with the regulation of APP expression
(Citron et al., 1992; Scheuner et al., 1996; Nilsberth et al., 2001). Despite the
differences in organ specificity and the extracellular deposition of the plaques in
Alzheimer‘s disease, the role of -amyloid in the pathogenesis of Alzheimer‘s disease
suggests that the protein may also play a role in the pathogenesis of sIBM.
Evidence for a role of APP, fragments of APP, -amyloid, or all three in the
degenerative aspect of sIBM is supported by multiple studies. The appearance of -
amyloid-positive, noncongophilic deposits precedes vacuolation in sIBM muscle fibres,
which suggests that the accumulation of -amyloid in muscle fibres is an upstream
event in disease progression (Askanas et al., 1992a; Murphy and Golde, 2006). APP
mRNA is also increased in the disease state (Sarkozi et al., 1996).
Direct transfer of the APP gene into normal cultured human muscle induces some
aspects of the sIBM disease phenotype within the muscle fibre. This includes
congophilic inclusions with myelin-like whorls, dense cytoplasmic bodies, clusters of 6-
10nm diameter filaments, and 15-18nm diameter tubulofilamentous inclusions within
the nuclei, but not the cytoplasmic paired helical filaments normally found in sIBM
muscle fibres (Askanas et al., 1997). Another study observed the effects of APP
overexpression in the skeletal muscle of transgenic mice. In those mice older than 10
months, intracellular immunoreactivity to APP and its derivatives was observed. This
led to a range of histopathological and clinical symptoms that resembled various facets
of sIBM pathology, including muscle weakening, inflammation and the characteristic
amyloid deposition in skeletal muscle (Sugarman et al., 2002). The results mirrored not
23
only the degenerative changes but also some of the immune profile and the age-related
aspect of sIBM. While the observed changes resulting from APP overexpression in
these papers are not a complete model of the disease, it has been interpreted as
suggesting a causal role of APP in sIBM (Murphy and Golde, 2006).
Several proteins associated with processing APP into the various -amyloid isoforms
are either overexpressed and/or are found in close association with -amyloid in sIBM
patients. These include beta-site APP cleaving enzymes 1 and 2, nicastrin and presenilin
(Askanas and Engel, 2001; Vattemi et al., 2001; Askanas and Engel, 2002; Askanas and
Engel, 2003; Vattemi et al., 2003). -amyloid itself appears to accumulate in the
congophilic muscle fibres of sIBM patients as the isoform -amyloid-42, which is much
more cytotoxic than the alternative isoform -amyloid-40. The latter is rarely seen
within the inclusions (Askanas and Engel, 2006).
The protein aggregates that form the inclusions in sIBM muscle fibres may be the result
of misfolded and unfolded polypeptides that interfere with the binding of normal
cellular proteins (Ellis and Pinheiro, 2002; Askanas and Engel, 2006). Protein
misfolding occurs as a result of multiple factors, including an aging cellular
environment and oxidative stress. Evidence for both factors is found in sIBM. While it
is known that cellular aging promotes accumulation and slow degradation of abnormal
proteins, research into the exact influence on sIBM pathology has been limited
(Sherman and Goldberg, 2001). Oxidative stress results from the accumulation of -
amyloid and nitric oxide synthase, which accumulates in the sIBM muscle fibre to
produce nitric oxide and subsequently nitrotyrosine, resulting in the impairment of
protein functions (Beckman and Koppenol, 1996; Yang et al., 1996; Butterfield, 1997).
Other known indicators of oxidative stress are malondialdehyde – a product of lipid
peroxidation and nuclear factor-B, which is accumulated on the cytoplasmic paired
helical filaments of sIBM muscle fibres (Askanas and Engel, 1998b; Yang et al., 1998).
The role of misfolded proteins in sIBM is reinforced by a recent study into mutant
ubiquitin (UBB+1
), which is the result of a non-DNA-encoded dinucleotide deletion
within the mRNA (Fratta et al., 2004). Ubiquitin is normally involved in the
degradation of short-lived normal, misfolded and otherwise damaged proteins through
the ―ubiquitin-proteosome system‖ (Ciechanover and Brundin, 2003). It was found that
24
all ten of the sIBM patient muscle biopsies studied showed evidence of UBB+1
. The
paper suggested that UBB+1
would inhibit the ubiquitin-proteosome system, resulting in
the accumulation of misfolded and otherwise cytotoxic proteins, including the -
amyloid found in sIBM-affected muscle fibres (Fratta et al., 2004). This suggests a
strong link between sIBM, the dysfunction of ubiquitin and by extension, the
accumulation of misfolded proteins.
The ability of -amyloid and APP to generate sIBM-like muscle pathology suggests
that errors in the expression of these proteins are an upstream event that induces other
abnormalities found within sIBM-affected muscle fibres, such as tau phosphorylation,
oxidative stress, endoplasmic reticulum stress and inhibition of the ubiquitin-
proteosome system. This would further augment normal signal transduction and
transcription of APP and effectively create a self-perpetuating destructive mechanism
(Askanas and Engel, 2006). It is thus possible that the expression of APP is a key
upstream mechanism in the pathogenic cascade of sIBM.
However, if -amyloid were to play a central role in the pathogenesis of sIBM, one
might expect that patients with Alzheimer‘s disease would show an increased
susceptibility to sIBM and vice versa (Murphy and Golde, 2006). Despite multiple
studies into the diseases co-presenting with sIBM, no study thus far has identified such
an association (Koffman et al., 1998a; Felice and North, 2001; Badrising et al., 2004).
In addition, APP and its related proteins are overexpressed in sIBM patients and in
other myopathies, including polymyositis and hIBM (Askanas and Engel, 1998a). This
suggests that the effects of APP in sIBM muscle are a secondary downstream process,
common to multiple diseases but initiated by different pathogenic mechanisms.
Observations of end-stage pathology provide only limited detail of causative events.
When considering sIBM, other methods are required to determine whether -amyloid or
fragments containing -amyloid within the inclusion bodies are indicators of a primary
event, or are instead a secondary symptom brought about by another, as yet unknown
factor (Murphy and Golde, 2006).
25
1.6.4 Genetic susceptibility
A sizable body of evidence suggests a genetic factor in the pathogenesis of sIBM. The
strongest evidence for a genetic influence for sIBM pathogenesis has been the presence
of rare, familial clusterings of sIBM cases, as well as an association with genes of the
major histocompatibility complex (MHC). The association of sIBM with -amyloid-
related genes has also been considered, as have mitochondrial deletions and in recent
years, the role of the basic helix-loop-helix factor B3 gene.
1.6.4.1 Familial inclusion body myositis
A role for genetics in the pathogenesis of sIBM is reinforced by the observation of
multiple cases of sIBM within a given family, examples of which have been reported in
several case studies (Neville et al., 1992; Naumann et al., 1996; Sivakumar et al., 1997;
Amato and Shebert, 1998; Hengstmann et al., 2000; Tateyama et al., 2003; Ranque-
Francois et al., 2005; Mastaglia et al., 2006).
Unlike hIBM, ―familial sIBM‖ (fIBM) has proven to be clinically and histologically
identical to sIBM, and is considered to be the same disease (Mizusawa, 2003). One
possible exception is a case study that exhibited no rimmed vacuoles in the muscle
biopsy of one fIBM patient (Hengstmann et al., 2000). This may have been a sampling
error, given the multifocal nature of the disease and the fact that this patient‘s sister,
who also suffered from fIBM, did exhibit rimmed vacuoles. One other study of fIBM
examined a family with what was described by the authors as ―autosomal dominant
sIBM‖ (Neville et al., 1992). Age at onset for the patients in this family was lower than
expected, with symptoms manifesting in the third or fourth decade of life. Amyloid
fibres could not initially be identified in muscle biopsies by Congo-red staining,
although this was later found to be a result of the authors inexperience with the
technique (Mendell and Sahenk, 1992). Anecdotal evidence also suggests that fIBM
responds better to treatment than sIBM (Naumann et al., 1996; Mizusawa, 2003).
1.6.4.2 The genetics of β-amyloid
If APP were to play a central role in the pathogenesis of sIBM then it‘s expected that
there would be some correlation between the disease susceptibility and mutations in
genes associated with βAPP, as is the case with Alzheimer‘s disease. While there has
been no genetic association identified between sIBM and either presenilin 1, presenilin
26
2 or βAPP, one possible association has been reported with the Val122Ile mutation in
the -amyloid related gene transthyretin (TTR), which normally binds with -amyloid
to prevent fibrillar amyloidogenesis. In this study, muscle fibres were cultured in vitro
from a patient with sIBM and cardiac amyloidosis associated with the TTR mutation
(Askanas et al., 2003). The results showed that in the presence of an overexpressed
βAPP gene, aspects of the sIBM phenotype were greatly increased compared to cultured
muscle fibres without the TTR mutation. The authors suggested that the TTR mutation
could be a susceptibility allele for sIBM, triggered by environmental factors or an aging
cellular environment, although it is also likely that it may simply exacerbate a pre-
existing sIBM phenotype (Askanas et al., 2003).
1.6.4.3 Mitochondrial DNA deletions
Other genetic abnormalities that have been considered in sIBM patients are
mitochondrial DNA deletions. One study found that patients with sIBM are more likely
to carry multiple mitochondrial deletions, although some of these deletions accumulate
as a normal part of aging (Simonetti et al., 1992; Santorelli et al., 1996; Wang et al.,
2001). Together with the presence of ragged-red fibres and cytochrome-C oxidase
negative fibres, multiple mitochondrial DNA deletions are often indicative of impaired
oxidative metabolism, which could also contribute to the pathology of the disease.
However studies using 31
P magnetic resonance spectroscopy have not shown any
impairment of oxidative metabolism in sIBM patients (Argov et al., 1998; Lodi et al.,
1998). It has also been found that the overexpression of βAPP contributes to
mitochondrial DNA deletions (Askanas et al., 1996b). Thus far, there has been no
definitive evidence to suggest that changes to mitochondria are a primary, upstream
event in sIBM pathology (Tawil and Griggs, 2002).
1.6.4.4 Basic helix-loop-helix factor B3
The basic helix-loop-helix factor B3 gene (BHLHB3) is known to inhibit myogenic
differentiation (Azmi et al., 2004), and is over expressed in sIBM patient
mesoangioblasts (Morosetti et al., 2006). A recent study reported that mesoangioblasts
from sIBM patients show severely impaired myogenic differentiation into skeletal
myotubes. This may explain the inability of the muscle fibres in sIBM patients to
regenerate (Morosetti et al., 2006). Further investigation of BHLHB3 and possible
mutations that could influence expression in sIBM patients is thus warranted.
27
1.6.4.5 sIBM and the Major Histocompatibility Complex
As previously discussed, sIBM may be driven by an autoimmune component to the
disease pathology. As is common with autoimmune diseases, sIBM patient cohorts were
genotyped for alleles of the HLA class I and II genes (Love et al., 1991). This led to the
discovery of a consistent association between the sIBM and the HLA genes of the major
histocompatibility complex, located on chromosome 6p21.3. Before considering these
associations however, an understanding of the characteristic features of this region of
the human genome is required.
1.7 The major histocompatibility complex
Figure 2: Gene map for the classical and extended MHC region located on human chromosome 6p21.3, along with
several HLA and non-HLA genes found throughout the region. Relative distances are not to scale.
HLA-DPB1
CentromereHLA-DQB1
HLA-DRB1
C4B,A
TNFa,b
HLA-A HLA-B
HLA-C
HLA-DRA
Cla
ss II Su
breg
ion
(0.9
Mb
)
Cla
ss III Su
breg
ion
(0.7
Mb
)
Cla
ss I Su
breg
ion
(1.9
Mb
)
TelomereNOTCH4
BTNL2AGER
Human Chromosome 6Long ArmShort Arm
Ex
tend
ed C
lass I
Su
breg
ion
(3.9
Mb
)
Ex
tend
ed C
lass II
Su
breg
ion
(0.2
Mb
)
Figure 1.2: Gene map for the classical and extended MHC region, along with several
HLA and non-HLA genes found throughout the region (adapted from Horton et al.,
2004). Relative distances not to scale.
The classical major histocompatibility complex (MHC) is a region of the human
genome approximately 3.5Mb long, located in the distal portion of the 6p21.3 band.
Gene products from this region were first identified in 1936 and were later revealed to
be human leukocyte antigens (HLA). These gene products were initially studied for
their ability to confer tolerance to tissue grafts and, subsequently, organ transplants
(Horton et al., 2004).
The classical MHC region is divided into the Class I, II, and III subregions (Figure 1.2).
The presence of immune-related genes located far beyond the boundaries of the
classical MHC has led to the concept of an ‗extended‘ MHC in humans. These extended
28
class I and extended class II subregions are situated at either end of the classical MHC
region (Stephens et al., 1999; Mungall et al., 2003). Together, the classical and extended
subregions of the MHC total 7.6Mb (Mungall et al., 2003; Horton et al., 2004).
The MHC was initially characterised due to the presence of HLA genes, which remain a
major focus for those studying this region. The HLA genes are subdivided into the HLA
Class I and II genes according to which subregion they are found in. The HLA class I
genes process and present endogenous (intracellular origin) antigens to CD8+ T-cells
while the HLA class II genes present exogenous (extracellular origin) antigens to the
CD4+ T-cells (Horton et al., 2004). However, exceptions have been reported where
HLA class I genes present exogenous antigens and HLA class II genes present
endogenous antigens (Reimann and Schirmbeck, 1999; Wick and Ljunggren, 1999).
The HLA and HLA-like genes only make up a small proportion of the genes within the
MHC. The majority of the genes within the MHC are those that either play some other
role in the immune system or have an entirely non-immune related role (Shiina et al.,
2004). The immune-related genes account for approximately 40% of expressed genes in
the MHC (Forbes and Trowsdale, 1999).
The class III region has no HLA genes, although it does contain genes related to
immune function and inflammation such as complement components 2 and 4, B factor,
tumour necrosis factor (TNF), lymphotoxin alpha (LTA) and lymphotoxin beta, as well
as many genes associated with non-immune functions such as transcription regulation,
house-keeping, biosynthesis, electron transport and hydrolase activity, and various
protein interactions (Shiina et al., 2004).
The MHC has been extensively studied compared to the rest of the human genome and
in contrast to other regions, is remarkable in five areas;
1. Gene density
2. Gene clustering.
3. Linkage disequilibrium.
4. The high level of polymorphism.
5. Disease association.
29
1.7.1 Gene density and gene clustering
Of the 421 loci within the classical and extended MHC, 252 are expressed genes, 30 are
transcripts with no known open reading frame and 139 are pseudogenes (Horton et al.,
2004). This gives a total density of one gene locus per 18.1kb (including expressed
genes, transcripts and pseudogenes). This is in contrast to one gene per 127.9kb, as is
predicted for the entire the human genome (Consortium, 2004). The class III region of
the is even more gene dense, with approximately one gene per 14.5kb (Shiina et al.,
2004).
Most of the MHC-encoded genes related to the immune response appear to cluster
together (Forbes and Trowsdale, 1999). For instance, in the extended class I region there
is a set of immunoglobulin genes closely related to butyrophilin, as well as ubiquitin-
like genes, proteases and transcription factors expressed predominantly in immune
tissues (Gruen and Weissman, 1997; Tazi-Ahnini et al., 1997). The class II region
effectively makes up an immune related gene cluster in itself, with all but one gene
(Ring Finger Protein 3) in the Class II region involved in the immune system (Beck and
Trowsdale, 1999). The class III region includes a cluster of more than seven immune
related genes, which has prompted some to speculate on the existence of a ―class IV‖
region encompassing these genes (Gruen and Weissman, 1997).
The evolutionary advantage of clusters of closely related genes may be to facilitate the
co-inheritance of allele combinations that function efficiently together (Carrington,
1999). Gene clusters are likely to have been the result of both small and large scale
segmental duplication (Gu et al., 2002), a phenomenon that accounts for 5.2% of the
human genome (Bailey et al., 2002).
1.7.2 Linkage disequilibrium
The high level of sequence diversity throughout the MHC is found in a series of
polymorphic blocks of conserved DNA. These polymorphic blocks are characterised by
continuous linkage disequilibrium – the non-random association of two or more alleles
at multiple loci (Carrington, 1999). Mutation and recombination within each
polymorphic block is rare, whilst recombination occurs more frequently on either side
of these blocks (Carrington, 1999; Dawkins et al., 1999; Yunis et al., 2003).
30
The size of individual polymorphic blocks in the MHC can vary from 5-150kb and each
block is highly polymorphic between individuals within and between ethnic groups.
Some polymorphic blocks appear restricted to a single ethnic population, such that it
may be common within a single ethnicity, yet very rare outside that population (Yunis
et al., 2003).
Yunis et al. (2003) proposed that the MHC can be broadly divided into four major
polymorphic blocks, as defined by ‗recombination hotspots‘ between each block and
characterised by the alleles of certain genes (Figure 1.3).
Figure 3: Major polymorphic blocks on the MHC {Yunis, 2003 #2}.
Centromere DP DQ DRC4 B,A
TNF, AHLA-B HLA-Cw
Bf
C2
Class II Region (700kb) Class III Region (900kb) Class I Region (1800kb)
NOTCH4
CYP21B,A
HLA-DR/DQ block
Complotype blockHLA-Cw/B block
TNF block
HLA-DPB1
CentromereHLA-DQB1
HLA-DRB1
C4B,A
TNFa,b
HLA-A HLA-B
HLA-C
HLA-DRA
Class II Subregion
(0.9mb)
Class III Subregion
(0.7mb)
Class I Subregion
(1.9mb)
TelomereNOTCH4
BTNL2AGER
Extended Class I
Subregion (3.9mb)
Extended Class II
Subregion (0.2b)
Figure 1.3: Major polymorphic blocks on the MHC (Yunis et al., 2003).
Conservation of polymorphic blocks is thought to be due to particular combinations of
alleles generating a more effective immune response together, compared with alleles
found on another polymorphic block (Carrington, 1999). This is not always the case,
and genes with seemingly unrelated functions may also maintain strong linkage
disequilibrium due to existing on the same, commonly inherited, polymorphic block
(Klitz and Thomson, 1987; Robinson et al., 1991).
Much larger stretches of conserved MHC DNA, consisting of multiple polymorphic
blocks are also co-inherited as ancestral haplotypes (AHs, also referred to as
―Conserved Extended Haplotypes‖ or CEH) that are inherited en bloc (Degli-Esposti et
al., 1992; Dawkins et al., 1999; Yunis et al., 2003). When considering AHs, specific
polymorphic blocks are often haplospecific for a particular AH, sometimes with one
particular allele at one locus being highly correlated with an entire MHC haplotype
(Yunis et al., 2003). A prime example is the highly conserved 8.1AH. This extended
haplotype is traditionally characterised by the alleles HLA-A*0101, HLA-B*0801, HLA-
DRB3*0101, HLA-DRB1*0301 and HLA-DQB1*0201. The majority of individuals with
the 8.1AH inherited the haplotype in its entirety and the presence of this AH in an
31
individual can be strongly inferred by the presence of the haplotype-specific allele HLA-
B*0801. Conserved AHs account for 73% of the MHC diversity in a given Caucasian
population (Degli-Esposti et al., 1992).
1.7.3 Polymorphism
Sequence variations, including single nucleotide polymorphisms (SNPs), indels and
microsatellites, occur between two individuals at a rate of 3.87 polymorphisms per kb in
the MHC, as opposed to 0.4-0.9 per kb in the rest of the human genome, giving at least
a four-fold difference in variation (Group, 2001; Stewart et al., 2004). The level of
polymorphism in the MHC is highest in those parts associated with HLA-A, HLA-B,
HLA-C and HLA–D (Stewart et al., 2004), with HLA-B considered the most
polymorphic gene in the human genome (Mungall et al., 2003). This is consistent with
the role of HLA genes in antigen presentation and immunity, as it is believed that
individuals heterozygous at HLA loci are capable of presenting a greater variety of
antigenic peptides than a homozygous individual. By extension, this would result in a
more effective immune response to an extensive array of pathogens (Carrington, 1999).
This extensive polymorphism does not appear to be restricted to coding regions
(Dawkins et al., 1999).
The sequence diversity is highest at those parts of the MHC that are in linkage
disequilibrium with the HLA class I and class II genes. The lowest level of variation
extends across the class III region, from the gene HLA-B Associated Transcript 4 to 1-
Acylglycerol-3-Phosphate O-Acyltransferase 1 (Stewart et al., 2004).
1.7.4 Disease association
Many diseases are associated with the MHC region, with the diversity of these disorders
as impressive as their number (Shiina et al., 2004). It is not just the HLA genes and
genes involved in immunity that are associated with the disease, but also genes
unrelated to the immune system (Table 1.4). Most, if not all autoimmune diseases are
associated with alleles of the MHC (Lechler and Warrens, 2000), which is attributed to
the large number of immune-related genes in the region, and the high linkage
disequilibrium across the MHC.
32
However, in more than 40 years of research, no single polymorphism within the MHC
has been assigned direct responsibility for a complex, immunological disease. This is in
contrast to the relatively simple monogenic diseases, which have been directly
associated with gene defects and polymorphisms within the MHC. One example is
congenital adrenal hyperplasia due to 21-hydroxylase deficiency, where several
polymorphisms in the gene CYP21 have been found to directly disrupt gene function
and subsequently generate the disease phenotype (White and Speiser, 2000).
Complex immunological diseases have instead been associated with a specific gene in
the MHC, often a HLA gene allele. For instance, Coeliac disease is associated with
HLA-DQA1*0501 and HLA-DQB1*0201 (Sollid et al., 1989), although no single variant
explains the correlation between the associated genotypes and the disease phenotype
(Ciclitira et al., 2005). In some cases, a specific SNP confers susceptibility to a disease,
such as two separate SNPs in the HFE (HLA-H) gene that are associated with hereditary
haemoachromatosis (Feder et al., 1996). However, it has often not been established
whether the disease association originates from the associated allele, or another
variation in linkage disequilibrium.
33
Table 1.4: A selection of diseases associated with the MHC region and some of the
genes with which they have been genetically associated. Adapted from the Genetic
Associations Database (GAD; http://geneticassociationdb.nih.gov/cgi-bin/index.cgi). A
comprehensive list of diseases associated with HLA and non-HLA alleles can be found
in Shiina et al. (2004).
Phenotype or Disease Disease Class Associated Gene/s
Asthma Immune TNF, LTA, PAFAH, HLA-DQB1, -DQA1
Ankylosing Spondylitis Immune HLA-B27
Bone Mineral Density Metabolic RUNX2, TNF
Cervical Cancer Cancer TAP1, HLA-DRB1
Colon cancer Metabolic HFE
Crohn's disease Immune TNF, HLA-DRB1
Diabetic Retinopathy Metabolic AGER
Gastric Adenocarcinoma Cancer HLA-DRB1
Hepatitis C Unknown TAP2, HLA-B
Hypertrophic Cardiomyopathy Cardiovascular HLA-B
Leprosy Infection HLA-A,HLA -B
Psoriasis Immune TAP, TNF, MICA
Rheumatoid arthritis Immune TNF, HLA-DRB1, MICA
Schizophrenia Psychological TNF, RXRB, NOTCH4
Sepsis Immune TNF
Silicosis Immune TNF
Sjogren's syndrome Immune TAP2, HLA-DRB1
Stevens-Johnson syndrome Immune HLA-B
Systemic Lupus Erythematosus Immune HLA-DRB1, -DQB1, TAP2, TNF
Type 1 Diabetes Immune LTA, MICA, PSMB8, BAT2, TNF, TAP2
Type 2 Diabetes Metabolic LTA, TNF, AGER, HFE
1.7.5 Locating MHC-related disease susceptibility alleles
Studies of disease association within the MHC often use HLA class I and II alleles as
the defining markers, since they are already very well characterised (Marsh et al., 2005).
Together with their role in immunity, this can occasionally result in the erroneous
assumption that alleles for the class I and II HLA genes are directly responsible for the
observed genetic association with a disease (Dawkins et al., 1999). Such a conclusion
requires a plausible mechanism linking the gene with the disease pathogenesis and
definite proof of the causation. Otherwise any other allele in linkage disequilibrium with
a particular HLA allele is just as likely to be the direct cause of the observed disease
association. Therefore consideration should also be given to non HLA-genes in the
MHC when defining disease association.
34
AHs have proven to be a double-edged sword in isolating disease susceptibility alleles.
Strong genetic conservation makes AHs an excellent tool for defining disease
associations. HLA-typing can thus be used to identify disease associations with little
difficulty, by assigning susceptibility to a conserved AH using the component HLA
alleles of a particular haplotype. Once a (presumed) susceptibility haplotype is
identified, a disease susceptibility region can be defined according to the boundaries of
the associated AH or polymorphic block. Thereafter, attempts to further define disease
susceptibility to a single gene or allele becomes difficult. Strong linkage disequilibrium
across the susceptibility haplotype minimises any genetic variation between patients,
complicating efforts to differentiate the source of the disease susceptibility from an
allele in linkage disequilibrium with it.
Even without the complication of linkage disequilibrium, establishing an allele as
directly responsible for an observed disease can be problematic. Almost all MHC-
associated diseases are multifactorial, with multiple genetic, epigenetic and
environmental factors all acting to either inhibit or predispose an individual to a disease
(Horton et al., 2004). Identifying a precise disease susceptibility allele may thus require
eliminating the influence of other predisposing factors on the disease phenotype. Efforts
to isolate disease-associated alleles can also be confounded by genetic heterogeneity,
where different loci or alleles trigger what appears to be the same disease in patients via
different pathways (Dawkins et al., 1999). It is therefore necessary to precisely establish
and characterise disease phenotype of each patient to identify any variations of the
disease and allow them to be studied separately.
One approach for identifying MHC-related susceptibility genes is recombination
mapping, also known as positional cloning (Collins, 1995). For most genetic diseases
associated with loci outside the MHC, this process involves the comparison of alleles
between closely related positive and negative individuals for the target disease
(Broeckel and Schork, 2004). Recombination during meiosis ensures that related
affected individuals do not carry all of the same genetic markers. Consequently, a
condition can be mapped to a specific region by finding markers that are common only
to individuals positive for the disease. When studying regions with strong linkage
disequilibrium such as the MHC, recombination mapping is limited by the enhanced
linkage disequilibrium defining only large blocks of multiple genes rather than single
genes or gene segments. Nevertheless, this technique can still be used by comparing
35
patients that carry portions of ancestral haplotypes due to historical recombinations with
an original founder mutation, rather than recent (familial) recombinations. This
approach to defining disease susceptibility has been used in mapping complex diseases
such as type I diabetes mellitus susceptibility to alleles of the TNF region (Cheong et
al., 2001), prostate cancer to part of chromosome 22q12.3 (Camp et al., 2007) and
mapping sIBM susceptibility to the border of the MHC Class II and III regions (Kok et
al., 1999; Price et al., 2004). The study by Camp et al. into prostate cancer is an
example where recombination mapping defined a susceptibility region outside of the
MHC (Camp et al., 2007).
A variation on recombination mapping that has been utilised in the past is transracial
mapping, which is the comparison of allele or polymorphism frequencies in several
ethnic populations. This approach has been used for MHC-related diseases such as type
I diabetes mellitus, ankylosing spondylitis, dermatomyositis and polymyositis, (Lopez-
Larrea et al., 1995; Arnett et al., 1996; Gonzalez-Roces et al., 1997; Park et al., 2001).
The benefit of transracial mapping in the MHC is that different ethnic populations
invariably carry different sets of polymorphic blocks (Yunis et al., 2003). Therefore a
definitive susceptibility allele common to several ethnicities may be easier to locate.
1.7.6 HLA Allele Typing
Over time, the identification of HLA alleles has moved from serological, or antibody-
based typing (serotyping), to sequence-based genotyping. This has allowed the
differentiation of genetically distinct alleles that bind to the same antigenic target. HLA
pseudogenes can also be identified with sequence-based genotyping, but would not be
found by serotyping due to their lack of expression.
A single HLA serotype can therefore be split into multiple HLA genotypes. For
example, individuals who are serologically HLA-DR3 are split into the genotypes HLA-
DRB1*0301, HLA-DRB1*0302 and others. Of significance is the fact that HLA-
DRB1*0301 is associated with multiple diseases, including sIBM, while DRB1*0302 is
not. It is thus necessary to critically assess or re-assess studies involving HLA
serotyping in light of the possible related genotypes. A detailed breakdown of HLA
genotypes and their related serological alleles can be found in the report by Marsh et al.
(2005) and an abridged summary is found in the Appendix – Table A1.1.
36
1.8 sIBM-associated HLA alleles
There have been multiple studies of HLA susceptibility for sIBM. A summary of these
results is shown in Table 1.5.
Table 1.5: Past studies demonstrating HLA susceptibility alleles for sIBM.
Reference Cohort
Size Associated HLA alleles
Associated
AHa
Love et al. (1991) 26 HLA-DR3, HLA-DRw52
Garlepp et al. (1994) 13 HLA-DR3, HLA-DRw52
HLA-B18, HLA-DR3
8.1
18.2
Koffman et al. (1998) 30 HLA-DRB1*301, HLA-DRB3*0101,
HLA-DQB1*0201
HLA-DRB1*0101 (possible)
Garlepp et al. (1998) 15 HLA-B8, DR3 8.1
Lampe et al. (2003) 47 HLA-B*08
HLA-DRB1*03
HLA-A*03,
HLA-DQB1*05
8.1
Price et al. (2004) 42 HLA-B8, DR3
HLA-A3, HLA-B35, HLA-DR1
8.1
35.2
Badrising et al. (2004) 52 HLA-B8, HLA-DR3, HLA-DRw52,
HLA-DQ2
HLA-DR53 (protective)
HLA-DR4 (protective)
HLA-DQ8 (protective)
8.1
37
Table 1.5: (cont.)
Reference Cohort
Size Associated HLA alleles
Associated
AH?a
O‘Hanlon et al. (2005) 48 HLA-A*0101, HLA-B*0801,
HLA-Cw*0701, HLA-DRB1*0301,
HLA-DQA1*0501
HLA-DQA1*0201 (protective)
HLA-C*14
HLA-DQA1*0103 (protective)
8.1
a Associated AH is defined according to the AHs classified by Cattley et al. (2000) and
is only specified if the paper defines the AH itself or patients carrying both the HLA-B
and DR alleles corresponding to that AH.
Serotyping first demonstrated a genetic association in sIBM patients with the HLA
alleles HLA-DR3 and HLA-DRw52 when compared to other IIMs (Love et al., 1991).
This was confirmed in Caucasian patients by serotyping and genotyping in multiple
studies (Garlepp et al., 1994; Garlepp et al., 1998; Koffman et al., 1998b; Lampe et al.,
2003; Badrising et al., 2004; Price et al., 2004; O'Hanlon et al., 2005). The results of
these studies support a genetic association between sIBM and alleles of the highly
conserved 8.1AH (HLA-B*0801, HLA-DRB1*0301, HLA-DRB3*0101, HLA-
DQB1*0201).
A genetic association with alleles defining the 18.2AH (HLA-B*1801, HLA-
DRB1*0301, HLA-DRB3*0101, HLA-DQB1*0201) has also been proposed (Garlepp et
al., 1994). The 18.2AH shares identical alleles with the 8.1AH between HLA-DRB1 and
HLA-DQB1 (Cattley et al., 2000). However, an association between the 18.2AH and
sIBM is unlikely, as patients show increased carriage of HLA-B*0801 but not HLA-
B*1801 (Price et al., 2004).
HLA-DRB1*0101 was first identified as a statistically significant susceptibility allele for
sIBM by Koffman et al. (1998). HLA-DRB1*0101 was also observed in several other
studies of sIBM patient cohorts, albeit without statistical significance (Love et al., 1991;
Badrising et al., 2004). The association was later extended to alleles of the 35.2AH, as
defined by HLA-B*3501, HLA-DRB1*0101, HLA-DQB1*0501 (Price et al., 2004;
O'Hanlon et al., 2005).
38
Several studies have also suggested that protection from sIBM may also be conferred by
HLA alleles. These include HLA-DRw53 in a Dutch population, and HLA-DQA1*0201
and HLA-DQA1*03 in a North American population (Badrising et al., 2004; O'Hanlon
et al., 2005). Of these alleles, HLA-DQA1*0201 also has a protective effect on
polymyositis (O'Hanlon et al., 2005).
As sIBM is most prevalent in Caucasian populations (Shamim et al., 2002; Needham
and Mastaglia, 2007), most studies have focused on this ethnic group, with relatively
little attention given to the genetic association of sIBM in other ethnic groups. In the
Japanese, research prior to this PhD had been limited to case studies of small numbers
of patients (Tateyama et al., 2003; Warabi et al., 2004). In one case study of two
Japanese sisters diagnosed with sIBM, both patients carried HLA-DRB1*1502 and HLA-
DRB1*0405. Due to the small sample size and familial relationship of the patients, it
was impossible to draw any conclusions regarding HLA-associations with sIBM from
this study (Tateyama et al., 2003).
Studies on the HLA alleles found in fIBM identified results identical to that of studies
using unrelated patients with sIBM. In almost all Caucasian cases where the HLA
alleles have been genotyped, family members with fIBM all carried HLA-DRB1*0301,
which is indicative of the 8.1AH (Sivakumar et al., 1997; Ranque-Francois et al., 2005).
The only exception was a report on a mother and son with sIBM, where the mother
carried HLA-B8, HLA-DRB1*0301 (8.1AH) and the son had HLA-B5, HLA-
DRB1*1502, which comprise the 52.1AH (Mastaglia et al., 2006). It should be noted
that HLA-DRB1*1502 was also found in the Japanese sisters diagnosed with fIBM
(Tateyama et al., 2003). Another finding was that three of the nine HLA-typed fIBM
patients carried HLA-DRB1*01, HLA-DQB1*0501, while a further three carried HLA-
DRB1*01(Sivakumar et al., 1997; Ranque-Francois et al., 2005). This allele
combination is found as part of the 35.2AH, although these alleles are not unique to that
haplotype. Given that patients with fIBM share the same susceptibility alleles associated
with sIBM, one could hypothesise that fIBM and sIBM share the proposed sIBM
genetic susceptibility.
39
1.9 The sIBM susceptibility region
The AH most commonly associated with sIBM is the 8.1AH. The high frequency of this
haplotype amongst Caucasian sIBM patients has allowed the possibility of fine mapping
of the source of sIBM susceptibility in the 8.1AH by recombination mapping.
Recombination mapping of patients with the 8.1AH localised the sIBM susceptibility
locus to near the border of the Class II and III regions of the MHC (Kok et al., 1999).
Eighteen patients were typed for five alleles that were haplotypic, but not unique
(haplospecific) to the 8.1AH, these being HLA-B8, TNFa2b3, HSP70*2, C4A*Q0 and
HLA-DR3. All 18 patients carried HLA-DR3, but not all carried C4A*Q0 or any other
alleles that make up the 8.1AH. This led to the definition of an sIBM susceptibility
region as lying centromeric of C4 and extending at least as far as HLA-DRB1.
Further recombination mapping was completed on an expanded cohort of sIBM patients
apparently recombinant for the 8.1AH, as defined by the carriage of either HLA-DR3 or
HLA-B8 (Price et al., 2004). In this instance nine polymorphic loci, including HLA-B
and HLA-DR, were analysed in 14 recombinant patients to further define the sIBM
susceptibility region to between HLA-DRB1 and PBX2 (Figure 1.4).
Figure 4: The sIBM susceptibility region (marked in blue) in patients with the 8.1AH as defined by Price et al.
(2004). Coding genes are marked in red while pseudogenes or gene fragments are marked in white.
HLA-DPB1
Centromere
HLA-DQB1
HLA-DRB1
C4B,A
TNFa,b
HLA-A HLA-B
HLA-C
HLA-DRA
Telomere
NOTCH4
BTNL2AGER
sIBM susceptibility
BTNL2C6orf10NOTCH4
GPSM3
PBX2
HCG23AGERHLA-DRA HLA-DRB1
HLA-DRB9 HLA-DRB2
HLA-DRB3
MHC Region
Figure 1.4: The sIBM susceptibility region (shown in blue) in patients carrying the
8.1AH as defined by Price et al. (2004). Coding genes are shown in red while
pseudogenes or gene fragments are shown in white.
HLA-DRB1 was excluded from the proposed susceptibility region due to the fact that
when carriage of the serological allele for HLA-DRB1*0301, namely HLA-DR3, was
compared between positive controls and sIBM patients, carriage of HLA-DR3 without
40
other alleles haplotypic of the 8.1AH was less common in patients (Price et al., 2004).
This was taken as suggesting that HLA-DRB1 was not the direct cause of the disease,
but was instead in linkage disequilibrium with the sIBM susceptibility allele (Price et
al., 2004). The region immediately surrounding HLA-DRB1 is also highly similar
between the 8.1AH and the 18.2AH, which despite also carrying HLA-DRB1*0301, did
not show any association with sIBM (Price et al., 2004). The similarity between the two
haplotypes is illustrated by Traherne et al. (2006), which revealed that the 8.1AH and
18.2AH were almost identical around HLA-DRB1 and HLA-DQB1, but diverged to
show considerable variation at HLA-DRB3 and further telomeric of HLA-DRB3
(Traherne et al., 2006b). The genetic association for sIBM is thus likely to lie telomeric
of HLA-DRB1, where sequence variation in the 8.1AH is distinct from the non-sIBM
linked 18.2 AH.
Price et al. (2004) excluded PBX2 from the proposed sIBM susceptibility region. The
authors proposed that the susceptibility region should extend as far as, but not include
the allele HOX12*C. However this allele lies within the PBX2 promoter region,
meaning that the remainder of the PBX2 promoter between the alleles HOX12*C and
HLA-DRB1*0301 could still contain an sIBM susceptibility allele. It therefore remains
possible that a sIBM susceptibility allele could influence the expression of PBX2
through a mutation in the promoter of this gene.
While there has not been any other refinement of the genetic susceptibility region for
sIBM, O‘Hanlon et al. (2005) found that HLA-DRB1*0301 showed a stronger
association than the linked allele HLA-DQA1*0501. This supports the conclusion by
Price et al. (2004) and Kok et al. (1999) that the susceptibility region lies closer to the
Class III region, telomeric of HLA-DRB1.
According to recent MHC mapping studies (Horton et al., 2004; Shiina et al., 2004),
there are a total of 10 genes and pseudogenes within the susceptibility region for sIBM
patients with the 8.1AH, as defined by Price et al. (2004). These genes are PBX2,
GPSM3, NOTCH4, C6orf10, HCG23, BTNL2, HLA-DRA, HLA-DRB9, HLA-DRB3 and
HLA-DRB2, with AGER and HLA-DRB1 lying at opposite ends of the susceptibility
region.
41
1.10 Aims and Hypotheses.
It is clear that there are two parallel processes occurring in sIBM patients, these being
the inflammatory component and the degenerative component. The inflammatory
component is driven by CD8+ T cells and macrophages responding to an unknown
antigen localised within the MHC-I expressing skeletal muscle. The degenerative
process is evident from the vacuolated muscle fibres and is hypothesised as being
independent from the autoimmune process by its lack of interaction with CD8+ T cells
(Dalakas, 2004). The origin of these processes and how they interact are unknown.
Microarray studies of sIBM patient muscle biopsies have revealed little information.
Expression of genes involved in the immune component, such as immunoglobulins,
HLA and cytokines are generally increased (Greenberg et al., 2002; Greenberg et al.,
2005; Walsh et al., 2007). However no novel genes, including those within the defined
sIBM susceptibility region (Price et al., 2004) have been reported with significantly
increased expression (Greenberg et al., 2002). Therefore other approaches beyond
mRNA expression studies are required to determine a pathogenic mechanism for sIBM.
Of the previously proposed pathogenic mechanisms, viral infections such as HIV and
HTLV-1 do not cause sIBM in all infected individuals and the pathogenic picture for the
degenerative component and β-amyloid remains incomplete, with a currently unknown
initiating factor. It is possible that the genetic association between sIBM and the MHC
susceptibility region is either a key factor in the pathogenesis of sIBM, or may be one of
multiple elements contributing to a patient‘s disease susceptibility.
In either case, knowledge of the precise location and nature of an allele causing sIBM
susceptibility should provide evidence as to the upstream pathogenic mechanism of
sIBM. It may also clarify any link that unites the degenerative and inflammatory
components of this disease into a common pathogenic cascade.
The central hypothesis of this thesis was that susceptibility to sIBM is conferred by a
single allele found within a region defined using the 8.1AH and carried by multiple
haplotypes associated with sIBM.
In order to address this hypothesis, knowledge of HLA, AH and potential gene
associations with sIBM were examined. Hence the aims of the thesis were as follows;
42
1. To compile any variations on the 8.1AH that are located within the sIBM
susceptibility region defined by Price et al. (2004).
2. To analyse polymorphisms in the most likely candidate susceptibility genes
within the identified sIBM susceptibility region.
3. To further analyse the MHC region in an expanded cohort of Caucasian sIBM
patients to confirm previously known HLA associations and identify possible
new associations.
4. To identify new HLA allele and haplotype associations in a cohort of Japanese
sIBM patients.
5. To identify susceptibility alleles common to multiple AHs associated with
sIBM.
6. To use recombination mapping in Caucasian sIBM patients with part of the
8.1AH to further refine a common overlapping region and thus determine the
most likely 8.1AH-derived sIBM susceptibility region.
The isolation of potential sIBM susceptibility alleles or genes should facilitate future
investigation into the precise genetic cause for the observed sIBM susceptibility in the
MHC, provide clues as to the pathogenesis of sIBM and by extension, identify new
targets for treatment.
43
CHAPTER TWO
2 METHODS
44
2.1 Patients and cell lines
2.1.1 Australian cohort
The ‗Australian‘ cohort of sIBM patients was expanded from 42 patients studied
previously (Price et al., 2004). DNA was obtained from a total of 77 Caucasian patients
diagnosed with sIBM through the Inflammatory Myopathies Clinic at the Australian
Neuromuscular Research Institute (ANRI), the Department of Neurology at Royal Perth
Hospital, the Department of Neurology at Royal Melbourne Hospital, the
neuromuscular clinic at the Monash Medical Centre and the neuromuscular clinic at
Concord Hospital.
The patients in this cohort fulfilled the criteria for definite or probable sIBM according
to the clinical and muscle biopsy criteria proposed by Griggs et al. (1995) and
subsequently modified by Needham & Mastaglia (2007).
2.1.2 American cohort
Blood samples from 28 Caucasian patients were obtained from Professor Marinos
Dalakas, the National Institutes of Health in Bethesda (Maryland, USA). Patients were
collected from across the United States of America. Diagnosis of sIBM in these patients
were confirmed by clinical and muscle biopsy criteria (Dalakas, 2006).
2.1.3 German cohort
DNA from 51 Caucasian patients who fulfilled the clinical and histological (light
microscopy) criteria for definite sIBM (Vershuuren et al., 1997) was obtained from Dr
Maggie C. Walter at the Neurological departments of the Universities of Munich and
Bonn in Germany. HLA frequency data for the German cohort was published previously
(Lampe et al., 2003).
2.1.4 Japanese cohort
DNA samples from 31 sIBM patients from across Japan were studied. These patients
were diagnosed over a period of 7 years at the National Centre for Neurology and
Psychiatry in Tokyo. All patients were elderly (69.5 +/- 6.8 years old) and were reported
as having typical pathological findings.
45
2.1.5 Cell lines
A total of thirty one homozygous, consanguineous, or heterozygous Epstein-Barr virus
(EBV)-transformed B-cell lines carrying conserved MHC haplotypes were chosen from
the 10th
International Histocompatibility Workshop (10IHW) panel (Prasad and Yang,
1996) and the 4th
Asia-Oceania Histocompatibility Workshop (4AOH) panel (Degli-
Esposti et al., 1993; Degli-Esposti et al., 1995). DNA from the cell lines was extracted
by the method described by Miller et al. (Miller et al., 1988) and had been previously
genotyped for a broad selection of polymorphic markers within the MHC (Cattley et al.,
2000). The characteristics of the cell lines used in this study are detailed in Table 2.1.
10IHW no. 4AOH no. Name Zygositya
AH HLA A* HLA Cw* HLA B* HLA-DRB1* HLA-DQA1* HLA-DQB1* HLA-DPB1
9013 100158D SCHU - 7.1 0301 0702 0702 1501 0102 0602 0402
9318 PGF Con 7.1 0301 0702 0702 1501 0102 0602 0401
9131 100043X KUROIWA - 7.2 24 7 7 0101 0101 0501 0401:0402
9022 100045T COX Con 8.1 0101 0701 0801 0301 0501 0201 0301
9132 100044V REE GD Het 8.1 1:24 8 0301 0501 0101:0201
9046 BH - 13.1 0201 0602 1302 0701 0201 0202 0401:1701
9008 100050A DO208915 - 18.1 2501 1203 1801 1501 0102 0602:0603 0201:2301
9020 QBL Con 18.2 2601 0501 1801 0301 0501 0201 0202
9018 100036U L0081785 - 18.2 0301:2402 0501 1801 0301 0501 0201 0301
9042 100018W TISI Con 35.1 2402 0401 3508 1103 0505 0301 0402
9006 100052W WT100BIS Con 35.2 1101 0401 3501 0101 0101 0501 0101
9136 100053U SPE, G Het 18.2/35.3 1101:3002 4:5 18:35 0101:0301 0101:0501 0201:0501 0202:0401
9026 100009X YAR Hom 38.1 2601 1203 3801 0402 0301 0302 0401
9021 100007B RSH - 42.1 3001:6802 1701 4201 0302 0401 0402 0101:0402
9302 SSTO Hom 44.1 3201 0501 4402 0403 03 0401
9050 100058H MOU Con 44.2 2902 1601 4403 0701 0201 201 0201
9053 100145P HOR - 44.4 3303 1403 4403 1302 0102 0604 0401
9076 100059F T7526 Het 46.1 0206:0207 0102:0801 4601 0901 0302 0303 1301
9066 100063R TAB089 - 46.2 0207:0201 0102 4601 0803 0103 0601 0202
9047 100064P PLH Con 47.1 0301 0602 4701 0701 0201 0202 1501
9142 100065M HARA Hom 52.1 24 52 1502 0103 0601 0901
9141 100062T HOKKAIDO Hom 54.1 24 1 54 0405 03 0401 0501
9052 100084G DBB Con 57.1 0201 0602 5701 0701 0201 0303 0401
9133 100047P MAD, MF Het 57.1/8.1 1:3 8:57 0301:07 0201:0501 0201:0303 0301:0401
9156 100086C WON, PY Hom 58.1 33 3 58 0301 0501 0201 0401
9157 100087A HAU, ML Hom 58.1 33 0301 5801 0301 0501 0201 0501:1301
9098 100068E MT14B Con 60.1 3101 0304 4001 0404 03 0302 0402
9059 SLE005 - 60.3 0201 0304 4001 1302 0102 0301
9031 100072Q BOLETH Con 62.1 0201 0304 1501 0401 0301 0302 0401
9060 100022F CB6B Con 62.3 0101 0303 1501 1301 0103 0603 1901
9079 100002N LWAGS Hom 65.1 3301 0802 1402 0102 0101 0501 0301:0401
a - For cell line zygosity, Con = Consanguineous; Het = Heterozygous, Hom = Homozygous.
Table 2.1: 10IHW and 4AOH cell lines used throughout the study. Previous HLA genotyping data on these cell lines was obtained from Cattley et al (2000) and supplemented with data from
the IMGT/HLA database (http://www.ebi.ac.uk/imgt/hla/cell_query.html Accessed: 5/11/2007).
47
2.2 Experimental procedures
2.2.1 Lymphocyte DNA extraction
2.2.1.1 Reagents for lymphocyte DNA extraction
1X Phosphate Buffered Saline (PBS) contained 137mM NaCl, 2.7mM KCl, 10.1mM
Na2HPO4 and 1.8mM KH2HPO4. The solution was adjusted to pH 7.4 and stored at
room temperature.
Red Cell Lysis Buffer (RCLB) contained 10mM Tris (pH 7.6), 10mM NaCl and 5mM
MgCl. The solution was stored at room temperature.
White Cell Lysis Buffer (WCLB) contained 10mM Tris (pH 7.6), 10 mM EDTA (pH
8.0), 50 mM NaCl and 0.2% SDS. The solution was stored at room temperature.
Proteinase K was purchased from Sigma-Aldrich (USA) and stored at -20oC.
TE Buffer was composed of 10mM Tris (pH 7.6) and 1mM EDTA (pH 8.0) adjusted to
pH 8.0.
2.2.1.2 Method for lymphocyte DNA extraction
The following method was used for the extraction of DNA from the American cohort
(Miller et al., 1988). 1.5mL samples of frozen (-80oC) buffy coat were defrosted at 37
oC
and immediately resuspended in a 15mL tube with 10mL of PBS. The solution was
centrifuged at 200g for 5 mins at room temperature, before the supernatant was removed
and the pellet resuspended in 5mL of PBS. Following a further 5 min centrifugation at
200g the supernatant was removed and the pellet resuspended with 500µL of RCLB.
3mL WCLB and 750ng proteinase K were added and the solution incubated with
rocking overnight at 42oC.
Following incubation, 3.25mL of 6M NaCl was added and the solution was vigorously
shaken for 15 sec and centrifuged at 1400g for 15 min. The supernatant was added to a
fresh 50mL tube, along with 10mL of 1:1 ethanol/isopropanol.
48
The resultant solution was mixed by inversion and the precipitated DNA was transferred
to a fresh 1.5mL cryotube with a pipette. The precipitate was washed with 1mL of 70%
ethanol, before pelleting the DNA with a microfuge at maximum speed. The supernatant
was removed and the pellet dried at room temperature for 10 mins, before being
resuspended in 1mL of TE buffer. The DNA was left to dissolve on a mixer at room
temperature overnight. DNA was quantified using a spectrophotometer from NanoDrop
Technologies (USA) and stored at 4oC.
2.2.2 Whole genome amplification
Whole genome amplification was performed on some patient DNA samples using a
REPLI-g Mini Kit from QIAGEN (Netherlands), according to the manufacturers
instructions. The DNA was stored at 4oC.
2.2.3 Gel electrophoresis
6X loading buffer and 100bp DNA ladder were purchased from Promega (USA) and
stored at 4oC.
5X Tris-borate-EDTA (TBE) buffer contained 0.45M trizma base, 0.45M boric acid and
10mM EDTA (pH 8.0), and stored at room temperature. The solution was diluted 1:10
prior to use.
2% agarose solutions were prepared by dissolving agarose (Promega, USA) in 0.5X
TBE Buffer. Agarose solutions were supplemented with ethidium bromide to a final
concentration of 0.5µg/mL prior to cooling. Agarose gel electrophoresis was performed
in 0.5X TBE.
2.2.4 DNA amplification/PCR
2.2.4.1 Reagents for PCR
100mM solutions of each dNTP were purchased from Promega (USA). Working dNTP
solutions containing 10mM each of dATP, dGTP, dCTP and dTTP were stored at -
20oC.
49
PCR primers were ordered from Sigma-Proligo (NSW, Australia) and supplied at an
initial concentration of 100µM. Primers were stored at -20oC and diluted to 10µM prior
to use. Some primers were also covalently tagged with a fluorescent dye, either 6-FAM
or HEX, for use in microsatellite typing. All primers used in this study are shown in
Table 2.2.
Taq DNA polymerase was purchased from Promega (USA) and used in PCR reactions
until the product was discontinued by Promega. ―GoTaq® Flexi DNA Polymerase‖
(Promega, USA) was then used. All polymerases were stored at -20oC.
The PCR buffers supplied with the DNA polymerase from Promega (USA) were stored
at -20oC. Taq DNA polymerase was supplied with thermophilic DNA polymerase 10X
buffer which, when diluted to 1X, had a composition of 10mM Tris-HCl (pH 9.0 at
25oC), 50mM KCl and 1% Triton
® X-100. GoTaq
® Flexi DNA Polymerase was
supplied with 5X Colourless GoTaq® Flexi Buffer (pH 8.5). Neither buffer contained
MgCl.
25mM MgCl was supplied with the DNA polymerase by the manufacturer and stored at
-20oC.
The 10X PCR buffers used for optimisation reactions contained 500mM KCl, 100mM
Tris-HCl, (pH 8.3-9.2), 10-25mM MgCl2 and 0.1mg/ml gelatin. Four variations of pH
(8.3, 8.6, 8.9 and 9.2) and MgCl2 concentration (10mM, 15mM, 20mM and 25mM)
combined for a total of 16 different optimisation buffers. Aside from the gelatin all
stock solutions were autoclaved prior to use. The PCR buffers were stored at -20oC.
Table 2.2: Primer sequences used in this study and their optimum conditions.
Name Target polymorphism/s Nucleotide Sequence (5'-3')Maximum
Product Size
(bp)
LabelAnnealing
Temp. (oC)
pHMgCl2
conc (mM)
8306F rs1800625 Fwd: GCCAGACTGTTGTCTGCAAG 239 55 8.5 2
8306R Rev: GCAGTTCTCTCCTCACTTGT
14185F rs176095 Fwd: CTGAATCAGGGATCTAAGCG 191 55 9 2
14185R Rev: CGGCTGGTTAATTACTGGCT
15822F rs3134605 Fwd: AATGGAGTGGGCCTTGGTAA 215 55 8.3 2.5
15822R Rev: CCACTGCTTGACTAGAATGG
17718F rs204989 Fwd: GCAGATCTCTGTGCCTCAAT 193 55 8.5 2
17718R Rev: GTCCACCTTGCAGCAATATG
24649F rs3134942 Fwd: AGCAAGGAAGCGGAGTAGAA 220 60 8.3 2.5
24649R Rev: TCAGTGCTGGGTAAGAAGCT
35287_F_FAM rs9279509 Fwd: GACAGACTGGGACTCCATCT 130 6-FAM 60 8.5 2.5
35287_R_NIL Rev: AGGCCTCTACACCCAGAGAT
44266F rs422951 Fwd: CAGTGAAAGCTACCAGCAGA 198 60 8.5 2.5
44266R Rev: ACATCCATGACACCCATGGC
46273F rs915894, rs443198 Fwd: AGCAGCGCTTACCTGTCCAT 258 60 8.5 2.5
46273R Rev: AGAACGCCCAGCTCTGCCAA
47544_F_FAM2 rs9281675, rs367398 Fwd: CTGACCACTGAGACACATAG 222 6-FAM 60 8.5 2.5
47544_R_NIL2 Rev: AGGAAACAGCTCAGACGTGA
49108F rs3130295, rs9279514 Fwd: ATTCAGGTCCTGCCAATTGC 464 60 8.3 1.5
49108R Rev: AATGCCAGTATCGGCCAGGT
60361F rs693797 Fwd: GGTGTGTCCATACAATGGAA 201 55 9 2
60361R Rev: CTGAGCCCTAGACAATCACT
79335F rs3130319, rs3130321, rs3132966 Fwd: TTTGAGGAGAGAAGGCGCTT 777 60 8.6 1.5
79335R Rev: GCATTGGGACTCATCAGGAA
105803F rs9268117 Fwd: TAGCACCAGGAGGACAGGAT 407 60 9 2
105803R Rev: ATAGGTCTCTAGGAACTTGC
110007_F_HEX rs9279556 Fwd: CCATAGTAGTCAAGGAGACC 97 HEX 60 8.5 2.5
110007_R_NIL Rev: CCTCCACATGTACTTGCTGA
117582F rs7775397 Fwd: TGGACCTCTTGTTCCTTTGG 211 60 8.3 2
117582R Rev: AGATGGGTGTGCCAAGAAGA
117837F rs3749966 Fwd: CACTCTTCGTTACTTGGGCT 195 60 8.3 2.5
117837R Rev: TCAAGGTAGACAGTGACGCT
126101_F_HEX rs5875354 Fwd: GCATGTCCTGTGAGGTAAGA 223 HEX 60 8.5 2.5
126101_R_NIL Rev: ACCCTGCTGTTGTAGCACAA
160133F rs1265754 Fwd: ACTGAAATGCTAGGTTGAAG 224 55 8.3 2.5
160133R Rev: CACAGTGGTGAAGCATACTG
161985F rs926593 Fwd: GAGACACTAGACCCACATAC 228 55 9 2
161985R Rev: GAGAGCAAATACTGGGTAGG
196196F rs2050189 Fwd: GGTCTCGCATCATCTGGATT 203 60 8.3 2.5
196196R Rev: TTCTAGAACCTTCACAGGCC
196728Frs6913309, rs6913471, rs17202155,
rs3117110Fwd: GCTTTGGAGGACCTTGAACT 472 60 8.5 1.5
196728R Rev: TTCTGTGGAAGGTTCTCTGC
197423F rs3117109, rs3129944 Fwd: GCTTATTACCCAGGTGACTA 400 60 8.5 2.5
197423R Rev: GCTGGGTAACTTCTAGTGTC
198571_F_HEX rs9279614 Fwd: TATGCTAGTCTGTGCCAAGG 91 HEX 60 8.5 2.5
198571_R_NIL Rev: GAATGTTGAAGGTGTACCTC
206113F rs3117103 Rev: GAATCAGACTACTGGTTGCC 204 55 8.5 2
206113R Rev: GCTCAAGAAGATTAGGCTTG
214760_F rs3129950, rs3117099 Fwd: AGATCCAGCCAATCTGCACA 290 60 8.5 2.5
214760_R Rev: CAGTCACATTCTCTCACTGT
218382_F rs3129953 Fwd: TGCAGTGTGCTCCGCTGTTT 216 60 8.5 2.5
218382_R Rev: CCTAGAAGCTGCTCAGATGA
BTNL2E6_F BTNL2*E6 Fwd: GAGTAAGTCTGAGTTGGTCT 402 60 8.5 2.5
BTNL2E6_R Rev: TGCCCACTCATCCACTTGAA
219776F rs1980493 Fwd: GGGTCACATGGACAGGATTA 192 55 8.3 2.5
219776R Rev: CAAGTCTTGGATATGCTACG
232386F rs3129959 Fwd: AGACTTTGGACCACCCTCAA 253 60 8.5 2.5
232386R Rev: CAACAGATGAACCTAAGGAG
245344F rs2213580, rs3135366 Fwd: GACTTCTCTGTGGGATACTG 248 55 8.5 2
245344R Rev: CCCATGACACCTCTTCTGTA
HLA_DRP_1F rs9268632, rs9268636 Fwd: GAGAGTCGAAGTCTCCTAAT 416 55 8.5 2.5
HLA_DRP_2R Rev: CAGCTCATTGTAATCTCCGC
263555Frs28993482, rs9357142, 263598,
rs9268641Fwd: GCGGAGATTACAATGAGCTG 234 60 8.5 2
263555R Rev: GGAGCTACCTTCTTCTCATC
HLA_DRP_3F
rs9268642, rs3129872, rs2395179,
rs2395180, rs2395181, rs3129873,
rs3129874, rs3129875
Fwd: GATGAGAAGAAGGTAGCTCC 555 55 8.5 2.5
HLA_DRP_4R Rev: GGACACAAGATACTCCGTTC
269298F rs1131541, rs1051336 Fwd: TCCTTGACCTCAGTGAAAGC 213 55 8.3 2.5
269298R Rev: CAGAGACAGACTCCTGTATG
51
2.2.4.2 Method for primer optimisation
The optimum pH, MgCl2 concentration, and annealing temperature for each primer pair
was determined empirically using the sixteen 10X PCR optimisation buffers with pHs
ranging from 8.3 to 9.2 and the MgCl2 concentration ranging from 1.0 to 2.5mM. 50uL
reactions were prepared containing 0.2uM each of the forward and reverse primers,
0.8mM of dNTP, 1ng/µL genomic DNA, 1U Taq DNA polymerase and one of the
sixteen PCR optimisation buffers at 1X dilution, to which a master mix containing the
other reagents was added.
PCR optimisation mixtures were amplified using an Eppendorf Mastercycler (Germany)
under the following conditions; denaturation at 95oC for 3 mins followed by 35 cycles
of 95oC for 30 sec, the annealing temperature for 30 sec and 72
oC for 30 sec. The
annealing temperature used was 55oC, or alternatively 60
oC if a higher stringency was
required to minimise amplification of secondary products.
Amplification of each product was confirmed by gel electrophoresis, with 5 µL of each
amplicon analysed by electrophoresis on a 2% agarose gel. An example of the PCR
optimisation process is shown in Figure 2.1. The buffer producing the strongest single
band was subsequently used for that primer pair.
52
Lane pH [MgCl2] Lane pH [MgCl2]
1 8.3 1.0mM 9 8.9 1.0mM
2 8.3 1.5mM 10 8.9 1.5mM
3 8.3 2.0mM 11 8.9 2.0mM
4 8.3 2.5mM 12 8.9 2.5mM
5 8.6 1.0mM 13 9.2 1.0mM
6 8.6 1.5mM 14 9.2 1.5mM
7 8.6 2.0mM 15 9.2 2.0mM
8 8.6 2.5mM 16 9.2 2.5mM
Figure 2.1: PCR Optimisation of the 35287_F_FAM / 35287_R_NIL primer pair.
Genomic DNA from the DO208915 cell line was amplified using buffer conditions
shown on the table at 55oC. The product amplified at all tested pHs, with weaker
amplification at pH 9.2. MgCl concentrations lower than 1.5mM showed very poor or
no amplification. A secondary band in each lane was just visible in the saved image file
and so the annealing temperature for this primer pair was increased to 60oC (gel not
shown).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
53
2.2.4.3 Method for DNA amplification
50ng genomic DNA was amplified in a 50uL reaction mix containing 0.2uM each of the
forward and reverse primers, 0.8mM dNTP, 1X PCR Buffer, 1.0-2.5mM MgCl2, 1U
Taq DNA polymerase and 0.5-2ng/µL genomic DNA, which was added to the reaction
last. All reactions were set up on ice to prevent non-specific primer binding. PCR
reactions were performed using an Eppendorf Mastercycler (Germany) under the
following conditions; denaturation at 95oC for 3mins followed by 35 cycles of 95
oC for
30sec, the annealing temperature for 30sec and 72 o
C for 30sec. This was followed by a
final 2 min extension time at 72oC. Amplification of the amplicon was confirmed by gel
electrophoresis, with 5µL of each amplicon analysed by electrophoresis on a 2%
agarose gel.
2.2.5 Restriction fragment length polymorphism (RFLP) analysis
2.2.5.1 Reagents for RFLP analysis
BsaI was purchased from New England Biolabs (USA). The appropriate buffer supplied
with the enzyme (10X NEB Buffer 3), when diluted 1:10, contains 100mM NaCl,
50mM Tris-HCl (pH 7.9 at 25oC), 10mM MgCl2 and 1mM DTT.
HaeIII was purchased from Promega (USA). The appropriate buffer (Buffer C) was
supplied at 10X concentration with this enzyme, and contained 100mM Tris-HCl (pH
7.9), 500mM NaCl, 100mM MgCl and 10mM DTT. Both HaeIII and Buffer C were
stored at -20oC.
2.2.5.2 Methods for RFLP
The presence of the rare allele for the marker rs422951 was confirmed by RFLP. BsaI
was initially used for RFLP and made one cut in the absence of the rare rs422951 allele.
BsaI was subsequently replaced with HaeIII, which could distinguish the rare allele for
the marker rs422951 and also made additional cuts within the amplicon that acted as an
internal control to confirm full digestion of the product. All results in this study were
obtained using HaeIII.
The 30uL reaction contained 10U HaeIII, 1X Buffer C and 15uL of the PCR product,
and was digested at 37oC for 16 hrs, after which the enzyme was denatured by
54
incubation at 80oC for 20mins. 10uL of the digest, along with positive and negative
controls, were visualised following electrophoresis on a 2% agarose gel. Expected band
sizes are shown in Figure 2.2.
Figure 2.2: RFLP of rs422951 with the restriction enzyme HaeIII. The enzyme
normally cuts the 198bp amplicon three times to produce bands of size 159, 19, 13 and
8bp. The presence of the rare allele creates a fourth recognition site, cutting the 159bp
fragment into two fragments of 95 and 64bp. Samples uncut by HaeIII would result in a
single 200 bp band. Lane 1 – 100bp DNA Ladder; Lane 2 – H2O; Lane 3 – 8.1AH
control with the rare allele; Lane 4 – 18.2AH control with the common allele; Lane 5 –
heterozygous 8.1/60.1AH control with the rare and common allele.
2.2.6 Sequencing
2.2.6.1 Reagents for sequencing
The BigDyeTM
Terminator v3.1 reaction mastermix and its V3.1 sequence buffer were
purchased from Applied Biosystems (USA). The mastermix and sequence buffer were
stored at -20oC and 4
oC respectively. Primer solutions were diluted to 1µM
Ethylenediaminetetra acetic acid disodium salt (EDTA) was diluted to a working
concentration of 125mM EDTA with the pH adjusted to 8.0.
Sodium Acetate (NaAc) was diluted to a working concentration of 3M with the pH
adjusted to 3.2.
1 2 3 4 5
100bp
200bp
500bp
1kbp
55
2.2.6.2 Sequencing reaction
PCR products were purified using either the PureLink™
PCR Purification Kit from
Invitrogen (USA) or the Ultraclean™
PCR Clean-up™
Kit from Mo Bio Laboratories
Inc. (USA). Some PCR products were extracted from agarose gels and purified using
the HiYield™
Gel/PCR DNA extraction kit purchased from the Real Biotech
Corporation (Taiwan).
5µL of purified product was added to 2µL Big Dye Terminator v3.1 reaction
mastermix, 0.5X V3.1 sequence buffer and 1ρmol of primer in a total volume of 10µL.
The sequencing reactions were run under the following conditions; denaturation at 96oC
for 1min followed by 24 cycles of 96oC for 30sec, 50
oC for 30sec and 60
oC for 4min.
2.2.6.3 Post-sequence PCR purification
Sequence reactions were purified by ethanol precipitation according to the following
method. 10µL of the sequence reaction product was made to a final volume of 40µL
with 10.4mM EDTA, 250mM sodium acetate and 83% ethanol. The solution was mixed
and incubated at room temperature for 15 mins, before a 20 min centrifugation at 13,000
rpm. Most of the supernatant was removed with a pipette and the pellet was washed
with 100 µL of 70% ethanol. After mixing, the reaction was centrifuged at 13,000 rpm
for a further 5 mins. The supernatant was removed and the remaining ethanol was
evaporated by incubation at 60oC for 5 mins.
2.2.7 Genescan
Microsatellite polymorphisms were analysed using Genescan (Applied Biosystems,
California, USA). DNA samples were amplified by PCR as described in Section 2.2.5,
using a forward primer with a covalently tagged fluorescent dye at the 5‘ end and with
an increased final extension time at 72oC of 10mins. 10uL of each amplicon was
visualised by electrophoresis on a 2% agarose gel to confirm amplification. Aliquots of
the PCR product were diluted by up to 1:30, depending on the strength of the band
shown in gel electrophoresis, and were analysed using an ABI 3730 48 capillary
sequencer from Applied Biosystems (California, U.S.A.) by the Western Australian
DNA sequencing service provided through the Department of Clinical Immunology and
Biochemical Genetics at Royal Perth Hospital.
56
2.2.8 HLA allele typing
Class I and II HLA alleles were genotyped at the department of Clinical Immunology
(Royal Perth Hospital) using in-house methods. Serological typing data were only used
where sequence-based genotyping results were unavailable.
HLA alleles for the 52 patients from Germany had been typed previously using
Sequence Specific Primer Technology (SSP)-PCR and sequence specific
oligonucleotides (SSO) using commercial test kits for SSP analysis (BAG, Lich,
Germany; Olerup AG, Saltsjöbaden, Sweden) and SSO analysis (Dynal Biotech GmbH,
Hamburg, Germany). Both SSO and SSP analyses were performed according to the
manufacturer‘s instructions. A detailed analysis of the HLA alleles in forty seven of the
patients in this cohort has been published previously (Lampe et al., 2003).
2.2.9 Single strand conformation polymorphism
The presence of the rare allele for the marker rs2050189 was confirmed in patients
using single strand conformation polymorphism (SSCP) analysis, using the primers
detailed in Table 2.2. This was completed by laboratory technicians at the Western
Australian Institute for Medical Research in Perth, Western Australia.
2.3 Analytial Methods
2.3.1 Sequence analysis
Sequence chromatograms were analysed with ChromasPro v1.32 (Technelysium,
Australia) and the resulting sequences were aligned using Bioedit v7.0.1 (Hall, 1999).
2.3.2 Microsatellite typing
Data output files for microsatellites analysed using Genescan technology were
interpreted using Genemapper® v3.7 Rev A and Peakscanner
™ v1.0 (Applied
Biosystems, California, USA). Comparison of the same data between the two programs
showed no discrepancies.
57
2.3.3 Statistics
The chi squared (χ2) test and Fishers exact test were utilised to compare the distribution
of mutations and polymorphisms in subjects and controls. A value of p < 0.05 was
accepted as statistically significant.
58
CHAPTER THREE
3 ALIGNMENT OF HAPLOTYPE SEQUENCES WITHIN THE SIBM SUSCEPTIBILITY REGION
59
3.1 Abstract
The specific identification of an sIBM susceptibility allele carried by the 8.1AH first
requires a complete knowledge of the candidate polymorphisms within the region of
interest. Therefore the genomic sequence of the 8.1AH was aligned with multiple other
conserved haplotypes to identify polymorphisms characteristic of the 8.1AH. The region
from RNF5 to HLA-DRA was aligned using sequence data from cell lines carrying the
8.1AH, 7.1AH, 18.2AH and 44.1AH, initially sequenced by an international consortium
(Horton et al., 2008).
3.2 Introduction
sIBM susceptibility is conferred by an allele found on the 8.1AH and one or more other
sIBM susceptibility haplotypes, such as the 35.2AH. Price et al. (2004) refined the
8.1AH-derived sIBM susceptibility region to the border of the Class II and Class III
MHC regions, between PBX2 and HLA-DRB1. Given that the region defined by Price et
al. (2004), is the most likely location for a susceptibility allele shared by the 8.1AH and
other sIBM-associated haplotype, it was thus the focus of this thesis.
The gene content between PBX2 and HLA-DRB1 is very well characterised due to
importance of the MHC in infection and autoimmunity (Horton et al., 2004). Detailed
sequence data for this region, from cell lines carrying conserved haplotypes, is available
from the Sanger Institute MHC Haplotype Project
(http://www.sanger.ac.uk/HGP/Chr6/MHC/ Accessed 5/11/2007) (Allcock et al., 2002;
Stewart et al., 2004; Traherne et al., 2006b). This sequence data can be used to identify
all polymorphisms in the available haplotypes and report on variation within the MHC
as a whole (Stewart et al., 2004; Traherne et al., 2006b; Horton et al., 2008). The same
data can also be used to locate those polymorphisms haplotypic of the 8.1AH (ie. where
the minor allele of a particular polymorphism occurs on the 8.1AH), as well as their
position relative to genes, within the defined sIBM susceptibility region.
In this chapter, sequence data already available from conserved cell lines was utilised to
generate a sequence alignment with which polymorphisms haplotypic of the sIBM-
associated 8.1AH could be identified directly. Selected alleles were then evaluated in
subsequent chapters as potential sIBM susceptibility alleles, whether through the
60
presence of the allele in patients, carriage by multiple susceptibility haplotypes or in
further defining the probable susceptibility region.
For the purpose of this study, the region from the centromeric end of HLA-DRA to the
telomeric end of HLA-DRB1 was not analysed in detail. HLA-DRB3 is the only
expressed gene on the 8.1AH in this particular region, and is not part of the 35.2AH or
any of the other susceptibility haplotypes studied within the region (Chapter 5). In
addition, given that promoter and exonic alleles were the focus of locating a common
susceptibility allele (Chapter 6), it was not considered necessary to investigate alleles in
a gene found on only one of the studied haplotypes.
61
3.3 Results
3.3.1 Sequence alignment of the sIBM region
Genomic sequences from four haplotypes, spanning 269,558bp from 2,025bp telomeric
of RNF5 to the centromeric end of HLA-DRA on chromosome 6p21.3, were aligned
(Figure 3.1). The haplotypes analysed were derived from the 10IHW cell lines COX
(HLA-B8, DR3 - 8.1AH), PGF (HLA-B7, DR15 - 7.1AH), QBL (HLA-B18, DR3 -
18.2AH) and SSTO (HLA-B44, DR4 - 44.1AH). Raw sequence data was originally
assembled, published and made freely available through the Sanger Institute MHC
Haplotype Project (http://www.sanger.ac.uk/HGP/Chr6/MHC/ Accessed 5/11/2007)
(Allcock et al., 2002; Stewart et al., 2004; Traherne et al., 2006b). To perform the
alignment, it was necessary to identify contiguous BAC clones from each cell line,
determine the degree of overlap and then align them with manual checking.
The location of each gene was determined by aligning mRNA reference sequences
(NCBI, http://www.ncbi.nlm.nih.gov/sites/entrez?db=gene Accessed 14/5/2008) with
the genomic sequence. Specifically, the sequence data contained in the following
accension numbers were used; NM_006913 for RNF5, NM_001136 and NM_17297 for
the two AGER isoforms, NM_002586.3 for PBX2, NM_022107.1 for GPSM3,
NM_004557.2 for NOTCH4, NM_006781.2 for C6orf10, AL935032 for HCG23 and
NM_019111.2 for HLA-DRA. The updated sequence AY881999 was used for BTNL2,
as it was proposed to supersede the reference sequence due to the identification of a
previously unrecognised exon (Valentonyte et al., 2005).
62
HLA-DPB1
Centromere
HLA-DQB1
HLA-DRB1
C4B,A
TNFa,b
HLA-A HLA-B
HLA-C
HLA-DRA
Telomere
NOTCH4
BTNL2AGER
Aligned region
BTNL2C6orf10NOTCH4
GPSM3
PBX2
HCG23AGERHLA-DRA HLA-DRB1
HLA-DRB9 HLA-DRB2
HLA-DRB3
MHC Region
Figure 3.1: The 270kb region of the MHC at which sequence data from four cell lines; COX,
PGF, QBL and SSTO were aligned .
RNF5
Figure 3.1: The 270kb region of the MHC for which sequence data from the cell lines
COX, PGF, QBL and SSTO were aligned. The solid red-blocks represent expressed
genes while the others are pseudogenes. The gene content varies according to haplotype
between HLA-DRA and HLA-DRB1 and in this figure is representative of the 8.1AH
(Andersson et al., 1994).
3.3.2 Identification of polymorphisms
Following the alignment of genomic and mRNA sequences, polymorphisms that define
one or more of the aligned haplotypes could be identified by visual inspection. All
polymorphisms resulting from this alignment have been identified previously, assigned
rs numbers and are found in the NCBI SNP database
(http://www.ncbi.nlm.nih.gov/SNP/ Accessed 8/1/2008).
A summary of the variations within the aligned region is shown in Table 3.1 and a
complete list is available online (http://www.waimr.uwa.edu.au/docs/Appendix-Table-
A1p2.pdf). The region contained a total of 1782 variations (single nucleotide
polymorphisms, microsatellites and indels), with an average of 6.61 polymorphisms per
kb (one polymorphism every 151bp). More than one third of variations (658) were
found in COX (8.1AH) but not PGF (7.1AH), QBL (18.2AH) or SSTO (44.1AH). The
COX cell line also had the highest density of variations (one polymorphism every
410bp) followed by SSTO (one polymorphism every 556bp), with PGF and QBL
showing equivalent levels of variation density (one polymorphism every 1079bp and
1119bp respectively) (Table 3.1). The high number of intronic variations across all cell
lines is primarily attributed to the expansive introns that comprise C6orf10. In total,
63
76% (627/823) of all intronic variations across all four cell lines were associated with
C6orf10.
Figure 3.2 shows the distribution of all polymorphisms and COX-specific
polymorphisms along the region studied. The overall density of polymorphisms
between the four cell lines was consistently above four per kb for the entire region, with
the exception of the region around AGER, PBX2 and NOTCH4, as well as around
HCG23 and at the telomeric end of C6orf10 (Figure 3.2). The density of polymorphisms
haplotypic of the 8.1AH generally followed the overall density of polymorphisms
between all four cell lines (COX, PGF, QBL and SSTO) in the region, and were highest
between NOTCH4 and C6orf10, near the telomeric end of C6orf10, and centromeric of
BTNL2. The most notable exception to this was part of the region within C6orf10,
where the overall density of all polymorphisms remained above 6 per kb while the
density of 8.1AH-polymorphisms did not increase above 1 per kb (Figure 3.2).
Table 3.1: Composition, and location and density of variations overall, and variations specific to each cell line, within the aligned region.
SNPs Indels Microsatellite Complex Exonic Promoter Intronic Intergenic
Total no. 1498 85 174 25 48 60 823 851 1782 6.61
COX (8.1 AH)a
524 39 86 9 17 27 260 354 658 2.44
PGF (7.1 AH)a
178 8 56 8 7 9 141 93 250 0.93
QBL (18.2 AH)a
169 6 60 6 3 8 95 135 241 0.89
SSTO (44.1 AH)a
396 23 53 13 15 21 277 172 485 1.80
a - The variations shown are those found in the listed cell line, but not in any of the other three cell lines.
Variation Type LocationOverall Polymorphisms/kb
65
SNPs per 1kb, using 5kb window and sliding 1kb each time
0
2
4
6
8
10
12
14
16
18
0 50000 100000 150000 200000 250000
Position
no
. S
NP
s
ALL per 1kb 8.1? Per 1kb
AG
ER
PB
X2
GP
SM
3
NO
TC
H4
C6
orf1
0
HC
G2
3
BT
NL
2
HL
A-D
RA
po
lym
orp
hism
s kb
-1
0
Figure 6.1: Incidence of polymorphisms within 270kb from RNF5 to HLA-DRA. The black line shows the total number
of polymorphisms per 1kb found when comparing COX, PGF, QBL and SSTO, while the grey line shows those
polymorphisms haplotypic of COX but none of the other three cell lines. Calculations are based on a 5kb window, sliding
1kb for each data point.
Telo
mere
Cen
trom
ere
RN
F5
Figure 3.2: Incidence of polymorphisms within the 270kb from RNF5 to HLA-DRA. The black line shows the total number of polymorphisms per 1kb
found when comparing COX, PGF, QBL and SSTO, while the grey line shows those polymorphisms haplotypic of COX but none of the other three
cell lines. Calculations are based on a 5kb window, sliding 1kb for each data point.
66
3.4 Discussion
3.4.1 Summary
Existing sequence data from four conserved cell lines, including one carrying the
8.1AH, were aligned within the region of interest. Polymorphisms were then identified,
including coding and promoter region polymorphisms haplotypic of the 8.1AH. All
polymorphisms haplotypic of the sIBM-associated 8.1AH were completely identified
within the region from RNF5 to HLA-DRA.
A total density of 6.61 polymorphisms per kb was found within the region investigated.
This is consistent with the previous studies, which reported a higher than average level
of sequence variation for the MHC, at 3.87 polymorphisms per kb, compared to the
entire human genome at 0.4-0.9 polymorphisms per kb (Group, 2001; Stewart et al.,
2004).
3.4.2 Previous work
Past studies investigating polymorphic variation in the MHC on a large scale have been
published using the sequence data from the Sanger Institute MHC Haplotype Project
(Stewart et al., 2004; Traherne et al., 2006b). However, these focussed on comparing
sequence variation across the entire MHC from multiple haplotypes to assess both
individual variation and regions commonly inherited between haplotypes. Another
paper partially sequenced 46 HLA haplotypes to compare variation across the MHC, in
relation to evolutionary origin and disease association (Smith et al., 2006). However
none of these papers provided enough fine detail for individual SNPs in a specific
region, as was required for this thesis. The present study required knowledge of the
location of polymorphisms relative to genes and in particular, their specificity to the
sIBM-associated 8.1AH. A sequence alignment of the region of interest, as described in
this chapter, was thus necessary.
3.4.3 Future studies
Of the alleles identified in this chapter as haplotypic for the 8.1AH, any could be
directly involved in sIBM pathogenesis as conferred by the 8.1AH. Subsequent chapters
have examined these alleles as possible susceptibility alleles and used them to refine the
disease susceptibility region.
67
CHAPTER FOUR
4 INVESTIGATION OF NOTCH4 CODING REGION POLYMORPHISMS IN SIBM PATIENTS
68
4.1 Abstract
In this chapter, 8.1AH-haplotypic polymorphisms within the candidate sIBM
susceptibility gene NOTCH4 were investigated. Four coding region polymorphisms
haplotypic of the sIBM-associated 8.1AH were identified in NOTCH4 and genotyped in
cohorts of Caucasian sIBM patients from Australia and the United States of America.
After considering patient allele and genotype frequencies as well as the possible role for
each polymorphism in NOTCH4 and sIBM susceptibility, none of the alleles could be
directly associated with sIBM pathogenesis.
4.2 Introduction
It is well established that susceptibility to sIBM is influenced by a gene within the
MHC, however the mechanism of this susceptibility remains unknown. Assuming that
an autoimmune aetiology is important to the pathogenesis of sIBM, a genetic
susceptibility gene could confer susceptibility in one of three different ways;
1. The susceptibility gene is involved in the immune system and could make an
autoimmune response to a self-antigen more likely.
2. The susceptibility gene could alter the likelihood of generating a muscle-derived
self-antigen.
3. The susceptibility gene could affect a process completely unconnected to
immunity, such as through the formation of β-amyloid inclusions within the
muscle fibres
The first possibility, that of enhancing the likelihood of an autoimmune response,
suggests the involvement of an immune-related gene. Conversely the second possibility,
involving a genetic variation that facilitates the generation of a self-antigen, could
involve an immune or a non-immune related gene. Past studies of sIBM have shown
that the restricted gene arrangement of Vβ subfamilies is specific to those T-cells within
the sIBM-affected muscle, suggesting that the immune response is driven by an antigen
within the skeletal muscle itself (Dalakas et al., 2007; Salajegheh et al., 2007).
Therefore if a genetic variation generates an sIBM-associated self-antigen, it is likely to
influence a gene with a function specific to skeletal muscle. Of the genes within the
sIBM susceptibility region defined previously (Price et al., 2004), NOTCH4 appears
most likely to have a function dependent on tissue type.
69
NOTCH4 is one member of a family of genes that encode heterodimeric cell surface
receptors. The extracellular domain consists of a signal peptide, 29-36 tandem
Epidermal Growth Factor (EGF)-like repeats and 3 Lin/Notch repeats. The intracellular
domain consists of the transmembrane region, a RAM domain, 6 cdc10/ankyrin repeats,
the Notch Cytokine Response (NCR) region (containing 2 nuclear localisation signals),
the OPA sequence, and a PEST domain. Different NOTCH proteins vary in the number
of EGF-like repeats and in the sequences that are found in the intracellular domain
(Uyttendaele et al., 1996). Of the Notch homologues, NOTCH4 is the most divergent.
Specifically, NOTCH4 has only 29 EGF repeats, a short intracellular domain and no
OPA sequence or NCR elements (Figure 4.1) (Uyttendaele et al., 1996; Sugaya et al.,
1997).
29x EGF repeats3x Lin12/Notch
repeats
Transmembrane
DomainRAM23
6x CDC10/ankyrin
repeats
PEST
Intracellular regionExtracellular region
Figure 4.1: Protein structure of NOTCH4. Adapted from Uyttendaele et al (1996) and Linheng et al (1998)
Signal peptide
Figure 4.1: Protein structure of NOTCH4. Adapted from Uyttendaele et al. (1996) and
Linheng et al. (1998)
Northern blot analysis identified two cDNA isoforms – the major NOTCH4(S)
transcript and a minor NOTCH4(L) transcript. NOTCH4(L) contains the intronic
sequences between exons 11 and 12 and exons 20 and 21, and is thought to encode two
additional proteins, one containing 7 EGF repeats, and the other encoding the
transmembrane region and intracellular domain (Li et al., 1998). The function of the
NOTCH4(L) isoform has not been investigated in subsequent studies.
While the particulars of NOTCH4 function remain elusive, the NOTCH gene family acts
as a driver of general cell development in many cell types, including skeletal muscle,
from embryonic to adult life and with effects dependent on the conditions and cell type
(Li et al., 1998; Artavanis-Tsakonas et al., 1999; Kadesch, 2004). It could thus be
70
hypothesised that the molecular targets and binding partners of NOTCH4 in skeletal
muscle may vary from those of other tissues, presenting the possibility of a muscle-
specific effect of NOTCH4 variants.
Of note is that NOTCH4 mRNA expression is inversely related to the differentiation of
neurospheres into neurons (Coowar et al., 2004) and active murine Notch4 can enhance
stem cell activity, reduce cellular differentiation and alter lymphoid development
(Vercauteren and Sutherland, 2004). In sIBM patients, myogenic differentiation of
mesoangiblasts into skeletal myotubes is severely impaired (Morosetti et al., 2006).
Genes involved in regulating cellular differentiation, such as NOTCH4, are thus
candidates for playing a role in this aspect of sIBM pathology.
Given the expression of NOTCH4 in skeletal muscle (Li et al., 1998) and its role in
cellular differentiation, NOTCH4 may play a role in the pathogenesis of sIBM by either
inhibiting the regeneration of skeletal muscle fibres, or generating antigens specific to
skeletal muscle fibres as an aberrant protein. It is also possible that genetic variations
within NOTCH4 might influence susceptibility to sIBM. Therefore, the association of
probable NOTCH4 functional variants with sIBM was investigated, just as NOTCH4
variants had been previously investigated for association with other diseases, such as
schizophrenia, narcolepsy and salivary gland tumour (Ando et al., 1997a; Ando et al.,
1997b; Wei and Hemmings, 2000; Zhang et al., 2004; Wang et al., 2006).
The NOTCH4 variants most likely to affect function, specifically non-synonymous
polymorphisms within the coding region, were the focus of this analysis.
Polymorphisms likely to alter gene expression, such as those in the promoter region,
were not considered due to a previous study that found no significant changes in
NOTCH4 mRNA expression in sIBM patients (Greenberg et al., 2002). Specific
polymorphisms were also selected where the minor allele was found in the 8.1AH.
71
4.3 Results
4.3.1 Selection of polymorphisms
Polymorphisms were selected from the sequence alignment described in Chapter 3.
Sequence comparison of the NOTCH4 coding region showed five polymorphisms
where the minor allele was found in the COX cell line (8.1AH), but not PGF (7.1AH),
QBL (18.2AH) and SSTO (44.1AH). The minor (rare) alleles for rs3134942 and
rs443198 were synonymous mutations. The minor alleles for rs422951 and rs915894
were missense mutations (Table 4.1). The fifth polymorphism is a CTGn microsatellite
that codes for a variable number of leucine residues in the NOTCH4 signal sequence.
The microsatellite is listed in 3‘-5‘ in dbSNP (CAGn), as rs9281675. The 12-repeat
variation of rs9281675 was found in the 8.1AH cell line only.
Table 4.1: Alleles from the NOTCH4 coding region that are found in the COX cell line
(8.1AH) but not PGF (7.1AH), QBL (18.2AH) or SSTO (44.1AH).
Allele Nucleotide Changea
Amino Acid
Change
rs3134942 C > A V-->V
rs422951 A > G T-->A
rs915894 A > C K-->Q
rs443198 T > C G-->G
rs9281675b 6 - 12 CTG 6L - 12L
a - The nucleotide change shows the alteration from the major (first) allele to the minor
(second) allele. The minor allele is found on the 8.1AH.
b - The microsatellite rs9281675 is also referred to as rs28359855, representing a
different repeat number to rs9281675. The relevant entries in dbSNP record the repeat
in the 3‘-5‘ orientation relative to NOTCH4, as a CAG microsatellite.
The rs3134942 and rs443198 alleles do not alter the NOTCH4 amino acid sequence (ie.
are synonymous mutations). Diseases arising from splice sites created by synonymous
mutations have been reported previously (Richard and Beckman, 1995; Richard et al.,
2007; Ramser et al., 2008). However these two synonymous variants do not increase the
likelihood of a splicing event at that position, as determined by splice site prediction
(http://www.fruitfly.org/seq_tools/splice.html Accessed 24-11-2008). The rs3134942
polymorphism was not studied further. However the rs443198 allele was included in the
study, as it was close enough to rs915894 that a single pair of primers could be designed
to analyse both alleles within a single amplicon.
72
4.3.2 Allele genotyping
The four NOTCH4 coding region polymorphisms were genotyped by RFLP and direct
sequencing (Sections 2.2.5 – 2.2.6). DNA samples from the Australian (Table 4.2) and
American (Table 4.3) patient cohorts (Section 2.1.1 – 2.1.2) totalling 74 and 28 patients
respectively were analysed. Differences in allele and genotype frequencies were
evaluated using the chi squared (χ2) test and Fisher‘s exact test (Table 4.4).
The minor allele frequencies for rs422951, rs915894 and rs443198 in healthy controls
were drawn from dbSNP (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp
Accessed 15-2-2008), with the CEU (Caucasian) population used. The CEU population
consists of 60 unrelated Utah residents with ancestry from northern and western Europe.
The control frequency used for rs9281675 was a cohort of 161 healthy British
Caucasians born in the U.K. and Ireland. The cohort had originally been used in a study
investigating rs9281675 in relation to schizophrenia (Sklar et al., 2001)
Patient
no.
AU_1 18 27 A A A A T T 10r 14r 3 3
AU_3 8 51 A A NDb
ND ND ND 10r 10r 1 13
AU_4 40 40 A G A C T C 9r 12r 3 13
AU_5 5 8 A G C C C C 9r 12r 3 13
AU_6 8 35 G G A C T C 6r 12r 1 3
AU_7 8 40 A G A C T C 10r 12r 3 4
AU_8 8 44 G G A C T C 6r 12r 01 0301
AU_9 8 35 A G A C T C 10r 12r 1 3
AU_10 8 44 A G A C T C 10r 12r 3 3
AU_12 8 44 A G A C T C 9r 12r 3 13
AU_13 8 15 A G A C T C 10r 12r 3 6
AU_14 7 51 A G A A T C 9r 10r 3 7
AU_15 8 ND A G A C T C 10r 12r 3 13
AU_16 8 35 G G A A T T 6r 12r 1 3
AU_17 7 38 A G A C T C 10r 12r 03 15
AU_18 4 14 A A A A T T 10r 10r 1 13
AU_19 7 8 A G A C T C 10r 12r 3 15
AU_20 8 51 G G A C T C 11r 12r 3 13
AU_21 8 15 A G ND ND ND ND 10r 12r 0301 1301
AU_22 7 35 G G A C T C 11r 12r 3 13
AU_23 8 8 A G C C T C 10r 12r 1 3
AU_28 8 8 A G A C T C 9r 12r 3 13
AU_29 5 44 A G A C C C 9r 10r 1001 1502
AU_32 8 15 G G A C T C 9r 12r 0301 1001
AU_33 8 7 G G C C T C 10r 12r 03 08
AU_34 07 4002 A G A C T C 5r 9r 0107 0401
AU_35 0801 2705 A G A C T C 10r 12r 0101 0301
AU_36 7 8 A A A C T C 10r 10r 0101 0401
AU_37 08 4402 A G C C C C 10r 12r 0301 0401
AU_41 3901 1501 A A A A T T 9r 9r 03 16
AU_42 4403 0801 G G C C T C 10r 12r 0101 0301
AU_43 0801 4102 G G C C C C 9r 12r 0301 1303
AU_45 0801 3801 G G C C C C 12r 12r 0301 0301
AU_46 5101 5101 G A A A T C 9r 10r 0301 701
AU_47 07 5201 G G A C T C 10r 10r 1501 1502
AU_48 0801 4901 A G A C T C 9r 12r 0301 1101
AU_49 0801 1501 A G A C T C 10r 12r 0301 1301
AU_50 1501 1801 A G A C T C 10r 12r 0301 1301/02
AU_51 0801 4001 G G C C T C 10r 12r 0301 1301
AU_52 8 44 G G A C C C 9r 12r 0301 1001
AU_53 07 51 A A A A T T 10r 10r 0301 1301
AU_54 0801 3501 A G A C T C 10r 12r 0101 0301
AU_55 0801 3901 A G A C T C 9r 12r 0301 1601
AU_56 07 15 A G A A T T 6r 10r 0101 0101
AU_57 5201 5703 A G A C T C 10r 11r 11 15
AU_58 3501 3906 A G A C T T 10r 10r 0103 0801
AU_59 0801 4001 A G A C T C 9r 12r 0101 0301
AU_60 0801 4402 G G C C C C 12r 12r 0301 1501
AU_61 0801 15 A G A C T C 10r 12r 0101 0301
AU_62 3501 4102 A G A C T C 10r 10r 0101 0101
AU_63 3901 4402 A G C C T C 10r 10r 0401 0801/02
AU_64 0801 15 A G C C T C 10r 12r 0301 1301
AU_65 1501 4001 A A A A T T 10r 10r 0401 0404
AU_66 1801 4403 A A A C T C 9r 9r 0701 1501
AU_67 0801 0801 G G C C C C 12r 12r 0301 0301
AU_69 0801 4402 A G A C T C 10r 12r 0101 0301
AU_70 0801 1501 G G A C T C 6r 12r 0101 0301
AU_71 08 3701 G G A C C C 9r 12r 0301 1001
AU_72 0702 5701 A G A C T C 9r 10r 0101 0701
AU_73 2705 5701 A G A C T C 9r 10r 0401 0701
AU_74 1801 3501 A A A A T T 10r 10r 0101 0301
AU_75 0702 4402 A G A A T T 6r 10r 0101 0301
AU_76 3501 4501 A G A C T C 10r 12r 0301 1301
AU_77 0801 4901 A G A C C C 9r 12r 0301 0301
AU_78 1302 2705 A G A C T C 10r 13r 0401 0701
AU_79 0801 1501 A G A C T C 10r 12r 0301 1301/02
AU_80 3906 4901 A G A A T T 6r 10r 0404 1501
AU_81 1501 4402 A A A C T C 9r 10r 0401 1301
AU_82 0801 4402 A G A C T C 10r 12r 0101 0301
AU_83 3501 4501 G G A A T T 6r 10r 0101 1101
AU_84 0801 3501 A G A C T C 10r 12r ND ND
AU_85 3502 5201 A G A C T C 10r 11r 1101/04 1501/02
AU_86 0801 0801 G G C C C C 12r 12r 0301 0301
AU_87 0801 1501 A G A C T C 10r 12r 0301 1301
a - The minor allele for each SNP is given in brackets and marked in red.
b - ND = Not determined
Table 4.2: NOTCH4 polymorphisms within the Australian cohort.
HLA-B*rs422951
(G)a
rs915894
(C)
rs443198
(C)rs9281675 HLA-DRB1*
Patient
AM_1 4001 0702 A G A A T C 6r 9r 1001 1602
AM_2 5601 0702 A G A A T T 10r 11r NDb
ND
AM_3 4402 0702 A A A C T C 9r 10r 0101 1301
AM_4 1501 1510 A G A A T C 9r 10r 0101 1001
AM_5 2702 3502 G G A A T T 11r 11r 1101 1101
AM_6 4901 0801 G G A A C C 9r 12r 0301 1001
AM_7 1801 3501 A G A C T T 10r 12r 0101 0301
AM_8 4403 3502 G G A A T T 6r 11r 0101 1104
AM_9 3501 3901 A G A A T T 10r 11r 0101 1101
AM_10 4402 5101 A G A A T T 6r 6r 0101 1602
AM_11 0702 0801 A G A C T C 10r 12r 0101 0301
AM_12 4001 0801 G G C C T C 10r 12r 0301 0801
AM_13 1801 3501 A G A A T T 6r 10r 0101 1501
AM_14 0801 1501 A G A C T C 10r 12r 0101 0301
AM_15 3501 3906 A G A C T C 6r 9r 0101 1301
AM_16 4402 4901 A A A C T C 9r 10r 0101 1301
AM_17 4402 5101 G G A C T T 6r 10r 0801 1101
AM_18 0801 3906 G G C C T C 10r 12r 0301 0801
AM_19 1510 4201 A A A A T T 9r ND 0302 1503
AM_20 1801 4001 G G A C T C 11r 12r 0301 1104
AM_21 5001 0801 A G C C C C 9r 12r 0301 0301
AM_22 2705 0801 A G A C T C 10r 12r 0101 0301
AM_23 1501 0801 G G A C T C 9r 12r 0301 1301
AM_24 0801 5201 A G C C C C 10r 12r 0301 1501
AM_25 4001 0801 G G C C T C 10r 12r 0301 0801
AM_26 0702 0801 A G A C T C 10r 12r 0301 1501
AM_27 0801 5101 A G A C T C 9r 12r 0301 0301
AM_28 0801 0801 G G C C C C 12r 12r 0301 0301
a - The minor allele for each SNP is given in brackets and marked in red.
b - ND = Not determined
Table 4.3: NOTCH4 polymorphisms within the American cohort.
HLA-B* rs422951
(G)a
rs915894
(C)
rs443198
(C)rs9281675 HLA-DRB1*
Australian Patients American Patients Controlsa
% (n/total) p-value OR (95%CI) % (n/total) p-value OR (95%CI) % (n/total)
rs422951 G 56.1 (83/148) 0.002 2.21 (1.35-3.61) 64.3 (36/56) 0.001 3.10 (1.61-6.02) 36.7 (44/120)
AG 60.8 (45/74) 0.056 2.03 (1.02-4.05) 53.6 (15/28) 0.492 1.51 (0.61-3.72) 43.3 (26/60)
GG 25.7 (19/74) 0.142 1.96 (0.81-4.72) 35.7 (10/28) 0.049 3.15 (1.10-8.98) 15 (9/60)
AG/GG 86.5 (64/74) <0.001 4.57 (1.97-10.60) 89.3 (25/28) 0.003 5.95 (1.62-21.90) 58.3 (35/60)
rs915894 C 50.0 (72/144) 0.002 2.22 (1.33-3.71) 44.6 (25/56) 0.091 1.79 (0.93-3.46) 31.0 (36/116)
AC 63.9 (46/72) 0.001 3.36 (1.63-6.93) 42.9 (12/28) 0.483 1.43 (0.57-3.59) 34.5 (20/58)
CC 18.1 (13/72) 0.633 1.38 (0.53-3.59) 21.4 (6/28) 0.370 1.70 (0.53-5.50) 13.8 (8/58)
AC/CC 81.9 (59/72) <0.001 4.86 (2.20-10.73) 64.3 (18/28) 0.176 1.93 (0.76-4.88) 48.3 (28/58)
rs443198 C 49.3 (71/144) 0.001 2.36 (1.42-3.94) 42.9 (24/56) 0.087 1.82 (0.94-3.52) 29.2 (35/120)
TC 68.1 (49/72) <0.001 4.60 (2.20-9.59) 53.6 (15/28) 0.062 2.49 (0.99-6.25) 31.7 (19/60)
CC 15.3 (11/72) 0.808 1.17 (0.44-3.13) 14.3 (4/28) 1 1.08 (0.30-3.95) 13.3 (8/60)
TC/CC 83.3 (60/72) <0.001 6.11 (2.74-13.62) 67.9 (19/28) 0.066 2.58 (1.01-6.62) 45.0 (27/60)
rs9281675 5r 0.7 (1/148) 1 1.09 (0.10-12.10) 0.0 (0/56) 1 N/A 0.6 (2/322)
6r 5.4 (8/148) 0.439 0.68 (0.30-1.54) 12.5 (7/56) 0.294 1.70 (0.70-4.14) 7.8 (25/322)
9r 15.5 (23/148) 0.085 0.63 (0.37-1.05) 17.9 (10/56) 0.488 0.74 (0.36-1.54) 22.7 (73/322)
10r 39.9 (59/148) 0.194 0.76 (0.51-1.13) 28.6 (16/56) 0.013 0.46 (0.25-0.85) 46.6 (150/322)
11r 2.7 (4/148) 0.240 0.50 (0.16-1.51) 10.7 (6/56) 0.129 2.15 (0.81-5.72) 5.3 (17/322)
12r 34.5 (51/148) <0.001 2.86 (1.82-4.50) 28.6 (16/56) 0.022 2.18 (1.13-4.18) 15.5 (50/322)
13r 0.7 (1/148) 0.670 0.43 (0.05-3.72) 0.0 (0/56) 1 N/A 1.6 (5/322)
14r 0.7 (1/148) 0.315 N/A 0.0 (0/56) 1 N/A 0.0 (0/322)
Table 4.4: Frequency of NOTCH4 polymorphism alleles and genotypes in the
Australian and American cohorts compared with a control population.
Allele/Genotype
a - The control population used for rs422951, rs915894 and rs443198 was the Caucasian "CEU" population, available from dbSNP
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp; Accessed 15-2-2008). The control population data used for rs9281675 was a
cohort of British Caucasians originally utilised by Sklar et al., 2001.
76
4.3.3 NOTCH4 SNPs in the Australian cohort
Within the Australian cohort, increased allelic frequencies with statistical significance
were observed for the minor allele of rs422951 (OR=2.21, p=0.002), rs915894
(OR=2.22, p=0.002) and rs443198 (OR=2.36, p=0.001). Individuals homozygous for
the rare allele were not increased for any of the three SNPs. However, a higher
frequency of heterozygotes was observed in patients for rs915894 (OR=3.36, p=0.001)
and rs443198 (OR=4.60, p<0.001), but not rs422951 (p=0.056). For both the rs195894
and rs443198 alleles, the heterozygotes were statistically significantly increased in the
patient cohort whereas the frequency of homozygotes for the minor allele was not.
When homozygous and heterozygous genotypes containing the rare allele were
considered together, rs422951, rs915894 and rs443198 were found at an increased
frequency of at least 81.9% in patients, with statistically significant (p<0.001) odds
ratios of at least 4.5 (Table 4.4).
4.3.4 NOTCH4 SNPs in the American cohort
Within the American cohort, only the minor allele of rs422951 showed an increased
allele frequency in patients (OR=3.10, p=0.001). The homozygous rare genotype for
rs422951 was also increased (OR=3.15, p=0.49), as were, when considered together,
genotypes carrying the rs422951 minor allele (OR=5.95, p=0.003). Of the three SNPs
investigated, presence of the minor allele in patients was highest for rs422951 (89.3%).
The allele and genotype frequencies for rs915894 and rs443198 showed no statistically
significant changes in frequency between the American patient and control cohorts
(Table 4.4).
4.3.5 The rs9281675 microsatellite
The 12-repeat variant of rs9281675 showed an increased frequency in both the
Australian (OR=2.86, p<0.001) and American (OR=2.18, p=0.022) patient cohorts
(Table 4.4). This variation was observed in 64% (47/74) and 55% (15/28) of patients in
the Australian and American cohorts respectively. In addition, the 10 repeat variation
was less frequent in the American cohort (OR=0.46, p=0.013), but not the Australian
cohort (p=0.194).
77
4.3.6 Carriage of all investigated 8.1AH alleles
A sub-group of each cohort was also considered, consisting of all individuals carrying at
least one of the minor alleles investigated and genotyped for HLA-DRB1 plus all four
investigated loci. This totalled 71 patients from the Australian cohort and 26 patients
from the American cohort (Table 4.5). Of those patients carrying at least one minor
allele, co-occurrence of all four minor alleles was observed in 68% (44/65) of the
Australian patients and 50% (13/26) of the American patients. Carriage of the 8.1AH-
associated HLA-DRB1*0301 or its serological equivalent HLA-DR3 was similar (48/65
for 74% and 15/26 for 58% of Australian and American patients respectively; Table
4.5). All patients carrying the four 8.1AH-haplotypic NOTCH4 alleles also carried
HLA-DRB1*0301
Table 4.5: Proportion of patients carrying at least one of the NOTCH4 minor alleles
(haplotypic of the 8.1AH).
Australian Cohort
(n=71)a
American Cohort
(n=26)a
Carries at least one minor allele 92% (65/71) 100% (26/26)
- Also carries all four 8.1AH alleles 68% (44/65) 50% (13/26)
- Also carries HLA-DR3 74% (48/65) 58% (15/26)
a – Only patients with genotyping results for all four NOTCH4 alleles and HLA-DR
were included.
78
4.4 Discussion
4.4.1 Summary
Given the presence of NOTCH4 within the previously defined sIBM susceptibility
region and its role in cellular differentiation, polymorphisms within the NOTCH4
coding region were identified and assessed within the Caucasian patient cohorts. Four
coding region polymorphisms for which the minor allele was characteristic of the sIBM-
associated 8.lAH were investigated. None of the minor alleles were found in 100% of
sIBM patients, although rs422951, rs915894, rs443198 were found in at least 81% of
Australian patients and rs422951 in 89.3% of American patients.
One study of a family with multiple generations of individuals with fIBM suggested an
autosomal dominant pattern of genetic association for sIBM (Neville et al., 1992). This
is supported by the increase in frequency of heterozygotes over homozygous rare
genotypes of rs915894 and rs4423198 in the Australian cohort (Table 4.4). Conversely
the homozygous rare rs422951 genotype in the American cohort instead suggests an
autosomal recessive pattern of inheritance. Such an observation would also occur if the
homozygous rare genotype was over-represented in the population, possibly due to
being more severe and thus easier to diagnose. Given the weak p-value (0.049) and
small cohort size (28 patients total) the increased frequency of the homozygous rare
genotype may have been the result of a type I statistical error (false positive).
4.4.2 Comparison of the Australian and American cohorts
A broad comparison of the alleles and genotypes investigated showed that with the
exception of some of the microsatellite repeats for rs9281675, the trends in p-values
were largely consistent between the Australian and American cohorts. However
statistical significance in the Australian cohort was often not replicated in the American
cohort (Table 4.4). This may be an indicator that the American cohort has a different
genetic composition to that of the Australian cohort. An alternative explanation is that
the observed difference in statistical significance was the result of a lack of statistical
power in the American cohort, given that it was less than half the size of the Australian
cohort.
A type 1 error (false positive) from a sampling bias or lack of statistical power is
unlikely to be replicated in two different populations for a given allele or genotype.
79
Hence those alleles that were increased in both sIBM cohorts, specifically the minor
allele of rs422951 and the 12-repeat variation for rs9281675, are probably not the result
of a type I error. The presence of these alleles and genotypes can thus be considered
markers for sIBM susceptibility.
4.4.3 Linkage disequilibrium
The question of whether the alleles investigated directly influence sIBM susceptibility is
another matter. The challenge inherent with investigating alleles within regions of
strong linkage disequilibrium, such as the MHC, is that an allele associated with a given
disease is not necessarily the cause of that disease association. The allele could instead
be inherited along with the causative allele as a result of strong linkage disequilibrium
between the markers analysed.
The effect of linkage disequilibrium within NOTCH4 can be observed in the co-
occurrence of all four minor alleles in most of the patients who carried at least one of
the minor alleles (Table 4.5). Furthermore, carriage of all four minor alleles was always
in conjunction with HLA-DRB1*0301, suggesting that in those patients, the alleles were
carried together as part of the 8.1AH, defined by HLA-B*0801, HLA-DRB1*0301
(Cattley et al., 2000). Thus, while the minor alleles of rs422951, rs915894, rs443198
and rs9281675 were all associated with sIBM in at least one of the two cohorts,
association analysis could further dissect their involvement with sIBM from their
carriage with the 8.1AH.
Carriage of some, but not all, of the investigated NOTCH4 minor alleles and HLA-DR3
does not necessarily suggest carriage of only part of the 8.1AH. It may instead result
from the carriage of these alleles on haplotypes other than the 8.1AH. For example,
within the controls the minor alleles for rs422951, rs915894, rs443198 and rs9281675
were found at frequencies of 36.7%, 31%, 29.2% and 15.5% respectively. The 8.1AH is
found at a frequency of 10-11% in Caucasian populations (Garlepp et al., 1994; Price et
al., 1999), and so with the possible exception of the minor allele at rs9281675, it is
unlikely that any of the three alleles are unique to the 8.1AH. Therefore, whilst carriage
of all four of the NOTCH4 minor alleles investigated strongly suggests the presence of
the 8.1AH, carriage of only some of the NOTCH4 minor alleles is instead indicative of a
non-8.1AH that carries those particular minor alleles.
80
4.4.4 The dilution of alleles by non-sIBM associated AHs
Association studies need to be carefully interpreted, given the degree of linkage
disequilibrium in the MHC. It is critical to note that an allele in linkage disequilibrium
with the causative disease susceptibility allele can also be carried without the causative
allele. A clear demonstration of this was found when comparing the COX, PGF, QBL,
and SSTO cell lines to identify COX-specific alleles (Chapter 3). A given allele was
often common to multiple haplotypes, of which only one, the 8.1AH, was associated
with sIBM. An allele would therefore only be associated with sIBM when it is carried
with a haplotype that also carries the causative sIBM allele itself.
The frequencies of non-sIBM associated haplotypes carrying the allele of interest would
not differ between patients and the normal population, or may decrease if the non-
disease causing AHs are reduced in patients due to a respective increase in the disease-
associated AH. This would effectively dilute, or offset any observed increase of the
allele in conjunction with the sIBM-associated haplotype (Figure 4.2).
Allele is not specific to the
disease-associated AH
Allele is specific to the
disease-associated AH
Disease
associated AH
Allele freq
uen
cy
Allele freq
uen
cy
Non-disease
associated AH
PatientsControls PatientsControls
Disease
associated AH
Figure X: Diagrammatic representation of the diluting effect observed in alleles not specific to the disease-associated haplotype.
The frequency of non-disease associated haplotypes would not increase in patients. Thus alleles not specific to the disease-
associated haplotype (A) would show a proportionately lower increase in frequency and thus odds ratio than an allele unique to the
disease-associated haplotype (B)
A B
Figure 4.2: The diluting effect observed in alleles not specific to the disease-associated
haplotype. The frequency of non-disease associated haplotypes would not increase in
patients. Thus alleles not specific to the disease-associated haplotype (A) would show a
proportionately lower increase in frequency and thus odds ratio than an allele unique to
the disease-associated haplotype (B).
The dilution of sIBM-associated alleles by non-disease associated haplotypes would
also affect the odds ratio observed for a given allele. Alleles found in both sIBM and
non-sIBM associated haplotypes would show a lower odds ratio. Therefore, a high odds
ratio for a given allele in the sIBM-affected cohort does not suggest a more likely role in
disease causation. Rather, it can be a reflection of how specific that allele is to the
disease-associated AH itself.
81
Given that a diluting effect will be relative to how specific that allele is to the disease-
associated haplotype, an allele that is haplospecific for the 8.1AH is much more likely
to show a statistically significantly increased frequency in patients, compared to an
allele haplotypic of the 8.1AH and multiple other non-disease associated haplotypes. As
argued previously (Chapter 4.4.3), it is unlikely that any of the investigated NOTCH4
minor alleles are unique to the 8.1AH, with the possible exception of the rs9281675 12
repeat allele. This is further reinforced by the observation that carriage of one or two of
the NOTCH4 alleles could occur independently of the other 8.1AH-haplotypic alleles or
HLA-DRB1*0301 (Table 4.5). If all four NOTCH4 minor alleles were unique to the
sIBM-associated 8.1AH, then with the very rare exception of a recombination event
between the alleles, co-occurrence of the minor alleles would be expected in all patients
carrying at least one of the alleles. Given that this was not the case in this patient cohort,
the alleles investigated may thus be influenced by any diluting effect from non-sIBM
associated haplotypes. This may have contributed to some of the NOTCH4 rare alleles
and genotypes not showing a statistically significantly increased frequency in patients,
such as the heterozygous genotype for rs422951 and the homozygous rare genotype for
all three NOTCH4 SNPs in the Australian cohort. The specificity of the NOTCH4 minor
alleles have been investigated in more detail in Chapter 5.
4.4.5 Possible allele function
Of the alleles investigated, rs915894 and rs422951 cause missense mutations, resulting
in lysine to glutamine and threonine to alanine amino acid changes, respectively. These
alleles are located in the 2nd
and 8th
EGF repeats of NOTCH4, respectively, and may
thus alter the receptor binding affinity or specificity. The amino acids coded by
rs422951 and rs915894 are not conserved between species (Sugaya et al., 1997), which
suggests that the variant alleles are unlikely to be critical to NOTCH4 function. The
alleles rs422951 and rs915894 have both been previously investigated for a possible
association with schizophrenia, although no link was identified (Zhang et al., 2004;
Wang et al., 2006).
As a synonymous mutation, rs443198 could affect gene expression by altering
translation. Alteration of translation could arise, for example, from differences in the
relative abundances of the individual codon tRNAs, by the introduction of splicing
variants, or by alteration of an exonic splice enhancer. Diseases arising from
synonymous mutations have been reported previously (Richard and Beckman, 1995;
82
Richard et al., 2007; Ramser et al., 2008), and it is possible that the minor allele for
rs443198 could have the same effect.
The rs9281675 3bp microsatellite is unusual in that it is located in the NOTCH4 signal
peptide. The rs9281675 allele alters the number of leucine residues in the h-region of
the signal peptide. A longer h-region, as caused by rs9281675, decreases the probability
of signal sequence cleavage during post-translational modification (Martoglio and
Dobberstein, 1998). Ordinarily, the cleaved signal peptide is processed and expressed
on the cell surface in association with HLA class I MHC molecules (Martoglio and
Dobberstein, 1998). Reduced presentation of the NOTCH4 signal peptide could thus
play a role in sIBM susceptibility, although the mechanism by which this could function
is not clear. Also of note is that the larger 13 and 14-repeat variations of the rs9281675
were not found at an increased frequency in patients (Table 4.4). Hence such an
association would need to be proved by observing the cell surface expression of
NOTCH4 before any theory describing a correlation between sIBM susceptibility and
an enlarged signal peptide h-region in NOTCH4 would be viable.
The rs9281675 microsatellite has previously been studied in schizophrenia, narcolepsy
and salivary gland tumours. The observed association with schizophrenia was with the
common 10-repeat allele (Wei and Hemmings, 2000), rather than the 12 repeat allele
found to be increased among sIBM patients. Subsequent studies have provided
conflicting results and so the exact nature of an association between NOTCH4 and
schizophrenia has not been defined (Zhang et al., 2004; Wang et al., 2006). In the two
studies that assessed rs9281675 in patients with narcolepsy or salivary gland tumours
(Ando et al., 1997a; Ando et al., 1997b), no significant association was found that could
not be accounted for by linkage disequilibrium with HLA alleles previously reported to
associate with the disease.
4.4.6 Future studies
In this chapter, NOTCH4 was screened for potential coding region alleles that might
play a role in sIBM. Four candidate polymorphisms in the NOTCH4 coding region with
minor alleles haplotypic of the 8.1AH were identified and screened against patients
from the Australian and American sIBM cohorts.
83
Of the alleles studied in this chapter, rs422951 and rs9281675 are both of particular
interest with regards to sIBM susceptibility. The minor allele for rs422951 is a missense
mutation that was present in 86.5% and 89.3% of sIBM patients in the Australian and
American cohorts respectively, and may influence NOTCH4 receptor binding and
affinity in sIBM-affected patients. The occurrence of rs9281675 in the NOTCH4 signal
peptide may influence presentation of the gene product at the cell surface. Further
investigation of these alleles should thus focus on their effect on ligand specificity and
cell surface presentation of NOTCH4 in sIBM patients.
Linkage disequilibrium is a considerable hurdle in identifying the source of an observed
association with sIBM. A strong association between sIBM and a given allele will
mostly be a reflection of its presence on the disease-associated haplotypes in that region.
A simple association study is thus insufficient in defining the source of an observed
MHC disease association. One approach is to consider the effect of variant alleles on
gene function and expression, which can provide clues to a possible role in sIBM
susceptibility. More conclusive evidence can be obtained by directly analysing the
functional effect of an allele on NOTCH4 in patients.
An alternative approach to identifying an sIBM susceptibility allele is to investigate the
haplotypic distribution of alleles in candidate sIBM susceptibility genes. An allele
common to all sIBM susceptibility haplotypes would be a strong contender for
conferring sIBM susceptibility, although the confounding effect of strong linkage
disequilibrium may still apply. A possible role for any of the investigated NOTCH4
alleles in sIBM susceptibility may therefore be inferred by the degree of specificity to
the 8.1AH and other sIBM susceptibility haplotypes. Alternatively, different alleles in
different susceptibility haplotypes could have the same effect on gene expression or
protein function. For example, multiple different mutations in a disease-associated gene
such as ACTA1 (Nowak et al., 2007) cause the same muscle disease phenotypes, despite
the mutations originating on different haplotypic backgrounds.
Although two alleles of interest were identified, this preliminary investigation of
NOTCH4 variants on the 8.1AH was unable to determine conclusively whether either
allele was responsible for conferring susceptibility to sIBM. This was due to the strong
linkage disequilibrium associated with the sIBM-associated 8.1AH. A more systematic
investigation of possible susceptibility alleles was subsequently undertaken.
84
Specifically, haplotypes associated with sIBM (Chapter 5) were used to identify and
investigate potential susceptibility alleles that are common between these haplotypes
(Chapter 6).
85
CHAPTER FIVE
5 HLA ALLELE AND ANCESTRAL HAPLOTYPE
ASSOCIATIONS IN THE AUSTRALIAN, AMERICAN AND
JAPANESE COHORTS
86
5.1 Abstract
In order to confirm the results of previous genetic susceptibility studies, HLA allele and
haplotype associations were assessed in sIBM patients. Three sIBM patient cohorts,
consisting of individuals from Australia, the United States of America (Caucasian) and
Japan were assembled and genotyped for HLA-B and HLA-DRB1 alleles. HLA allele
genotyping confirmed the association between the 8.1AH and sIBM, and associations
were also found for 7.2AH and 52.1AH in Caucasian and Japanese patients
respectively. This is the first identified MHC association for sIBM in the Japanese.
5.2 Introduction
Previous studies of the genetic factors influencing sIBM have mostly focussed on HLA
alleles in Caucasian sIBM cohorts because of the higher prevalence of sIBM in
Caucasians compared to other ethnicities (Shamim et al., 2002; Needham and
Mastaglia, 2007).
In Caucasian patient cohorts, sIBM has consistently shown a strong association with
carriage of HLA-DRB1*0301 and other alleles that define the 8.1AH (HLA-A1, HLA-
B8, HLA-DRB3*0101, HLA-DRB1*0301, HLA-DQB1*0201) (Love et al., 1991;
Garlepp et al., 1994; Garlepp et al., 1998; Koffman et al., 1998b; Lampe et al., 2003;
Badrising et al., 2004; Price et al., 2004; O'Hanlon et al., 2005). The HLA-DRB1*0101
allele has also been associated with sIBM susceptibility (Koffman et al., 1998b). In
Caucasians, HLA-DRB1*0101 is a component of the 35.2AH (Price et al., 2004;
O'Hanlon et al., 2005), characterised by HLA-A*1101, HLA-B*3501, HLA-DRB1*0101,
HLA-DQB1*0501 (Table A1.1). On this basis the 35.2AH has been considered a
susceptibility haplotype for sIBM (Price et al., 2004).
A single study identified an association between HLA-DRB1*1301 and HLA-
DRB1*1502, and sIBM (Koffman et al., 1998b), although the observation has not been
independently replicated. A possible protective effect against sIBM has also been
observed with HLA-DRB1*0401 (serologically HLA-DR4), which was found at a lower
than expected frequency in sIBM patients (Koffman et al., 1998b; Badrising et al.,
2004).
87
The aim of this thesis is to identify gene variations that confer susceptibility to sIBM. In
order to do this, three sIBM patient cohorts were collected for study. The first two
cohorts consisted of Caucasian patient samples collected from across Australia and the
United States of America, respectively. The third cohort of Japanese patients was
collected in collaboration with Professors I. Nishino and I. Nonaka of the National
Centre for Neurology and Psychiatry, Tokyo.
Taken together, the three cohorts studied in this chapter are the largest examined for
sIBM. The Japanese cohort is the largest non-Caucasian sIBM-affected cohort
investigated to date and the first investigation performed on the three cohorts was to
assess their HLA associations. This was required to both determine whether the HLA
associations in these cohorts were consistent with previous research, such as with the
8.1AH and 35.2AH in Caucasians, and to build upon existing knowledge of MHC
associations in sIBM. Systematic investigations of genetic susceptibility to sIBM in
other ethnic groups have been limited. Hence the acquisition of a cohort of Japanese
sIBM patients presented an excellent opportunity to study the genetics of sIBM in non-
Caucasians.
88
5.3 Results
5.3.1 DNA samples
Patient DNA was obtained from Australian, United States and Japanese sIBM patients
as described in Chapter 2.1.1 – 2.1.4 to establish the three cohorts. The Australian and
American cohorts consisted of 77 and 28 Caucasian patients with confirmed sIBM from
across Australia and the U.S.A respectively. The Japanese cohort consisted of 31
patients collected from across Japan.
Controls used for the Australian cohort consisted of 190 Caucasian members of the
Busselton community in Western Australia. The cohort was selected at random from
approximately 3000 individuals who attended the 1994 Busselton Health Survey
(http://www.busseltonhealthstudy.com Accessed 24-11-2008). The control population
used for analysis of the American cohort was a cohort of Caucasian blood donors
collected from Bethesda (USA). The population is available through
www.allelefrequencies.net (Accessed 2-2-08) and labelled "USA Caucasian Bethesda".
The Japanese patients were compared against a control population published by Saito et
al. (2000).
5.3.2 HLA typing and analysis
High resolution sequence-based genotyping was used to analyse HLA-B and HLA-DRB1
alleles in the Australian, American and Japanese cohorts, as described in Chapter 2.2.9.
To enable a comparison between sequence-based and serological alleles within the
Australian cohort and its control population, sequence based HLA alleles were
translated to their serological equivalents (Table 5.1) as defined by the WHO
Nomenclature Committee (Marsh et al., 2005).
Ancestral haplotypes for patients and controls were assigned by comparing possible
HLA-B and HLA-DRB1 combinations with the conserved population haplotypes
published by Cattley et al. (2000) for Caucasians and Saito et al. (2000) for the
Japanese.
Patient
AU_1 18 27 18 27 3 3a
3 3 18.2
AU_2 7 8 7 8 2 3 2 3 7.1 8.1
AU_3 8 51 8 5 1 13 1 6
AU_4 40 40 40 40 3 13 3 6 60.3
AU_5 5 8 5 8 3 13 3 6 8.1
AU_6 8 35 8 35 1 3 1 3 8.1 35.2
AU_7 8 40 8 40 3 4 3 4 8.1 60.1
AU_8 8 44 8 44 01 0301 1 3 8.1
AU_9 8 35 8 35 1 3 1 3 8.1 35.2
AU_10 8 44 8 44 3 3 3 3 8.1
AU_11 7 21 7 21 1 3 1 3 7.2
AU_12 8 44 8 44 3 13 3 6 8.1 44.4
AU_13 8 15 8 15 3 6 3 6 8.1 62.3
AU_14 7 51 7 5 3 7 3 7
AU_15 8 NDb
8 ND 3 13 3 6 8.1
AU_16 8 35 8 35 1 3 1 3 8.1 35.2
AU_17 7 38 7 38 03 15 3 2 7.1
AU_18 14 ND 14 ND 1 13 1 6
AU_19 7 8 7 8 3 15 3 2 7.1 8.1
AU_20 8 51 8 5 3 13 3 6 8.1
AU_21 8 15 8 15 0301 1301 3 6 8.1 62.3
AU_22 7 35 7 35 3 13 3 6
AU_23 8 8 8 8 1 3 1 3 8.1
AU_28 8 8 8 8 3 13 3 6 8.1
AU_29 5 44 5 44 1001 1502 10 2 52.1
AU_32 8 15 8 15 0301 1001 3 10 8.1
AU_33 7 8 7 8 03 08 3 8 8.1
AU_34 07 4002 7 40 0107 0401 1 4
AU_35 0801 2705 8 27 0101 0301 1 3 8.1
AU_36 7 8 7 8 0101 0401 1 4 7.2
AU_37 08 4402 8 44 0301 0401 3 4 8.1 44.1
AU_41 1501 3901 15 39 03 16 3 2
AU_42 0801 4403 8 44 0101 0301 1 3 8.1
AU_43 0801 4102 8 41 0301 1303 3 6 8.1
AU_44 1501 1501 15 15 0301 1301 3 6 62.3
AU_45 0801 3801 8 38 0301 0301 3 3 8.1
AU_46 5101 5101 5 5 0301 701 3 7
AU_47 07 5201 7 5 1501 1502 2 2 7.1 52.1
AU_48 0801 4901 8 49 0301 1101 3 11 8.1
AU_49 0801 1501 8 15 0301 1301 3 6 8.1 62.3
AU_50 1501 1801 15 18 0301 1301/02 3 6 18.2 62.3
AU_51 0801 4001 8 40 0301 1301 3 6 8.1
AU_52 8 44 8 44 0301 1001 3 10 8.1
AU_53 07 51 7 5 0301 1301 3 6
AU_54 0801 3501 8 35 0101 0301 1 3 8.1 35.2
AU_55 0801 3901 8 39 0301 1601 3 2 8.1
AU_56 07 15 7 15 0101 0101 1 1 7.2
AU_57 5201 5703 5 57 11 15 11 2 52.1
AU_58 3501 3906 35 39 0103 0801 1 8
AU_59 0801 4001 8 40 0101 0301 1 3 8.1
AU_60 0801 4402 8 44 0301 1501 3 2 8.1
AU_61 0801 15 8 15 0101 0301 1 3 8.1
AU_62 3501 4102 35 41 0101 0101 1 1 35.2
AU_63 3901 4402 39 44 0401 0801/02 4 8 44.1
AU_64 0801 15 8 15 0301 1301 3 6 8.1 62.3
AU_65 1501 4001 15 40 0401 0404 4 4 60.1 62.1
AU_66 1801 4403 18 44 0701 1501 7 2 18.1 44.2
AU_67 0801 0801 8 8 0301 0301 3 3 8.1 8.1
AU_69 0801 4402 8 44 0101 0301 1 3 8.1
AU_70 0801 1501 8 15 0101 0301 1 3 8.1
AU_71 08 3701 8 37 0301 1001 3 10 8.1 37.1
AU_72 0702 5701 7 57 0101 0701 1 7 7.2 57.1
AU_73 2705 5701 27 57 0401 0701 4 7 57.1
AU_74 1801 3501 18 35 0101 0301 1 3 18.2 35.2
AU_75 0702 4402 7 44 0101 0301 1 3 7.2
AU_76 3501 4501 35 45 0301 1301 3 6
AU_77 0801 4901 8 49 0301 0301 3 3 8.1
AU_78 1302 2705 13 27 0401 0701 4 7 13.1
AU_79 0801 1501 8 15 0301 1301/02 3 6 8.1 62.3
AU_80 3906 4901 39 49 0404 1501 4 2
AU_81 1501 4402 15 44 0401 1301 4 6 44.1 62.3
AU_82 0801 4402 8 44 0101 0301 1 3 8.1
AU_83 3501 4501 35 45 0101 1101 1 11 35.2
AU_84 0801 3501 8 35 ND ND
AU_85 3502 5201 35 5 1101/04 1501/02 11 2 35.1 52.1
AU_86 0801 0801 8 8 0301 0301 3 3 8.1 8.1
AU_87 0801 1501 8 15 0301 1301 3 6 8.1 62.3
a - Alleles and haplotypes matching the 8.1AH are marked in red.
b - ND = Not determined/unable to determine.
Table 5.1: HLA allele genotyping of the Australian sIBM patient cohort.a
HLA-B*
HLA-B
Serological
Specificity
HLA-DRB1*
HLA-DR
Serological
Specificity
Predicted Ancestral
Haplotype
ND
90
5.3.3 Australian cohort
5.3.3.1 Analysis of individual alleles
Comparison of individual HLA-B allele frequencies (Table 5.1) showed that HLA-B8
was more frequent in the Australian sIBM patients (OR=2.70, p<0.001). HLA-B44 was
less frequent in patients compared to controls (OR=0.45, p=0.008; Table 5.2). When the
HLA Class II region was examined, HLA-DR3 was associated with susceptibility to
sIBM (OR=4.88, p<0.001), whilst the alleles HLA-DR4 (OR=0.35, p<0.001), HLA-
DR7 (OR=0.22, p<0.001) and HLA-DR11 (OR=0.28, p=0.013) showed a reduced
frequency in sIBM patients (Table 5.3).
5.3.3.2 Analysis of inferred AHs
The alleles HLA-B8 and HLA-DR3 are characteristic of the 8.1AH, which was found at
a higher phenotypic frequency in patients compared to controls (55% vs 17%, OR=5.94,
p<0.001; Table 5.4). The 7.2AH and 62.3AH were also found at a higher frequency in
patients (OR=6.27, p=0.026 and OR=3.32, p=0.023 respectively) despite none of the
individual HLA-B or HLA-DR alleles that characterise these two haplotypes showing a
statistically significantly increased frequency in patients (Table 5.4). Of note is that the
7.2AH is defined by HLA-DRB1*0101, which is also carried by the 35.2 susceptibility
haplotype (Table A1.1). Taken together, the 8.1AH and 7.2AH were found in 61% of
patients.
The HLA-B44 allele, which was reduced in the Australian cohort can be inherited with
either HLA-DR4 or HLA-DR7 as part of either the 44.1AH or 44.2AH, respectively
(Table A1.1). Only the 44.2AH was found at a lower phenotypic frequency in patients
compared to controls (OR=0.11, p=0.010; Table 5.4).
Patients (2n = 154) Controlsa (2n = 380)
% Frequency (n) % Frequency (n)
5 7.1 (11) 6.3 (24) 0.703 1.14 (0.54-2.39)
7 9.1 (14) 9.7 (37) 0.872 0.93 (0.49-1.77)
8 31.8 (49) 14.7 (56) <0.001 2.70 (1.74-4.20)
13 0.6 (1) 1.6 (6) 0.679 0.41 (0.05-3.41)
14 0.6 (1) 3.4 (13) 0.078 0.18 (0.02-1.42.)
15 10.4 (16) 8.7 (33) 0.513 1.22 (0.65-2.29)
18 2.6 (4) 3.4 (13) 0.788 0.75 (0.24-2.35)
21 0.6 (1) 0.5 (2) 1 1.24 (0.11-13.72)
27 2.6 (4) 3.4 (13) 0.788 0.75 (0.24-2.35)
35 7.8 (12) 6.8 (26) 0.712 1.15 (0.57-2.34)
37 0.6 (1) 1.8 (7) 0.449 0.35 (0.04-2.85)
38 1.3 (2) 0.8 (3) 0.629 1.65 (0.27-9.99)
39 3.2 (5) 2.6 (10) 0.773 1.24 (0.42-3.69)
40 4.5 (7) 7.4 (28) 0.334 0.60 (0.26-1.40)
41 1.3 (2) 0.5 (2) 0.328 2.49 (0.35-17.81)
44 9.1 (14) 18.2 (69) 0.008 0.45 (0.25-0.83)
45 1.3 (2) 0.8 (3) 0.629 1.65 (0.27-9.99)
49 1.9 (3) 1.3 (5) 0.696 1.49 (0.35-6.31)
55 0.0 (0) 2.6 (10) 0.070 N/A
57 1.9 (3) 4.2 (16) 0.302 0.45 (0.13-1.57)
58 0.0 (0) 0.8 (3) 0.561 N/A
71 0.0 (0) 0.3 (1) 1 N/A
Other 1.9 (2) 0.0 (0) - -
Patients (2n = 152) Controlsa (2n = 380)
% Frequency (n) % Frequency (n)
1 17.8 (27) 11.3 (43) 0.064 1.69 (1.00-2.86)
2 8.6 (13) 13.2 (50) 0.181 0.62 (0.33-1.17)
3 40.8 (62) 12.4 (47) <0.001 4.88 (3.13-7.62)
4 7.2 (11) 18.4 (70) <0.001 0.35 (0.18-0.67)
6 14.5 (22) 12.4 (47) 0.568 1.20 (0.70-2.07)
7 3.9 (6) 15.8 (60) <0.001 0.22 (0.09-0.52)
8 2.0 (3) 2.4 (9) 1 0.83 (0.22-3.11)
9 0.0 (0) 2.4 (9) 0.066 N/A
10 2.6 (4) 0.5 (2) 0.059 5.11 (0.93-28.19)
11 2.6 (4) 8.7 (33) 0.013 0.28 (0.10-0.82)
12 0.0 (0) 2.6 (10) 0.070 N/A
Table 5.2: HLA-B allele frequencies for sIBM patients from the Australian cohort and a
healthy population.
a- The control population was a cohort of 190 Caucasian members of the Busselton
community in Western Australia (http://www.busseltonhealthstudy.com/).
Table 5.3: HLA-DR allele frequencies for sIBM patients from the Australian cohort and a
healthy population.
a- The control population was is a cohort of 190 Caucasian members of the Busselton
community in Western Australia (http://www.busseltonhealthstudy.com/).
Allele p-value OR (95%CI)
OR (95%CI)p-valueAllele
Patientsa (n = 76) Controls
ab (n = 180)
% Frequency (n) % Frequency (n)
7.1 5.3 (4) 10.0 (18) 0.328 0.50 (0.16-1.53)
7.2 6.6 (5) 1.1 (2) 0.026 6.27 (1.19-33.05)
8.1 55.3 (42) 17.2 (31) <0.001 5.94 (3.27-10.77)
13.1 1.3 (1) 1.7 (3) 1 0.79 (0.08-7.69)
18.1 1.3 (1) 1.7 (3) 1 0.79 (0.08-7.69)
18.2 3.9 (3) 1.7 (3) 0.36586837 2.42 (0.48-12.29)
35.1 0.0 (0) 0.6 (1) 1 N/A
35.2 9.2 (7) 7.2 (13) 0.61387986 1.30 (0.50-3.41)
37.1 1.3 (1) 1.1 (2) 1 1.19 (0.11-13.29)
38.1 0.0 (0) 0.6 (1) 1 N/A
44.1 3.9 (3) 10.6 (19) 0.093 0.35 (0.10-1.21)
44.2 1.3 (1) 10.6 (19) 0.010 0.11 (0.01-0.86)
44.4 1.3 (1) 0.6 (1) 0.506 2.39 (0.15-38.66)
50.1 0.0 (0) 1.1 (2) 1 N/A
51.1 0.0 (0) 2.2 (4) 0.322 N/A
52.1 5.3 (4) 1.7 (3) 0.201 3.28 (0.72-15.01)
55.1 0.0 (0) 0.6 (1) 1 N/A
57.1 2.6 (2) 4.4 (8) 0.728 0.58 (0.12-2.80)
58.1 0.0 (0) 1.7 (3) 0.557 N/A
60.1 2.6 (2) 4.4 (8) 0.728 0.58 (0.12-2.80)
60.3 1.3 (1) 2.2 (4) 1 0.59 (0.06-5.34)
62.1 1.3 (1) 3.3 (6) 0.678 0.39 (0.05-3.27)
62.3 11.8 (9) 3.9 (7) 0.023 3.32 (1.19-9.27)
65.1 0.0 (0) 2.2 (4) 0.322 N/A
OR (95%CI)
a - Individuals with HLA-B and HLA-DR allele combinations that could result in several
alternative haplotypes were excluded for the purpose of these calculations.
Table 5.4: AH phenotype frequencies among patients and controls from the Australian
cohort.
b - The control population was a cohort of 190 Caucasian members of the Busselton
community in Western Australia (http://www.busseltonhealthstudy.com/).
Allele p-value
93
5.3.4 American cohort
5.3.4.1 Analysis of individual alleles
Comparison of the HLA Class I alleles (Table 5.5) showed that HLA-B*0801 (OR=2.63,
p=0.010) and HLA-B*3906 (p=0.031) occurred at a higher allelic frequency in the
American cohort compared to controls (Table 5.6). Of the HLA-Class II alleles, HLA-
DRB1*0101 and HLA–DRB1*0301 were both more frequent in the patient cohort
(OR=2.67, p=0.018 and OR=4.18, p<0.001 respectively; Table 5.7). Only HLA-
DRB1*0701 showed a reduced frequency in the American patients (p<0.001; Table 5.7)
5.3.4.2 Analysis of inferred AHs
Carriage of the 8.1AH in patients was assessed by the presence of HLA-B*0801 and
DRB1*0301. In total 46% (13/28) carried the 8.1AH, of whom one was homozygous for
the 8.1AH. All patients with HLA-B*0801 also carried a HLA-DRB1*0301 allele. Four
patients carried HLA-DRB1*0301 without a corresponding HLA-B*0801 allele. Two of
these patients (AM_7 and AM_20) also carried HLA-B*1801 and hence the 18.2AH.
The other patients (AM_21 and AM_27) were homozygous for HLA-DRB1*0301 but
carried only one copy of the corresponding HLA-B*0801 allele (Table 5.5).
Alleles of the 35.2AH, defined by HLA-B*3501 and HLA-DRB1*0101 were identified
in 14% (4/28) of patients from the American cohort. The cohort included six additional
HLA-DRB1*0101 alleles that could not be assigned to any known conserved haplotype,
and a further two HLA-DRB1*0101 alleles carried with HLA-B*0702, suggesting
presence of the 7.2AH (Table 5.5).
Several of the statistically significant alleles in the American cohort, specifically HLA-
B*0801, HLA-DRB1*0301, and HLA-DRB1*0701, were also increased in the Australian
cohort as the serological specificities HLA-B8, HLA-DR3, and HLA-DR7. Only HLA-
B*3901 and HLA-DRB1*0101 in the American cohort, and HLA-B44, HLA-DR4 and
HLA-DR11 in the Australian cohort did not have a statistically significant counterpart
in the other Caucasian cohort.
Patient
AM_1 0702 4001 1001 1602
AM_2 0702 5601 NDa
ND
AM_3 0702 4402 0101 1301 7.2
AM_4 1501 1510 0101 1001
AM_5 2702 3502 1101 1101
AM_6 0801 4901 0301 1001 8.1
AM_7 1801 3501 0101 0301 35.2 18.2
AM_8 3502 4403 0101 1104
AM_9 3501 3901 0101 1101 35.2
AM_10 4402 5101 0101 1602
AM_11 0702 0801 0101 0301 8.1 7.2
AM_12 0801 4001 0301 0801 8.1
AM_13 1801 3501 0101 1501 18.1 35.2
AM_14 0801 1501 0101 0301 8.1
AM_15 3501 3906 0101 1301 35.2
AM_16 4402 4901 0101 1301
AM_17 4402 5101 0801 1101
AM_18 0801 3906 0301 0801 8.1
AM_19 1510 4201 0302 1503 42.1
AM_20 1801 4001 0301 1104 18.2
AM_21 0801 5001 0301 0301 8.1
AM_22 0801 2705 0101 0301 8.1
AM_23 0801 1501 0301 1301 8.1 62.3
AM_24 0801 5201 0301 1501 8.1
AM_25 0801 4001 0301 0801 8.1
AM_26 0702 0801 0301 1501 8.1 7.1
AM_27 0801 5101 0301 0301 8.1
AM_28 0801 0801 0301 0301 8.1 8.1
a - ND = Not determined/unable to determine.
b - Alleles and haplotypes matching the 8.1AH are marked in red.
Table 5.5: HLA allele genotyping for the American sIBM patient
cohort.
HLA-B* HLA-DRB1*Predicted Ancestral
Haplotype
Patients (2n = 56) Controlsa (2n = 258)
% Frequency (n) % Frequency (n)
0702 8.9 (5) 15.5 (40) 0.292 0.53 (0.20-1.42)
0704 0.0 (0) 0.4 (1) 1 N/A
0705 0.0 (0) 0.4 (1) 1 N/A
0801 25.0 (14) 11.2 (29) 0.010 2.63 (1.28-5.40)
1302 0.0 (0) 2.7 (7) 0.360 N/A
1402 0.0 (0) 4.3 (11) 0.224 N/A
1501 5.4 (3) 5.4 (14) 1 0.99 (0.27-3.55)
1510 3.6 (2) 0.4 (1) 0.083 9.52 (0.85-106.86)
1518 0.0 (0) 0.4 (1) 1 N/A
1801 5.4 (3) 2.3 (6) 0.204 2.38 (0.58-9.81)
2702 1.8 (1) 0.4 (1) 0.325 4.67 (0.29-75.85)
2705 1.8 (1) 4.3 (11) 0.700 0.41 (0.05-3.23)
3501 7.1 (4) 7.0 (18) 1 1.03 (0.33-3.16)
3502 3.6 (2) 1.2 (3) 0.218 3.15 (0.51-19.30)
3503 0.0 (0) 2.7 (7) 0.360 N/A
3508 0.0 (0) 0.4 (1) 1 N/A
3701 0.0 (0) 1.2 (3) 1 N/A
3901 1.8 (1) 1.9 (5) 1 0.92 (0.11-8.03)
3906 3.6 (2) 0.0 (0) 0.031 N/A
4001 7.1 (4) 6.6 (17) 0.775 1.09 (0.35-3.37)
4002 0.0 (0) 1.2 (3) 1 N/A
4101 0.0 (0) 0.4 (1) 1 N/A
4102 0.0 (0) 0.4 (1) 1 N/A
4201 1.8 (1) 0.0 (0) 0.178 N/A
4402 7.1 (4) 8.1 (21) 1 0.87 (0.29-2.64)
4403 1.8 (1) 6.6 (17) 0.215 0.26 (0.03-1.98)
4901 3.6 (2) 1.9 (5) 0.612 1.87 (0.35-9.92)
5001 1.8 (1) 0.0 (0) 0.178 N/A
5002 0.0 (0) 0.4 (1) 1 N/A
5101 5.4 (3) 2.7 (7) 0.392 2.03 (0.51-8.10)
5201 1.8 (1) 0.0 (0) 0.178 N/A
5301 0.0 (0) 0.4 (1) 1 N/A
5501 0.0 (0) 1.6 (4) 1 N/A
5601 1.8 (1) 0.0 (0) 0.178 N/A
5701 0.0 (0) 3.1 (8) 0.359 N/A
5703 0.0 (0) 0.4 (1) 1 N/A
5802 0.0 (0) 0.4 (1) 1 N/A
Table 5.6: HLA-B allele frequencies for sIBM patients from the American cohort and a healthy
population.
a- The control population was a cohort of Caucasian blood donors collected at Bethesda (USA).
The population is available through www.allelefrequencies.net and labelled "USA Caucasian
Bethesda".
Allele p-value OR (95%CI)
Patients (2n = 54) Controlsa (2n = 290)
% Frequency (n) % Frequency (n)
0101 22.2 (12) 9.6 (28) 0.018 2.67 (1.26-5.66)
0102 0 (0) 2.1 (6) 0.595 N/A
0103 0 (0) 0.7 (2) 1 N/A
0104 0 (0) 0.3 (1) 1 N/A
0301 33.3 (18) 10.7 (31) <0.001 4.18 (2.12-8.22)
0302 1.9 (1) 0.3 (1) 0.290 5.45 (0.34-88.53)
0401 0 (0) 7.2 (21) 0.056 N/A
0402 0 (0) 0.3 (1) 1 N/A
0403 0 (0) 1.7 (5) 1 N/A
0404 0 (0) 4.5 (13) 0.234 N/A
0406 0 (0) 1.4 (4) 1 N/A
0407 0 (0) 0.3 (1) 1 N/A
0408 0 (0) 0.3 (1) 1 N/A
0701 0 (0) 14.5 (42) <0.001 N/A
0801 7.4 (4) 2.1 (6) 0.055 3.79 (1.03-13.90)
0802 0 (0) 0.7 (2) 1 N/A
0804 0 (0) 1.2 (3) 1 N/A
0901 0 (0) 1.7 (5) 1 N/A
1001 5.6 (3) 1.4 (4) 0.081 4.21 (0.91-19.35)
1101 7.4 (4) 5.2 (15) 0.516 1.47 (0.47-4.60)
1102 0 (0) 0.7 (2) 1 N/A
1103 0 (0) 1.4 (4) 1 N/A
1104 3.7 (2) 2.8 (8) 0.660 1.36 (0.28-6.57)
1201 0 (0) 0.7 (2) 1 N/A
1202 0 (0) 0.3 (1) 1 N/A
1301 7.4 (4) 5.5 (16) 0.533 1.37 (0.44-4.27)
1302 0 (0) 4.8 (14) 0.139 N/A
1303 0 (0) 0.3 (1) 1 N/A
1401 0 (0) 4.1 (12) 0.226 N/A
1402 0 (0) 0.3 (1) 1 N/A
1501 5.6 (3) 8.6 (25) 0.593 0.62 (0.18-2.14)
1502 0 (0) 0.7 (2) 1 N/A
1503 1.9 (1) 0.0 (0) 0.157 N/A
1601 0 (0) 2.4 (7) 0.602 N/A
1602 3.7 (2) 0.3 (1) 0.065 11.12 (0.99-124.82)
Table 5.7: HLA-DRB1 allele frequencies for sIBM patients from the American cohort and a
healthy population.
a- The control population was a cohort of Caucasian blood donors collected at Bethesda (USA).
The population is available through www.allelefrequencies.net and labelled "USA Caucasian
Bethesda".
Allele p-value OR (95%CI)
97
5.3.5 Japanese Cohort
5.3.5.1 Analysis of individual alleles
Comparison of HLA-B and -DRB1 alleles in the Japanese sIBM patients (Table 5.8)
revealed an association with one HLA-B allele and two HLA-DRB1 alleles. HLA-
B*5201 was the only HLA-Class I allele that showed a statistically significantly
increased frequency in patients (OR=5.67, p<0.001; Table 5.9). HLA-B*4402 also
showed an increased prevalence in sIBM patients (OR=8.2), although the p-value was
slightly above 0.05, indicating insufficient statistical significance (Table 5.9).
Of the HLA Class II alleles, HLA-DRB1*1502 was found with a higher allele frequency
in patients (OR=5.3, p<0.001). In contrast, HLA-DRB1*0901 was not found at all in
patients (p=0.001), despite having the highest allele frequency amongst HLA-DRB1
alleles in the normal Japanese population, at 12.4% (Table 5.10).
5.3.5.2 Analysis of inferred AHs
Four and three individuals were identified as homozygous for HLA-B*5201 and HLA-
DRB1*1502, respectively. All three individuals homozygous for HLA-DRB1*1502 were
also homozygous for HLA-B*5201. HLA-DRB1*1502 is normally only found with
HLA-B*5201 in the Japanese population (Saito et al., 2000), which corresponds to the
previously identified 52.1 AH (Cattley et al., 2000). There was a statistically significant
increase in the haplotype frequency of the 52.1AH in patients compared to the Japanese
control population (OR=6.5, p<0.001; Table 5.11). The 52.1AH was present in 65%
(20/31) of the Japanese sIBM patients. Two other haplotypes, defined by HLA-B*3501,
HLA-DRB1*1501 and HLA-B*5101, HLA-DRB1*0802 were also found at a statistically
increased frequency in sIBM patients (OR=6.2, p=0.026 and OR=9.4, p=0.012).
However in both cases, the haplotype frequencies were low at 4.8% (Table 5.11).
Table 5.8: HLA allele genotyping for the Japanese sIBM patients.
Name
JAP_1 3501 5401 0803 1501 0201 1901 B*3501 / DRB1*1501 B*5401 / DRB1*0803
JAP_2 3501 5201b
0410 1502 0201 0901 B*5201 / DRB1*1502
JAP_3 1301 4002 0101 1202 0201 0402 B*1301 / DRB1*1202
JAP_4 5201 5201 1502 1602 0501 0901 B*5201 / DRB1*1502
JAP_5 1501 5201 1501 1502 0501 0901 B*1501 / DRB1*1501 B*5201 / DRB1*1502
JAP_6 2711 5201 0405 1502 0501 0901 B*5201 / DRB1*1502
JAP_7 5101 5201 0802 1502 0501 0901 B*5201 / DRB1*1502 B*5101 / DRB1*0802
JAP_8 3501 4402 0405 1301 0201 0501 B*3501 / DRB1*0405
JAP_9 0702 5201 0101 1502 0501 0901 B*0702 / DRB1*0101 B*5201 / DRB1*1502
JAP_10 5201 5401 0405 1502 0501 0901 B*5201 / DRB1*1502 B*5401 / DRB1*0405
JAP_11 5201 6701 0405 1502 0501 0901 B*5201 / DRB1*1502
JAP_12 5201 5601 1101 1502 0202 0901 B*5201 / DRB1*1502 / DPB1*0901
JAP_13 5101 5201 1202 1502 0501 0901 B*5201 / DRB1*1502
JAP_14 5201 5502 0101 1502 NDc
ND B*5201 / DRB1*1502
JAP_15 4001 5101 0101 0802 0402 0402 B*5101 / DRB1*0802
JAP_16 3501 5201 1403 1501 0501 0901 B*3501 / DRB1*1501
JAP_17 5201 5201 1502 1502 0201 0501 B*5201 / DRB1*1502 / DPB1*0201 B*5201 / DRB1*1502 / DPB1*0501
JAP_18 4402 5201 1301 1502 0501 0901 B*5201 / DRB1*1502
JAP_19 1501 5201 1406 1502 0501 0901 B*1501 / DRB1*1406 B*5201 / DRB1*1502
JAP_20 0702 4403 0101 1302 0401 0402 B*0702 / DRB1*0101 / DPB1*0402 B*4403 / DRB1*1302
JAP_21 4002 4601 0410 0803 0201 0202 B*4601 / DRB1*0803
JAP_22 5201 5201 1502 1502 0901 0901 B*5201 / DRB1*1502 / DPB1*0901 B*5201 / DRB1*1502 / DPB1*0901
JAP_23 4403 5201 1302 1502 0201 0901 B*4403 / DRB1*1302 / DPB1*0201 B*5201 / DRB1*1502 / DPB1*0901
JAP_24 4403 5101 0405 1302 0402 0501 B*4403 / DRB1*1302
JAP_25 5101 5201 0802 1502 0501 0901 B*5101 / DRB1*0802 B*5201 / DRB1*1502
JAP_26 1518 5801 0802 1302 0301 0501
JAP_27 3901 4801 0802 0803 0501 0501
JAP_28 3501 5201 1501 1502 0501 0901 B*3501 / DRB1*1501 B*5201 / DRB1*1502
JAP_29 4403 5201 1302 1502 0301 0901 B*4403 / DRB1*1302 B*5201 / DRB1*1502 / DPB1*0901
JAP_30 3501 3901 0405 0410 0301 0501 B*3501 / DRB1*0405
JAP_31 5201 5201 1502 1502 0901 0901 B*5201 / DRB1*1502 / DPB1*0901 B*5201 / DRB1*1502 / DPB1*0901
a - HLA-DPB1 alleles were assigned to conserved haplotypes where possible.
b -Alleles and haplotypes matching the 52.1AH are marked in red.
c - ND = Not determined/unable to determine.
HLA-B* HLA-DRB1* HLA-DPB1* HLA Haplotypea
Allele Patients (2n = 62) Controls (a) (2n = 742) p -value OR (95%CI)
% Frequency (n) % Frequency (n)
0702 3.2 (2) 6.5 (48) 0.419 0.48 (0.11-2.03)
1301 1.6 (1) 1.5 (11) 1 1.09 (0.14-8.57)
1302 0 (0) 0.3 (2) 1 N/A
1501 3.2 (2) 8.7 (65) 0.155 0.35 (0.08-1.45)
1502 0 (0) 0.1 (1) 1 N/A
1507 0 (0) 0.7 (5) 1 N/A
1511 0 (0) 0.4 (3) 1 N/A
1518 1.6 (1) 1.5 (11) 1 1.09 (0.14-8.57)
1527 0 (0) 0.1 (1) 1 N/A
2704 0 (0) 0.3 (2) 1 N/A
2705 0 (0) 0.1 (1) 1 N/A
3501 9.7 (6) 7.6 (56) 0.465 1.24 (0.51-3.00)
3701 0 (0) 1.3 (10) 1 N/A
3802 0 (0) 0.1 (1) 1 N/A
3901 3.2 (2) 4.4 (33) 0.123 0.72 (0.17-3.06)
3902 0 (0) 0.5 (4) 1 N/A
3904 0 (0) 0.1 (1) 1 N/A
4001 1.6 (1) 4.2 (31) 0.504 0.38 (0.05-2.80)
4002 3.2 (2) 8.6 (64) 0.223 0.35 (0.08-1.48)
4003 0 (0) 0.3 (2) 1 N/A
4006 0 (0) 3.9 (29) 0.15838656 N/A
4007 0 (0) 0.1 (1) 1 N/A
4402 3.2 (2) 0.4 (3) 0.050 8.21 (1.35-50.10)
4403 6.5 (4) 8.7 (65) 0.812 0.72 (0.25-2.04)
4601 1.6 (1) 3.6 (27) 0.716 0.43 (0.06-3.25)
4801 1.6 (1) 3 (22) 1 0.54 (0.07-4.05)
5101 8.1 (5) 7.7 (57) 0.807 1.05 (0.41-2.73)
5102 0 (0) 0.1 (1) 1 N/A
5103 0 (0) 0.1 (1) 1 N/A
5201 40.3 (25) 10.7 (79) < 0.001 5.67 (3.24-9.91)
5401 3.2 (2) 7.7 (57) 0.307 0.40 (0.09-1.68)
5502 1.6 (1) 1.9 (14) 1 0.85 (0.11-6.59)
5504 0 (0) 0.3 (2) 1 N/A
5601 1.6 (1) 0.5 (4) 0.331 3.02 (0.33-27.48)
5603 0 (0) 0.1 (1) 1 N/A
5801 1.6 (1) 0.4 (3) 0.275 4.04 (0.41-39.41)
5901 0 (0) 1.8 (13) 0.6141884 N/A
6701 1.6 (1) 1.1 (8) 0.516 1.50 (0.18-12.22)
2711 1.6 (1) 0 (0) 0.077 N/A
a - The control population originated from Saito et al (2000).
Table 5.9: HLA-B allele frequencies for Japanese sIBM patients and a healthy population.
Allele Patients (2n = 62) Controls (a) (2n = 742) p -value OR (95%CI)
% Frequency (n) % Frequency (n)
0101 8.1 (5) 6.5 (48) 0.593 1.27 (0.49-3.31)
0401 0 (0) 0.7 (5) 1 N/A
0403 0 (0) 0.4 (3) 1 N/A
0404 0 (0) 0.1 (1) 1 N/A
0405 9.7 (6) 11.5 (85) 0.835 0.828 (0.35-1.98)
0406 0 (0) 3.5 (26) 0.253 N/A
0407 0 (0) 0.9 (7) 1 N/A
0410 4.8 (3) 1.8 (13) 0.119 2.851 (0.79-10.29)
0701 0 (0) 0.3 (2) 1 N/A
0802 8.1 (5) 4 (30) 0.181 2.08 (0.78-5.57)
0803 4.8 (3) 8.1 (60) 0.467 0.58 (0.18-1.90)
0901 0 (0) 12.4 (92) <0.001 N/A
1001 0 (0) 0.9 (7) 1 N/A
1101 1.6 (1) 3.4 (25) 0.714 0.47 (0.06-3.53)
1201 0 (0) 3.8 (28) 0.159 N/A
1202 3.2 (2) 1.5 (11) 0.265 2.22 (0.48-10.22)
1301 1.6 (1) 0.7 (5) 0.383 2.42 (0.28-21.01)
1302 9.7 (6) 7.7 (57) 0.620 1.29 (0.53-3.12)
1401 0 (0) 4.2 (31) 0.162 N/A
1403 1.6 (1) 1.5 (11) 1 1.09 (0.14-8.58)
1405 0 (0) 1.1 (8) 1 N/A
1406 1.6 (1) 1.8 (13) 1 0.92 (0.12-7.15)
1407 0 (0) 0.3 (2) 1 N/A
1412 0 (0) 0.1 (1) 1 N/A
1501 6.5 (4) 8.5 (63) 0.81 0.74 (0.26-2.11)
1502 37.1 (23) 10 (74) <0.001 5.32 (3.02-9.40)
1602 1.6 (1) 0.9 (7) 0.475 1.72 (0.21-14.22)
a - The control population originated from Saito et al (2000).
Table 5.10: HLA-DRB1 allele frequencies for Japanese sIBM patients and a healthy population.
Patients (2n = 62) Controlsb (2n = 742)
% Frequency (n) % Frequency (n)
B *0702, DRB1 *0101 (7.2AH) 3.2 (2) 4 (30) 1 0.79 (0.18-3.39)
B *1301, DRB1 *1202 1.6 (1) 0.5 (4) 0.331 3.03 (0.33-27.48)
B *1501 DRB1 *0406 0 (0) 1.7 (13) 0.614 N/A
B *1501, DRB1 *1406 1.6 (1) 0.8 (6) 0.431 2.01 (0.24-16.97)
B *1501, DRB1 *1501 1.6 (1) 0.5 (4) 0.331 3.02 (0.33-27.48)
B *1518, DRB1 *0401 0 (0) 0.5 (4) 1 N/A
B *3501, DRB1 *0403 0 (0) 0.8 (6) 1 N/A
B *3501, DRB1 *0405 3.2 (2) 1 (7) 0.148 3.50 (0.71-17.22)
B *3501, DRB1 *0802 0 (0) 0.7 (5) 1 N/A
B *3501, DRB1 *1101 0 (0) 0.8 (6) 1 N/A
B *3501, DRB1 *1501 4.8 (3) 0.8 (6) 0.026 6.24 (1.52-25.57)
B *3701, DRB1 *1001 0 (0) 0.5 (4) 1 N/A
B *3901, DRB1 *0802 0 (0) 0.5 (4) 1 N/A
B *3901, DRB1 *0803 0 (0) 0.8 (6) 1 N/A
B *3901, DRB1 *1501 0 (0) 0.5 (4) 1 N/A
B *4001, DRB1 *0405 0 (0) 0.9 (7) 1 N/A
B *4001, DRB1 *0803 0 (0) 0.9 (7) 1 N/A
B *4001, DRB1 *1401 0 (0) 0.6 (4) 1 N/A
B *4002, DRB1 *0405 0 (0) 0.6 (4) 1 N/A
B *4002, DRB1 *0802 0 (0) 0.5 (4) 1 N/A
B *4002, DRB1 *0901 0 (0) 1.2 (9) 1 N/A
B *4002, DRB1 *1101 0 (0) 0.5 (4) 1 N/A
B *4002, DRB1 *1201 0 (0) 0.5 (4) 1 N/A
B *4002, DRB1 *1401 0 (0) 0.6 (4) 1 N/A
B *4002, DRB1 *1501 0 (0) 0.7 (5) 1 N/A
B *4006, DRB1 *0901 0 (0) 1.0 (7) 1 N/A
B *4403, DRB1 *0901 0 (0) 0.5 (4) 1 N/A
B *4403, DRB1 *0803 0 (0) 0.5 (4) 1 N/A
B *4403, DRB1 *1302 (44.4AH) 6.5 (4) 4.8 (36) 0.540 1.35 (0.47-3.93)
B *4601, DRB1 *0803 1.6 (1) 0.9 (7) 0.475 1.72 (0.21-14.22)
B *4801, DRB1 *0407 0 (0) 0.5 (4) 1 N/A
B*5101, DRB1 *0403 0 (0) 0.6 (4) 1 N/A
B *5101, DRB1 *0802 4.8 (3) 0.6 (4) 0.012 9.38 (2.05-42.90)
B *5101, DRB1 *0901 0 (0) 1.1 (8) 1 N/A
B *5101, DRB1 *1401 0 (0) 0.5 (4) 1 N/A
B *5201, DRB1 *0901 0 (0) 0.6 (4) 1 N/A
B *5201, DRB1 *1502 (52.1AH) 37.1 (23) 8.4 (62) <0.001 6.45 (3.63-11.52)
B *5401, DRB1 *0405 1.6 (1) 3.4 (25) 0.713 0.47 (0.06-3.53)
B *5401, DRB1 *0803 1.6 (1) 0.5 (4) 0.331 3.03 (0.33-27.48)
B *5901, DRB1 *0405 0 (0) 1.1 (8) 1 N/A
B *6701, DRB1 *1602 0 (0) 0.5 (4) 1 N/A
a - AHs are assigned to each haplotype, where possible, according to Table A1.1
b - The control population originated from Saito et al (2000).
Table 5.11: HLA-B / HLA-DRB1 haplotype frequencies for Japanese sIBM patients and a healthy population.
Haplotype a p -value OR (95%CI)
Patients (2n = 60) Controls (a) (2n = 742)
% Frequency (n) % Frequency (n)
0201 11.7 (7) 25.2 (187) 0.018 0.392 (0.18-0.88)
0202 3.3 (2) 3.4 (25) 1 0.989 (0.23-4.28)
0301 5 (3) 4.3 (32) 0.741 1.168 (0.35-3.93)
0401 1.7 (1) 5.8 (43) 0.243 0.276 (0.04-2.04)
0402 8.3 (5) 12.3 (91) 0.533 0.650 (0.25-1.67)
0501 33.3 (20) 3.6 (27) <0.001 13.241 (6.84-25.62)
0601 0 (0) 0.1 (1) 1 N/A
0901 35 (21) 9.7 (72) <0.001 5.011 (2.80-8.98)
1301 0 (0) 1.3 (10) 1 N/A
1401 0 (0) 1.5 (11) 1 N/A
1901 1.7 (1) 0.3 (2) 0.208 6.271 (0.56-70.18)
4101 0 (0) 0.3 (2) 1 N/A
a - The control population originated from Saito et al (2000).
Table 5.12: HLA-DPB1 allele frequencies for Japanese sIBM patients and a healthy population.
Allele p -value OR (95%CI)
102
The 52.1AH in the Japanese is divided into three sub-haplotypes defined by the alleles
HLA-DPB1*0201, HLA-DPB1*0501 and HLA-DPB1*0901 (Saito et al., 2000). In
order to determine whether the association with sIBM originated from one of these sub-
haplotypes, HLA-DPB1 alleles were compared between the Japanese patients and
controls. HLA-DPB1*0201, HLA-DPB1*0501 and HLA-DPB1*0901, all showed a
statistically significant difference between patients and controls (Table 5.12). While
HLA-DPB1*0501 and HLA-DPB1*0901 were increased in patients compared to
controls (OR=13.2, p<0.001 and OR=5.0, p<0.001 respectively), HLA-DPB1*0201 was
reduced in frequency in patients (OR=0.4, p=0.018; Table 5.12).
The frequency of each 52.1 sub-haplotype in patients could not be determined, as most
patients were heterozygous for two of the three HLA-DPB1 alleles associated with the
HLA-B*5201, HLA-DRB1*1502 sub-haplotypes. Of the three patients homozygous for
HLA-B*5201, HLA-DRB1*1502, two were homozygous for HLA-DPB1*0901, and the
last was heterozygous (HLA-DPB1*0501/0201).
Neither the 52.1AH, its defining alleles, nor HLA-DRB1*0901 were found at an
appreciable frequency in the Caucasian cohorts. Furthermore, the 7.2AH, defined by
HLA-B*0702 and HLA-DRB1*0101 and identified as a possible susceptibility haplotype
in the Australian cohort, was not statistically significantly increased in the Japanese
patients (Table 5.11).
104
5.4 Discussion
5.4.1 The 8.1AH
HLA typing of both Caucasian cohorts confirmed the genetic association between sIBM
and carriage of alleles matching the 8.1AH. This is in agreement with the results from
every other study on sIBM in Caucasian patients thus far (Love et al., 1991; Garlepp et
al., 1994; Garlepp et al., 1998; Koffman et al., 1998b; Lampe et al., 2003; Badrising et
al., 2004; Price et al., 2004; O'Hanlon et al., 2005). Although both the 8.1AH and the
18.2AH carry HLA-DRB1*0301, neither the 18.2AH nor its defining allele, HLA-
B*1801, showed an association with sIBM. This is consistent with a previous study that
showed HLA-DRB1*0301 was associated with sIBM in conjunction with alleles
defining the 8.1AH, but not the 18.2AH (Price et al., 2004). Both the 8.1AH and the
18.2AH are almost identical within the MHC Class II region defined by HLA-DRB1,
HLA-DQA1 and HLA-DQB1, and diverge telomeric of HLA-DRB1 and before HLA-
DRB3 (Traherne et al., 2006b). As suggested previously, it is likely that the centromeric
limit of the 8.1AH-derived sIBM susceptibility region lies between HLA-DRB1 and
HLA-DRB3 (Price et al., 2004).
5.4.2 Protective alleles within the Caucasian cohorts
Alleles and haplotypes with a reduced frequency in the patient cohorts are likely to
confer a protective effect against sIBM. Possible protective alleles identified in the work
described in this chapter are HLA-B44, HLA-DR4, HLA-DR7, HLA-DR11 and the
44.2AH in the Australian cohort, HLA-DRB1*0701 in the American cohort, and HLA-
DRB1*0901 and HLA-DPB1*0201 in the Japanese cohort.
Within the Australian cohort, the protective alleles serologically identified as HLA-DR4
and HLA-DR7 can be subdivided into sequence-based alleles found to have the same
effect in the American cohort, specifically HLA-DRB1*0401 and HLA-DRB1*0701. In
the Australian cohort, the only sequence-based allele present in the Australian cohort
that could be serologically identified as HLA-DR7 was HLA-DRB1*0701 (Table 5.1).
Hence it is likely that AHs containing the HLA-DRB1*0701 allele confer a protective
effect against sIBM in both Caucasian cohorts. HLA-DR7 has also been reported as
associated with protection for sIBM in one other study (Badrising et al., 2004).
105
The serological allele HLA-DR4 subdivides into many high resolution, sequence-based
alleles, including HLA-DRB1*0401 and HLA-DRB1*0404, both of which are found in
the Australian cohort. Past studies have reported that HLA-DR4 and HLA-DRB1*0401
are protective alleles (Koffman et al., 1998b; Badrising et al., 2004). While this does not
provide conclusive evidence either way, the observation and the results in this thesis
both suggest that HLA-DRB1*0401, rather than HLA-DRB1*0404, confers a protective
effect against sIBM in Caucasians. Neither HLA-DRB1*0401 nor HLA-DRB1*0404 was
reduced in the American cohort, although HLA-DRB1*0401 was close to statistical
significance (p=0.056; Table 5.7). While no conclusion could be made from this result,
it is possible that HLA-DRB1*0401 did not attain statistical significance due to the
small size of the American cohort (28 individuals). A larger cohort of American sIBM
patients would thus be likely to confirm any possible protective effect conferred by
HLA-DRB1*0401 in this population.
Both the 44.2AH and its component alleles, HLA-B44 and HLA-DRB1*0701, showed
a reduced incidence in Caucasian sIBM patients, providing strong evidence for the
44.2AH conferring a protective effect against sIBM. The source of this effect is likely to
lie nearer HLA-DRB1 than HLA-B, given that carriage of HLA-DRB1*0701, but not
HLA-B*4403, was decreased in both Caucasian cohorts.
5.4.3 Assignment of AHs
The individual AHs identified in the Caucasian and Japanese patients were assigned
based on allele pairings predicted from previously published conserved AHs (Cattley et
al., 2000; Saito et al., 2000). However, it is possible that two given alleles present in an
individual, despite matching a known AH (eg. HLA-B*0801, HLA-DRB1*0301
corresponding to the 8.1AH), may not have actually been inherited together on the same
chromosome. These wrongly assigned AHs could confound AH-disease associations,
resulting in a type I (false positive) or type II (false negative) statistical error. Such
errors can be minimised by confirming whether a disease association with a given AH is
supported by previously published research.
5.4.4 The 7.2AH and 35.2AH
An association between sIBM and the 35.2AH was first proposed by Price et al. (2004)
on the basis of the high frequency of the allele BTL-II(E6)*2 in patients. This allele was
106
specific to AHs carrying the HLA-DRB1*0101, in particular the 35.2AH and 7.2AH.
(Price et al., 2004). As the 7.2AH was considered an Asian AH, BTL-II(E6)*2 was
assumed to indicate the presence of the 35.2AH in Caucasians (Price et al., 2004). This
was supported by the results of O‘Hanlon et al. (2005) which found that alleles
matching the 35.2AH were increased in Caucasian sIBM patients when compared with
polymyositis (PM) patients.
Contrary to these published studies (Price et al., 2004; O'Hanlon et al., 2005), the
35.2AH and alleles matching the 35.2AH (HLA-B35, HLA-DR1) were not observed at
an increased frequency in the Australian or American cohorts studied here. Instead,
sIBM in the Australian and American cohorts was associated with alleles matching the
7.2AH (HLA-B*0702, HLA-DRB1*0101).
The 7.2AH and the 35.2AH are very similar around the MHC Class II region. Both
haplotypes carry the allele BTL-II(E6)*2 (Price et al., 2004), as well as HLA-
DRB1*0101, HLA-DQA1*0101 and HLA-DQB1*0501 (Cattley et al., 2000). In light of
this, there are two possible explanations for the discrepancy between this and previous
studies:
1. Both AHs are associated with sIBM via a commonly inherited region, or
2. Only one of the two AHs is associated with sIBM.
Given the similarity between the 7.2AH and the 35.2AH, the association between BTL-
II(E6)*2 and sIBM as observed by Price et al. (2004) may have been incorrectly
attributed to the 35.2AH. However, O'Hanlon et al‘s (2005) report of an association
between alleles matching the 35.2AH and sIBM was based on an increased allele
frequency for these alleles in sIBM patients relative to PM patients, suggesting a real
association of the 35.2AH with sIBM.
The alternative is that a region common to both AHs confers sIBM susceptibility. The
similarity between the 35.2AH and 7.2AH around the MHC Class II region suggests
that the two haplotypes may carry identical sequences in this region, possibly along with
a common sIBM susceptibility factor. Given that 8.1AH-derived sIBM susceptibility
has also been localised to this region (Price et al., 2004), the prospect of a susceptibility
region or allele common to the 7.2AH, 35.2AH and 8.1AH warranted further
investigation (see Chapter 6).
107
5.4.5 Other Caucasian AH associations
The 62.3AH was increased in the Australian cohort, although neither allele defining this
haplotype (HLA-B*1501, HLA-DRB1*1301) was increased in patients compared to
controls. An association between sIBM and the 62.3AH was also suggested by Koffman
et al. (1998), who identified HLA-DRB1*1301 as a possible sIBM susceptibility allele
(Koffman et al., 1998b). This association has not been replicated in other studies.
5.4.6 The Japanese 52.1AH
Haplotypes matching the 8.1AH or 35.2AH are not found at appreciable frequencies in
normal Japanese populations (Saito et al., 2000) and are thus unlikely to show an
association with sIBM in the Japanese. Thus, it was expected that the Japanese cohort
would demonstrate association of sIBM with HLA alleles or haplotypes different to
those found in Caucasians. Genotyping of HLA alleles in the Japanese cohort revealed a
previously unknown genetic association with alleles matching the 52.1AH, defined by
HLA-A*2402, HLA-Cw*1202, HLA-B*5201, HLA-DRB1*1502, HLA-DQA1*0103,
HLA-DQB1*0601 (Cattley et al., 2000). While this is the first time such a susceptibility
haplotype has been statistically shown for Japanese sIBM, a previous case study
identified two sIBM-affected Japanese sisters, both of whom carried alleles matching
the 52.1AH (Tateyama et al., 2003). While anecdotal, the case study supports the
identification of the 52.1AH as an sIBM susceptibility haplotype. Both the 8.1AH and
the 52.1AH were the most common AHs in the Australian and Japanese control
populations, respectively.
The 52.1AH can be further divided into three sub-haplotypes defined by the carriage of
either HLA-DPB1*0201, HLA-DPB1*0501 or HLA-DPB1*0901 (Saito et al., 2000).
Genotyping of the HLA-DPB1 locus did not clarify whether any of these sub-haplotypes
were responsible for the observed disease association. The reduced frequency of HLA-
DPB1*0201 does not exclude the equivalent 52.1AH sub-haplotype as an sIBM
susceptibility haplotype. The observed drop in allele frequency may instead be due to
the absence of other AHs carrying this allele in the patient group. This possibility is
reinforced by the high prevalence of HLA-DPB1*0201 among the normal Japanese
population (allele frequency = 25.2%) and its presence in many other Japanese
haplotypes (Saito et al., 2000).
108
Paired HLA-B and HLA-DR alleles matching the 52.1AH were found in four
individuals from the Australian cohort, one of whom was reported as in an unrelated
study as resistant to treatment (Mastaglia et al., 2006). The occurrence of the 52.1AH in
the Australian cohort was insufficient for statistical significance and so a relationship
between the 52.1AH and sIBM in Caucasians could not be established. Conversely, the
52.1AH-associated allele HLA-DRB1*1502 was previously identified as an sIBM
susceptibility allele in one other study (Koffman et al., 1998b). These results by
Koffman et al. have not been replicated in subsequent studies, so the relationship
between HLA-DRB1*1502 and sIBM in Caucasian sIBM patients remains unclear.
5.4.7 HLA-DRB1*0901 in the Japanese cohort
Comparison of the Japanese cohort and controls revealed that HLA-DRB1*0901,
normally the most common HLA-DRB1 allele in the healthy Japanese population,
exhibited a strong negative association with sIBM. It is possible that the reduced
frequency for HLA-DRB1*0901 is the result of the much higher prevalence of the HLA-
DRB1*1502. In any given population, a higher frequency of one allele must be
compensated by an equivalently reduced frequency by other alleles. Therefore the
increase in HLA-DRB1*1502 in Japanese patients will result in a lower frequency of
those alleles that do not confer susceptibility to sIBM, including HLA-DRB1*0901.
However it is unlikely that a reduction in allele frequency from 12.4% in the normal
population to 0% in controls could be solely the result of an increase by the 52.1AH.
The alternative hypothesis is that HLA-DRB1*0901 confers a protective influence
against sIBM.
5.4.8 The 7.2AH in the Australian and Japanese cohorts
The differential effect of the same AH between ethnicities can be observed with the
7.2AH, which was identified as a susceptibility haplotype in the Australian cohort, but
not the Japanese. However unlike the 52.1AH, its absence as a susceptibility haplotype
cannot be attributed to a low frequency in the normal Japanese population. One
possibility is that the ―Caucasian‖ 7.2AH and the ―Asian‖ 7.2AH are not the same
haplotype and are genetically dissimilar between their otherwise identical defining
alleles HLA-B*0701 and HLA-DRB1*0101. This was observed previously with the
Caucasian 8.1AH, where a haplotype from Northern India also carried HLA-B*0801,
109
HLA-DRB1*0301 and HLA-DQB1*02, yet varied from the 8.1AH at HLA-Cw*07 and
HLA-DRB3 (Witt et al., 2002). Confirmation of such a phenomenon would require
screening alleles in DNA samples homozygous for both the Caucasian and Asian
7.2AH.
5.4.9 Past disease associations with sIBM susceptibility haplotypes
The four sIBM susceptibility haplotypes identified in this chapter, the 8.1AH, 7.2AH,
35.2AH and 52.1AH, have been associated with other diseases in past studies. The
diverse array of disease associations in Caucasians with the 8.1AH are well documented
(Price et al., 1999). The allele HLA-DRB1*0101, common to the 7.2AH and 35.2AH,
has been associated with susceptibility to rheumatoid arthritis (Mattey et al., 2007),
nevirapine hypersensitivity (Martin et al., 2005) protection against multiple sclerosis
(Fdez-Morera et al., 2006) and, as part of the 35.2AH, a reduced progression of AIDS
(Flores-Villanueva et al., 2003). In the Japanese, the 52.1AH is associated with
susceptibility to Takayasu arteritis (Dong et al., 1992; Kimura et al., 1996; Kitamura et
al., 1998), ulcerative colitis (Sugimura et al., 1993), abdominal aortic aneurysm with
simultaneous aorto-iliac occlusive disease (Sugimoto et al., 2003), juvenile
dermatomyositis (Tomono et al., 2004) and resistance to type 1 diabetes mellitus
(Awata and Kanazawa, 1994). It may be possible that a single mechanism in each
haplotype drives susceptibility or protection to the associated diseases. Furthermore, one
or more of these haplotypes may share this mechanism. This may, in turn, also cause
susceptibility to sIBM in these haplotypes.
5.4.10 Future studies
In this chapter, the relationship between the 8.1AH in Caucasians and sIBM
susceptibility was confirmed in the Australian and American cohorts. HLA-genotyping
revealed a strong association between the 52.1AH and sIBM in the Japanese cohort, and
the AH-specificities did not overlap between the two ethnicities investigated. It is still
unclear as to whether the 7.2AH, the 35.2AH or a region common to both AHs
influence sIBM susceptibility in Caucasians and so further investigation of these two
haplotypes is recommended.
Given that four MHC haplotypes are associated or potentially associated with sIBM, the
most logical explanation is that a mechanism common to these haplotypes drives the
110
sIBM association. A hypothesis such as this could be tested by genotyping a wide
selection of candidate alleles, for example those identified in Chapter 3, in control
individuals carrying the sIBM susceptibility haplotypes. This was the approach was
taken in Chapter 6.
Another option for investigating sIBM susceptibility within the assembled patient
cohorts is through recombination mapping – by genotyping multiple patients carrying
part of a susceptibility haplotype to identify a common overlapping region.
Recombination mapping was previously used to define the 8.1AH-derived sIBM
susceptibility region (Kok et al., 1999; Price et al., 2004). The same approach could be
used for patients potentially carrying part of the 8.1AH, 7.2AH, 35.2AH or 52.1AH to
identify a common susceptibility region within each of the sIBM-associated AHs, or
which may overlap between all of the susceptibility haplotypes. Recombination
mapping of the 8.1AH is described in more detail in Chapters 6 and 7.
Publication arising from this chapter (See Appendix):
Scott AP, Allcock RJ, Mastaglia F, Nishino I, Nonaka I, Laing N (2006) Sporadic
inclusion body myositis in Japanese is associated with the MHC ancestral
haplotype 52.1. Neuromuscular Disorders 16:311-315
111
CHAPTER SIX
6 CHARACTERISATION OF SIBM-ASSOCIATED HAPLOTYPES IN THE 8.1AH-DEFINED
SUSCEPTIBILITY REGION
112
6.1 Abstract
The aim of this chapter was to investigate whether the identified sIBM-associated
haplotypes, the 8.1AH, 7.2AH, 35.2AH and 52.1AH, confer sIBM susceptibility
through a common allele. Promoter and exonic polymorphisms, characteristic of the
8.1AH within the sIBM susceptibility region (Price et al., 2004), were identified and
genotyped in cell lines carrying the 7.2AH, 35.2AH and 52.1AH. The specificity of
alleles to these haplotypes was assessed and implications for the hypothesis of a
common susceptibility allele between sIBM-associated haplotypes is discussed. None of
the alleles investigated were specific to all of the sIBM-associated AHs, although the
minor allele for rs2050189 was found in the 8.1AH, 7.2AH, 52.1AH and one non-sIBM
associated AH in Caucasians. Further investigation of this allele in Caucasian sIBM
cohorts showed insufficient evidence for a direct association between rs2050189 and
sIBM.
6.2 Introduction
Prior to this thesis, studies had shown that the 8.1AH (HLA-B*0801, HLA-DRB1*0301,
HLA-DQB1*0201) and the 35.2AH (HLA-B*3501, HLA-DRB1*0101, HLA-
DQB1*0501) are associated with sIBM in Caucasians (Price et al., 2004; O'Hanlon et
al., 2005). The results of Chapter 5 suggested that the 52.1AH in the Japanese (HLA-
B*5201, HLA-DRB1*1502) was also associated with susceptibility (Section 5.4.6). The
35.2AH was identified as a potential sIBM susceptibility haplotype by the co-
inheritance of HLA-DRB1*0101 and the allele BTL-II(E6)*2. This allele combination is
also carried by the 7.2AH – a haplotype considered by Price et al. (2004) to be absent in
Caucasians. The results presented in Chapter 5 suggest that not only is the 7.2AH found
in Caucasians, but also that it shows a statistically significant association with sIBM. It
can thus be proposed that either the 7.2AH, the 35.2AH, or a region common to both
confers susceptibility to sIBM.
There are seven expressed genes common to the 8.1AH, 7.2AH, 35.2AH and 52.1AH
within the 8.1AH-derived sIBM susceptibility region defined by Price et al. (2004) –
PBX2, GPSM3, NOTCH4, C6orf10, HCG23, BTNL2 and HLA-DRA (Figure 6.1).
Additional expressed genes exist within the sIBM susceptibility region but are present
in no more than one of the sIBM susceptibility haplotypes. Specifically, between HLA-
DRA and HLA-DRB1 the 8.1 and 52.1AHs each carry one additional expressed gene,
113
HLA-DRB3 and HLA-DRB5 respectively, while the 35.2AH and 7.2AH do not carry any
expressed genes within the region (Andersson et al., 1994).
PBX2
GPSM3
NOTCH4 C6orf10 HCG23
BTNL2
HLA-DRA HLA-DRB3 HLA-DRB1
Figure 5.1: The 389kb sIBM susceptibility region between PBX2 and HLA-DRB1, as found
in the MHC on chromosome 6p21.3. The gene content of the region between HLA-DRA and
HLA-DRB1 varies between haplotypes and while found in the 8.1AH, HLA-DRB3 is not
present in the 7.2AH, 35.2AH or 52.1AHs {Andersson, 1994 #343}. Pseudogenes are not
shown.
Tel
om
ere
Cen
tro
mer
e
52.1AH
7.2AH, 35.2AH
8.1AH
HLA-DRB5
Figure 6.1: The 389kb sIBM susceptibility region between PBX2 and HLA-DRB1, as
found in the human MHC. The gene content of the region between HLA-DRA and HLA-
DRB1 varies between haplotypes and while found in the 8.1AH, HLA-DRB3 is not
present in the 35.2 or 52.1AHs (Andersson et al., 1994). Pseudogenes are not shown.
Genetic factors on the 8.1AH, 52.1AH and the 7.2AH/35.2AH could confer
susceptibility to sIBM by one of two mechanisms. The first is that several of the
haplotypes share one or more identical disease susceptibility alleles, which could either
be inherited from a common ancestor, or the result of a historical recombination or gene
conversion event between haplotypes. Gene conversion is the unidirectional transfer of
genetic material, normally 200bp-1kb in length, between sister chromatids, homologous
chromosomes, or homologous sequences on the same or different chromosomes (Chen
et al., 2007). Alternatively, each haplotype may instead have developed susceptibility
alleles independently, all of which lead to a similar mechanism of disease pathogenesis
and phenotype. In this instance, the probability of two or more of these haplotypes
sharing one or more identical susceptibility alleles is negligible.
The objective of this chapter was to investigate the first hypothesis – that sIBM
susceptibility may be conferred through an allele common to multiple sIBM
susceptibility haplotypes. If sIBM susceptibility is conferred by an allele common to all
sIBM susceptibility haplotypes, such an allele should be specific to the 8.1AH, the
52.1AH and the 7.2AH/35.2AH. In order to test this hypothesis, candidate coding and
promoter alleles in the 8.1AH were genotyped in cell lines carrying the 7.2AH, 35.2AH
and 52.1AH. Alleles found in the 8.1AH and more than one of the three other AHs were
then genotyped on additional AH cell lines, totalling 27 AHs, to define the specificity of
the allele to the sIBM-associated haplotypes.
114
6.3 Results
6.3.1 Selection of polymorphisms
As described in Chapter 3, the investigated sIBM susceptibility region from RNF5 to
HLA-DRA contained 658 polymorphisms on the COX cell line (8.1AH) but not the PGF
(7.1AH), QBL (18.2AH) and SSTO (44.2AH) cell lines. Of these, 35 polymorphisms
haplotypic of the 8.1AH (ie. the minor allele was found in the COX cell line) were
within gene promoters (defined as less than 1.5kb from the 5‘ end of the associated
gene) or exonic regions. This excluded those polymorphisms in RNF5 or PBX2, which
do not lie within the proposed sIBM susceptibility region (Price et al., 2004). Despite
matching the criteria for inclusion in this study, the polymorphisms rs7773668 (BTNL2
promoter), rs28993482 (HLA-DRA promoter) and rs3210271 (HLA-DRA exonic region)
were not studied further due to difficulties in designing primers that would amplify the
region surrounding each SNP. The characteristics of the remaining 32 polymorphisms
are shown in Table 6.1.
6.3.2 Analysis of sIBM susceptibility haplotypes
The 32 selected polymorphisms were genotyped in the 10IHW cell lines REE GD
(8.1AH), KUROIWA (7.2AH) WT100BIS (35.2AH), and HARA (52.1AH) using
sequencing, RFLP or Genescan, with the results shown in Table 6.2.
The COX and REE GD cell lines, both of which were derived from unrelated Caucasian
donors and homozygous for the 8.1 AH, were identical at all loci analysed with the
exception of rs9268642.
rs no.Associated
Gene
Position Relative to
Gene a
Nucleotide
Change
Population
Frequency b
Amino Acid
Change
rs3134605 GPSM3 coding A > G - H-->R
rs3134942 NOTCH4 coding C > A 0.100 V-->V
rs422951 NOTCH4 coding A > G 0.367 T-->A
rs915894 NOTCH4 coding A > C 0.310 K-->Q
rs443198 NOTCH4 coding T > C 0.292 G-->G
rs9281675c
NOTCH4 coding 6-12CTG - 6L-->12L
rs3130295 NOTCH4 promoter -1375 C > T - -
rs9279514 NOTCH4 promoter -1460 16T-21T - -
rs7775397 C6orf10 coding T > G 0.092 K-->Q
rs3749966 C6orf10 coding T > C 0.208 I-->V
rs1265754 C6orf10 coding A > T 0.092 I-->F
rs2050189 C6orf10 5' UTR -164 A > G 0.175 -
rs3117110 C6orf10 promoter -523 G > A - -
rs3117109 C6orf10 promoter -1218 G > A - -
rs3129944 C6orf10 promoter -1219 C > G 0.142 -
rs3129950 HCG23 promoter -86 G > C 0.092 -
rs3117099 HCG23 promoter -17 C > T 0.129 -
rs3129953 BTNL2 coding C > T 0.108 T-->T
rs9268632 HLA-DRA promoter -1269 C > G - -
rs9268636 HLA-DRA promoter -1070 C > A - -
rs9357142 HLA-DRA promoter -793 G > A - -
rs9268641 HLA-DRA promoter -777 C > T 0.227 -
rs9268642 HLA-DRA promoter -566 C > T 0.000 -
rs3129872 HLA-DRA promoter -511 A > T 0.233 -
rs2395179 HLA-DRA promoter -362 A > G 0.241 -
rs2395180 HLA-DRA promoter -354 T > G 0.241 -
rs2395181 HLA-DRA promoter -260 G > C 0.233 -
rs3129873 HLA-DRA promoter -231 G > C - -
rs3129874 HLA-DRA promoter -224 T > C - -
rs3129875 HLA-DRA promoter -196 T > C 0.204 -
rs1131541 HLA-DRA 3' UTR +149 T > A - -
rs1051336 HLA-DRA 3' UTR +175 G > A 0.125 -
c - Also referred to as rs28359855, with a different repeat number. dbSNP lists rs9281675 in
the 3'-5' orientation, as a CAG repeat.
Table 6.1: Alleles in the coding and promoter regions of genes in the sIBM susceptibility
region, between the centromeric ends of PBX2 and HLA-DRA. The alleles listed are found in
COX (8.1AH) but not QBL (18.2AH), SSTO (44.1AH) or PGF (7.1AH).
a - Distance in bp either upstream of the first exon (for promotor polymorphisms), upstream
of the start codon (negative value - for 5' UTR polymorphisms), or downstream of the stop
codon (positive value - for 3' UTR polymorphisms).
b - The population frequency of the minor allele is from dbSNP
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp), with the "CEU" population used as
a reference. CEU is a Caucasian population consisting of more than 100 Utah residents with
ancestry from northern and western Europe.
10IHW
cell line 90
22
a
91
32
91
31
90
06
91
42
Name
CO
X
RE
E G
D
KU
RO
IWA
WT
10
0B
IS
HA
RA
AH 8.1 8.1 7.2 35.2 52.1
rs3134605 G G A A A GPSM3
rs3134942 A A C C C
rs422951 G G G G A
rs915894 C C A A C
rs443198 C C T T C NOTCH4
rs9281675bc 12r 12r 6r 6r 10r
rs3130295 T T C C C
rs9279514c 16r 16r 17r 17r 20r
rs7775397 G G T T T
rs3749966 C C T T T
rs1265754 T T A A A
rs2050189 G G G A G C6orf10
rs3117110 A A G G G
rs3117109 A A G G G
rs3129944 G G C C G
rs3129950 C C G G G
rs3117099 T T C C T
rs3129953 T T C C C BTNL2
rs9268632 G G C G C
rs9268636 A A C C C
rs9357142 A A A A G
rs9268641 T T T T C
rs9268642 T C C C C
rs3129872 T T T T A
rs2395179 G G G G A
rs2395180 G G G G T
rs2395181 C C C C G
rs3129873 C C C C G
rs3129874 C C C C T
rs3129875 C C C C T
rs1131541 A A T T T
rs1051336 A A G G G
Table 6.2: Genotyping to identify alleles common to the 8.1AH and
the 7.2AH, 35.2AH, or 52.1AH.
a - Genotyping data for COX was derived from sequence data
published by the Sanger MHC Haplotype Project
(http://www.sanger.ac.uk/HGP/Chr6/MHC/).
b - Also referred to as rs28359855, with a different repeat number.
c - The results for rs9281675 and rs9279514 are displayed as the
number of microsatellite repeats.
HCG23
HLA-DRA
117
Fourteen of the polymorphisms analysed were found in HLA-DRA. The minor (rare)
allele for nine of these polymorphisms, all of which were in the promoter, was shared
by the 8.1AH, 7.2AH and 35.2AH with one more shared by the 8.1AH and 7.2AH. Two
of the twelve alleles carried by the 8.1AH within the HLA-DRA promoter were found
only in the 8.1AH (rs9268636 and rs9268642) and the alleles for both exonic HLA-DRA
polymorphisms (rs1131541 and rs1051336) were not found in the non-8.1AH cell lines
(Table 6.2).
Outside the HLA-DRA region, the minor allele of the NOTCH4 coding SNP rs422951,
was found in the 8.1AH, 7.2AH and 35.2AH. The 8.1AH and 52.1AHs shared five of
the alleles genotyped, of which two were located in NOTCH4 (rs915894 and rs443198),
two in C6orf10 (rs2050189 and rs3129944) and one in HCG23 (rs3117099). The minor
allele of rs2050189 was found in the 7.2AH in addition to the 8.1AH, and the 52.1AH
(Table 6.2). The cell lines carrying the 7.2AH and 35.2AH shared the same allele at all
loci tested, with the exception of rs2050189 and rs9268632.
In total 16 polymorphisms were shared between the cell lines carrying the 8.1AH and
either the 7.2AH, 35.2AH or 52.1AH. The remaining alleles were found only on the
8.1AH (Table 6.2).
6.3.3 Analysis of multiple ancestral haplotypes
Having initially identified polymorphisms that were found on the 8.1AH and the
52.1AH, 35.2AH or 7.2AH, it was next necessary to determine which other haplotypes
carried these alleles. All sixteen polymorphisms of interest were genotyped in a larger
panel of 27 10IHWS cell lines (Table 6.3). Of the 16 alleles investigated, none were
found exclusively on the 8.1AH and one or more of the sIBM susceptibility AHs (ie. the
7.2AH, 35.2AH and 52.1AH). In determining alleles found in the 8.1AH, the 52.1AH
and either the 7.2AH or 35.2AH, only rs2050189 fulfilled the criteria. The minor allele
of rs2050189 has a frequency of 0.175 (Table 6.1).
The 10 polymorphisms associated with the HLA-DRA promoter almost always carried
their respective minor alleles in the same cell lines, suggesting that these alleles are
normally inherited as a single block.
Table 6.3: Haplotypic distribution of 16 selected alleles between the centromeric ends of PBX2 and HLA-DRA in twenty seven 10th Workshop cell lines.
10IHW cell 9013 9131 9022 9132 9046 9008 9020 9042 9006 9136 9026 9021 9302 9050 9053 9076 9066 9047 9142 9141 9133 9156 9098 9059 9031 9060 9079
Name SCHU KUROIWA COX REE GD BH DO208915 QBL TISI WT100BIS SPE, G YAR RSH SSTO MOU HOR T7526 TAB089 PLH HARA HOKKAIDO MAD, MF WON, PY MT14B SLE005 BOLETH CB6B LWAGS
Zygositya - - Con Het - - Con Con Con Het Hom - Hom Con - Het - Con Hom Hom Het Hom Con - Con Con Hom
AH 7.1 7.2 8.1 8.1 13.1 18.1 18.2 35.1 35.2 18.2/35.3 38.1 42.1 44.1 44.2 44.4 46.1 46.2 47.1 52.1 54.1 57.1/8.1 58.1 60.1 60.3 62.1 62.3 65.1
HLA Ab 0301 24 0101 0101 0201 2501 2601 2402 1101 1101:3002 2601 3001:6802 3201 2902 3303 0206:0207 0207:0201 0301 24 24 1:3 33 3101 0201 0201 0101 3301
HLA B 0702 7 0801 0801 1302 1801 1801 3508 3501 18:35 3801 4201 4402 4403 4403 4601 4601 4701 52 54 8:57 58 4001 4001 1501 1501 1402
rs422951 A Gc
G G G A A G G G:A G A A A G A A A A A G A A A G A A
rs915894 A A C C C A A A A A A A A C C C A A C C C A A A C A C
rs443198 T T C C C T T T T T T T T C C C T C C C C T T T T T C
rs2050189 A G G G A A A G A A A A A A A A:G A G G A A:G A A A A A A
rs3129944 C C G G C C C C C C C G C C G C G C G G C:G C C G C C G
rs3117099 C C T T C C C C C C C T C C C C T C T T T:C C C C:T C C T
rs9268632 C C G G C C C C G C:G C C C C G C C G C C C:G C C G C C C
rs9357142 G A A A G G G G A G G G G G A G G A G G G G G A G G G
rs9268641 C T T T C C C C T C:T C C C C T C C T C C C:T C C T C C C
rs3129872 A T T T A A A A T A:T A A A A T A A T A A A:T A A T A A A
rs2395179 A G G G A A A A G A:G A G A A G A G G A A A:G A A G A A A
rs2395180 T G G G T T T T G T:G T G T T G T G G T T T:G T T G T T T
rs2395181 G C C C G G G G C G:C G C G G C G C C G G G:C G G C G G G
rs3129873 G C C C G G G G C G:C G G G G C G G C G G G:C G G C G G G
rs3129874 T C C C T T T T C C:T T T T T C T T C T T C:T T T C T T T
rs3129875 T C C C T T T T C C:T T C T T C T C C T T C:T T T C T T T
HLA-DRB1* 1501 0101 0301 0301 0701 1501 0301 1103 0101 0101:0301 0402 0302 0403 0701 1302 0901 0803 0701 1502 0405 0301:07 0301 0404 1302 0401 1301 0102
HLA-DQB1* 602 0501 0201 0201 0202 0602:0603 0201 0301 0501 0201:0501 0302 0402 201 0604 0303 0601 0202 0601 0401 0201:0303 0201 0302 0302 0603 0501
a - For cell line zygosity, Con = Consanguineous; Het = Heterozygous, Hom = Homozygous.
b - HLA genotyping data derived from the IMGT/HLA database (http://www.ebi.ac.uk/imgt/hla/) and supplemented by Cattley et al. (2000).
c - Minor alleles are shaded. For heterozygous cell lines, the alleles are only shaded if the haplotype marked in bold carries the minor allele.
119
The ―MAD, MF‖ cell line, which carries the 8.1AH (Cattley et al., 2000), did not carry
the minor allele of rs9357142. A similar type of discrepancy has been noted previously
in other regions of the MHC. For example the cell lines T7526 (46.1AH) and SLE005
(60.3AH), which are considered homozygous for their respective haplotypes (Cattley et
al., 2000), were heterozygous for the rs2050189 and rs3117099 SNPs, respectively
(Table 6.3).
A breakdown of the number of AHs carrying each allele (Table 6.4) showed that the
minor alleles of rs2050189 and rs9357142 were both carried by the least number of non-
sIBM associated haplotypes (three each). When AHs not normally found in Caucasians
were removed from the analysis, the rs2050189 minor allele was found in only one
other AH, specifically the 35.1AH. By the same criteria of including only Caucasian,
non-sIBM associated AHs in the analysis, the rs9357142 minor allele and all of the
minor alleles analysed in the HLA-DRA promoter were found in only two haplotypes -
the 44.4AH and the 60.3AH.
6.3.4 Analysis of rs2050189
The only polymorphism found in the 8.1AH, 7.2AH and 52.1AH was the minor allele
of rs2050189. The allele was thus genotyped in the Australian and American sIBM
patient cohorts described in Section 2.1. Genotyping was performed using single strand
conformation polymorphism analysis (SSCP; Section 2.2.9), and in several cases
confirmed by direct sequencing (Section 2.2.6). An additional allele not haplotypic of
the 8.1AH and not relevant to this study (rs2073045) was also located within the
amplicon. This allele did not affect the SSCP results (data not shown). Four Australian
patients were excluded from this investigation due to failed genotyping.
Table 6.4: The total number of haplotypes investigated carrying each allele.
Susceptibility
AHs onlya
Non-susceptibility
AHs only
Caucasian, non-
susceptibility AHs onlyb
rs422951 3 7 6
rs915894 2 8 6
rs443198 2 8 5
rs2050189 3 3 1
rs3129944 2 6 3
rs3117099 2 5 2
rs9268632 2 4 2
rs9357142 3 3 2
rs9268641 3 4 2
rs3129872 3 4 2
rs2395179 3 6 2
rs2395180 3 6 2
rs2395181 3 6 2
rs3129873 3 4 2
rs3129874 3 4 2
rs3129875 3 6 2
a - Susceptiblity haplotypes were considered the 7.2AH, 8.1AH, 35.2AH and
52.1AH
b - "Caucasian" haplotypes were those found in the control population as
detailed in Table 3.4. Specifically, this excluded the 35.3AH, 42.1AH,
46.1AH, 46.2AH, 47.1AH and 54.1AH
121
Genotyping results for rs2050189 in the Australian and American cohorts are shown in
Table 6.5 and Table 6.6 respectively. The rs2050189 minor (G) allele was present in
58.9% of the Australian cohort (43/73) and 75% of the American cohort (21/28). Of the
62 Australian and American patients genotyped for rs2050189 and carrying the 7.2AH,
8.1AH or 52.1AH, ten did not carry a matching minor allele. Three more individuals
carried 7.2AH or 8.1AH on both chromosomes, yet were heterozygous for the minor
allele (AU_86, AM_11, AM_28 Table 6.5 and Table 6.6). Of the six Australian and
American patients analysed that carried the 7.2AH, four did not carry a corresponding
minor allele for rs2050189 (AU_36, AU_56, AU_72 and AU_75; Table 6.5) and one
more was heterozygous for the minor allele despite carrying both the 8.1AH and 7.2AH
(AM_11; Table 6.6).
The allelic frequency for the rs2050189 minor allele was increased in the Australian
cohort, at 34.9% compared to 17.5% in controls (OR=2.53, p=0.001; Table 6.7). When
homozygous and heterozygous genotypes containing the rare allele were considered
together (AG/GG), the allele was found in 58.9% of patients compared to 33.4% of
controls (OR=2.87, p=0.005; Table 6.7).
Similar results were observed for the American cohort, with a statistically significant
increase in the minor (G) allele frequency of 50%, compared to 17.5% in controls
(OR=4.71, p<0.001; Table 6.7). The frequency of genotypes carrying the minor allele
(AG/GG) was increased (75% vs. 33.4%; OR=6.00, p<0.001). However unlike the
Australian cohort, the frequency of the homozygous rare genotype (GG) was also
increased, at 25% compared with 1.7% in controls (OR=19.67, p=0.001).
Table 6.5: Occurence of the minor allele for rs2050189 in Australian patients.
Patient
Presence of
7.2AH, 8.1AH
or 52.1AH?b
rs2050189 matches
the 8.1AH, 7.2AH
or 52.1AH?
AU_1 18 27 A A 3 3a
AU_3 8 51 A A 1 13
AU_4 40 40 A G 3 13
AU_5 5 8 A G 3 13 8.1
AU_6 8 35 A A 1 3 8.1 No
AU_7 8 40 G G 3 4 8.1
AU_8 8 44 A G 01 0301 8.1
AU_9 8 35 A A 1 3 8.1
AU_10 8 44 A G 3 3 8.1
AU_12 8 44 G G 3 13 8.1
AU_13 8 15 A G 3 6 8.1
AU_14 7 51 A A 3 7
AU_15 8 NDc
A A 3 13 8.1 No
AU_16 8 35 A G 1 3 8.1
AU_17 7 38 A G 03 15
AU_18 14 ND A A 1 13
AU_19 7 8 A G 3 15 8.1
AU_20 8 51 A G 3 13 8.1
AU_21 8 15 A G 0301 1301 8.1
AU_22 7 35 A G 3 13
AU_23 8 8 A G 1 3 8.1
AU_28 8 8 A G 3 13 8.1
AU_29 5 44 G G 1001 1502 52.1
AU_32 8 15 A G 0301 1001 8.1
AU_33 7 8 A G 03 08 8.1
AU_34 07 4002 A G 0107 0401
AU_35 0801 2705 A G 0101 0301 8.1
AU_36 7 8 A A 0101 0401 7.2 No
AU_37 08 4402 A G 0301 0401 8.1
AU_41 1501 3901 A G 03 16
AU_42 0801 4403 A G 0101 0301 8.1
AU_43 0801 4102 A G 0301 1303 8.1
AU_45 0801 3801 G G 0301 0301 8.1
AU_46 5101 5101 A A 0301 701
AU_48 0801 4901 A G 0301 1101 8.1
AU_49 0801 1501 A G 0301 1301 8.1
AU_50 1501 1801 A G 0301 1301/02
AU_51 0801 4001 A G 0301 1301 8.1
AU_52 8 44 G G 0301 1001 8.1
AU_53 07 51 A A 0301 1301
AU_54 0801 3501 A G 0101 0301 8.1
AU_55 0801 3901 A G 0301 1601 8.1
AU_56 07 15 A A 0101 0101 7.2 No
AU_57 5201 5703 A A 11 15 52.1 No
AU_58 3501 3906 A A 0103 0801
AU_59 0801 4001 G G 0101 0301 8.1
AU_60 0801 4402 A G 0301 1501 8.1
AU_61 0801 15 A A 0101 0301 8.1 No
AU_62 3501 4102 A A 0101 0101
AU_63 3901 4402 A A 0401 0801/02
AU_64 0801 15 A G 0301 1301 8.1
AU_65 1501 4001 A A 0401 0404
AU_66 1801 4403 A A 0701 1501
AU_67 0801 0801 G G 0301 0301 8.1
AU_69 0801 4402 A G 0101 0301 8.1
AU_70 0801 1501 A G 0101 0301 8.1
AU_71 08 3701 A A 0301 1001 8.1 No
AU_72 0702 5701 A A 0101 0701 7.2 No
AU_73 2705 5701 A A 0401 0701
AU_74 1801 3501 A A 0101 0301
AU_75 0702 4402 A A 0101 0301 7.2 No
AU_76 3501 4501 A G 0301 1301
AU_77 0801 4901 A A 0301 0301 8.1 No
AU_78 1302 2705 A A 0401 0701
AU_79 0801 1501 A G 0301 1301/02 8.1
AU_80 3906 4901 A A 0404 1501
AU_81 1501 4402 A A 0401 1301
AU_82 0801 4402 A G 0101 0301 8.1
AU_83 3501 4501 A A 0101 1101
AU_84 0801 3501 A G ND ND
AU_85 3502 5201 A A 1101/041501/02 52.1
AU_86 0801 0801 A G 0301 0301 8.1 / 8.1 No
AU_87 0801 1501 A G 0301 1301 8.1
a - The minor allele is given in brackets.
b - Haplotypes were predicted as detailed in Chapter 5.
c - ND = Not determined/unable to determine.
HLA-B*rs2050189
(G)a HLA-DRB1*
Patient
Presence of
7.2AH, 8.1AH
or 52.1AH?b
rs2050189 matches
the 8.1AH, 7.2AH
or 52.1AH?
AM_1 0702 4001 A G 1001 1602
AM_2 0702 5601 A A NDc
ND
AM_3 0702 4402 G G 0101 1301 7.2
AM_4 1501 1510 A A 0101 1001
AM_5 2702 3502 G G 1101 1101
AM_6 0801 4901 A G 0301 1001 8.1
AM_7 1801 3501 G G 0101 0301
AM_8 3502 4403 A A 0101 1104
AM_9 3501 3901 G G 0101 1101
AM_10 4402 5101 A G 0101 1602
AM_11 0702 0801 A G 0101 0301 8.1 / 7.2 No
AM_12 0801 4001 G G 0301 0801 8.1
AM_13 1801 3501 A A 0101 1501
AM_14 0801 1501 A G 0101 0301 8.1
AM_15 3501 3906 A A 0101 1301
AM_16 4402 4901 A A 0101 1301
AM_17 4402 5101 A A 0801 1101
AM_18 0801 3906 G G 0301 0801 8.1
AM_19 1510 4201 A G 0302 1503
AM_20 1801 4001 A G 0301 1104
AM_21 0801 5001 A G 0301 0301 8.1
AM_22 0801 2705 A G 0101 0301 8.1
AM_23 0801 1501 A G 0301 1301 8.1
AM_24 0801 5201 A G 0301 1501 8.1
AM_25 0801 4001 A G 0301 0801 8.1
AM_26 0702 0801 A G 0301 1501 8.1
AM_27 0801 5101 G G 0301 0301 8.1
AM_28 0801 0801 A G 0301 0301 8.1 / 8.1 No
a - The minor allele is given in brackets.
b - Haplotypes were predicted as detailed in Chapter 5.
c - ND = Not determined/unable to determine.
Table 6.6: Occurence of the minor allele for rs2050189 in American patients.
HLA-B* rs2050189 (G)a HLA-DRB1*
Australian Patients American Patients Controlsa
% (n/total) p-value OR (95%CI) % (n/total) p-value OR (95%CI) % (n/total)
rs2050189 G 34.9 (51/146) 0.001 2.53 (1.42-4.52) 50.0 (28/56) <0.001 4.71 (2.33-9.53) 17.5 (21/120)
AG 49.3 (36/73) 0.052 2.10 (1.03-4.28) 50.0 (14/28) 0.106 2.16 (0.86-5.41) 31.7 (19/60)
GG 9.6 (7/73) 0.072 6.26 (0.75-52.37) 25.0 (7/28) 0.001 19.67 (2.28-169.46) 1.7 (1/60)
AG/GG 58.9 (43/73) 0.005 2.87 (1.41-5.84) 75.0 (21/28) <0.001 6.00 (2.19-16.47) 33.4 (20/60)
Table 6.7: Frequency of rs2050189 alleles and genotypes in the Australian and American cohorts compared with a control
Allele/Genotype
a - The control population used for rs2050189 was the Caucasian "CEU" population, available from dbSNP
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp; Accessed 15-2-2008).
125
6.4 Discussion
6.4.1 Alleles common to multiple susceptibility haplotypes
The hypothesis addressed in this study was that multiple sIBM susceptibility haplotypes
share one or more identical disease susceptibility alleles, either through a common
ancestor or by a historical recombination or gene conversion event between haplotypes.
An allele haplotypic of the 8.1AH and either the 7.2AH or 35.2AH is unlikely to have
been derived from a common ancestor. This is because phylogenetic analysis of HLA-
DRB loci revealed that HLA-DRB1*0301 (8.1AH) is not closely related to HLA-
DRB1*0101 (7.2AH and 35.2AH) (Bergstrom et al., 1999). If the 8.1AH and either the
7.2AH or 35.2AH carried a susceptibility allele derived from a common ancestor, then
many other haplotypes derived from the same ancestor would also be likely to carry this
susceptibility allele.
Alternatively, a susceptibility allele may have arisen on one established haplotype first,
such as the 8.1AH, before it was passed on to the 7.2AH, 35.2AH and/or 52.1AH as
they are currently defined, through recombination or gene conversion events. Gene
conversion in particular may have resulted in the transfer of a 200bp-1kb region
containing the susceptibility allele on one haplotype, such as the 8.1AH, to other
haplotypes like the 7.2AH, 35.2AH and the 52.1AH.
Of the alleles investigated, those in the HLA-DRA promoter region and the minor allele
for rs2050189 were the most relevant in addressing whether multiple sIBM-associated
haplotypes may carry a common disease susceptibility allele.
6.4.2 Alleles in the HLA-DRA promoter region
Almost all of the investigated alleles across the HLA-DRA promoter were found in three
of the sIBM susceptibility haplotypes, the 8.1AH, 7.2AH and 35.2AH, and only two
other Caucasian haplotypes (44.4AH and 60.3AH). This suggests a common region
between these haplotypes, which may additionally confer susceptibility to sIBM in
Caucasians via one of these alleles. Past research has also shown a six-fold increase in
HLA-DRA mRNA expression in sIBM patients (Greenberg et al., 2002). This may be
evidence of a link between promoter region polymorphisms and sIBM pathogenesis,
126
although it could instead be a result of downstream immunological processes, unrelated
to pathogenesis.
If one or more of the HLA-DRA promoter alleles conferred susceptibility to sIBM, then
the frequency of the 44.4AH and 60.3AH, which carry these alleles, should also be
increased in Caucasian sIBM patients. However whilst the 44.4AH, 60.3AH and their
component alleles (HLA-B*4403, HLA-B*4001, HLA-DRB1*1302) were present in
Caucasians, there was no observable increase in sIBM patients (Table 5.2, Table 5.3,
Table 5.4). It is thus unlikely that the HLA-DRA promoter alleles themselves confer
sIBM susceptibility.
6.4.3 The rs2050189 minor allele
While none of the alleles were unique to the 8.1AH and more than one of the other
susceptibility haplotypes, the rs2050189 minor allele was common to the 8.1AH,
7.2AH, 52.1AH and three other non-sIBM associated AHs – the 35.1AH, 46.1AH and
47.1AH. The rs2050189 minor allele is located in the 5‘ UTR of the gene C6orf10
(Table 6.1). Very little research exists on this gene and aside from its expression in
human testes (Liang et al., 1994) and the adult medulla (Strausberg et al., 2002), the
function of C6orf10 has yet to be characterised.
If rs2050189 was to confer susceptibility to sIBM, then the 35.1AH, 46.1AH and
47.1AH should also show an increased frequency in sIBM patients. Of those, the
46.1AH and 47.1AH are not normally found in Caucasians or the Japanese, which is
suggested from their absence in the control populations used in Chapter 5 (Table 5.4
and Table 5.11). Thus if rs2050189 confers susceptibility to sIBM then this would
account for why the 46.1AH and 47.1AH were not increased amongst the Caucasian
patients. Despite carrying the minor allele for rs2050189, the 35.1AH may not have
been increased in patients due to its rarity in Caucasians. The 35.1AH was found in one
individual in the Caucasian control cohort (phenotype frequency = 0.6%; Table 5.4),
and may have thus failed to show an increase in sIBM susceptibility due to a lack of
statistical power (type II statistical error).
Genotyping of the rs2050189 locus in the Australian and American sIBM patient
cohorts revealed conflicting results. The allele frequency and carriage of the rs2050189
minor allele was significantly increased in both sIBM patient cohorts. This suggests that
127
either the rs2050189 minor allele or another allele within linkage disequilibrium is
involved in conferring susceptibility to the 8.1AH. However, several discrepant
individuals carrying the 8.1AH, 7.2AH or 52.1AH did not carry a corresponding minor
allele, including almost all patients carrying the 7.2AH. The AHs assigned to each
patient are based on the presence of particular HLA-B/HLA-DRB1 allele combinations.
It is thus possible that some of these ‗discrepant‘ individuals do not in fact carry the
8.1AH, 7.2AH or 52.1AH in the first place. Confirmation of a given AH requires further
haplotypic alleles to be genotyped in each patient. Suitable genotyping data for
confirming the presence of the 7.2AH or 52.1AH in the Australian and American
patients are not available, so these haplotypes can be neither confirmed nor disproven in
the discrepant patients. However such data is available for the 8.1AH from three
NOTCH4 SNPs and one microsatellite genotyped in Chapter 4. Of the eight discrepant
patients carrying the 8.1AH (AU_6, AU_15, AU_61, AU_71, AU_77, AU_86, AM_11
and AM_28), all of these individuals also carried all four 8.1AH-defining NOTCH4
alleles from Chapter 4, which provides strong evidence for the presence of the 8.1AH in
these patients.
The inconsistent occurrence of the rs2050189 minor allele in the 8.1AH and its near-
absence in patients with the 7.2AH suggests that this allele is unlikely to be indicative of
a common region between the sIBM-associated haplotypes. While the rs2050189 minor
allele was increased in patients, this association could still be a result of its carriage with
the 8.1AH in the majority of patients with that haplotype.
6.4.4 Alleles common to the 7.2AH, 35.2AH and 52.1AH
Unlike the 8.1AH, detailed sequence data was not available for the 7.2AH, 35.2AH or
52.1AH. Therefore alleles common to two or more of these haplotypes, but excluding
the 8.1AH could not effectively be assessed. Should such sequence data become
available, the possibility of a shared disease susceptibility allele between the 52.1AH
and either the 7.2AH, 35.2AH or both warrants consideration.
6.4.5 Alleles outside of the exonic or promoter regions
Although this study comprehensively screened 8.1AH-haplotypic promoter and coding
region alleles within the sIBM susceptibility region, it remains possible that an allele
unique to multiple sIBM susceptibility haplotypes may exist within an intron or in the
128
intergenic regions. For example, an intronic polymorphism in a critical position could
affect the splicing of its associated gene, possibly resulting in an aberrant mRNA that
could lead to an altered phenotype (Cartegni et al., 2002). Screening all alleles outside
of the coding and/or promoter regions within the 8.1AH sIBM susceptibility region for
their presence in multiple AHs would require genotyping more than 600 polymorphisms
in multiple cell lines. An alternative approach is to reduce the number of candidate
polymorphisms through methods such as recombination mapping, before screening the
polymorphisms themselves.
6.4.6 Independently acquired susceptibility alleles
Unless a functional link between sIBM and a specific polymorphism can be established,
the hypothesis that the 8.1AH developed sIBM susceptibility independently from the
7.2AH, 35.2AH, 52.1AH and other possible susceptibility AHs cannot be disregarded.
When considering a disease susceptibility allele unique to a haplotype, it is possible that
such an allele may only exist within a ‗sub-haplotype‘ of the known susceptibility
haplotype. The rs9268642 allele carried exclusively by the COX cell line is an example
of a SNP that suggests the existence of sub-haplotypes of the 8.1AH, which is also
strengthened by the observations in this study of HLA-homozygous samples with
heterozygous results for the alleles rs2050189 and rs3117099. The existence of sub-
haplotypes is an important consideration for future research into sIBM and other MHC-
associated diseases. It is difficult to determine whether the sub-haplotypes carried by the
available 10IHW cell lines carry the allele that confer susceptibility to the studied
disease, given that there is no indication as to whether donors who provided the
workshop cell lines suffered from specific autoimmune diseases. Therefore emphasis
must be placed on the importance of eventually using sIBM patient samples, through
direct sequencing or genotyping, to verify the role of an allele in conferring sIBM
susceptibility.
6.4.7 NOTCH4
Seven of the 32 8.1AH alleles tested against multiple susceptibility haplotypes were
within NOTCH4, of which three were also found either in the 7.2AH, 35.2AH or
52.1AH. Four of the coding region polymorphisms in NOTCH4 – rs422951, rs915894,
rs443198 and rs9281675, were investigated in more detail in Chapter 4.
129
The presence of the minor allele for rs422951 but not rs915894 or rs443198 in the sIBM
associated 7.2AH and 35.2AH (Table 6.2) may account for why only rs442951
registered a statistically significant increase in allele frequency in both the Australian
and American patient cohorts (Table 4.4), given that an allele carried by multiple
susceptibility haplotypes is more likely to show a statistically significant increase in
sIBM patients. By contrast, the minor alleles for rs915894 and rs443198 were carried by
one sIBM associated haplotype in Caucasians (the 52.1AH is not increased in
Caucasians) thus reducing the likelihood of showing a statistically significant increase
in allele frequency.
NOTCH4 itself has been the focus of several studies (Sugaya et al., 1994; Uyttendaele et
al., 1996; Sugaya et al., 1997; Li et al., 1998; Coowar et al., 2004; Vercauteren and
Sutherland, 2004), although its exact function is unknown. The current research, as well
as the known function of other genes in the NOTCH gene family (Artavanis-Tsakonas et
al., 1999; Kadesch, 2004), suggest a role in cellular differentiation, such as the
development of neurons and lymphoid tissue (Coowar et al., 2004; Vercauteren and
Sutherland, 2004). The NOTCH4 alleles studied in this chapter did not appear to be
candidates for conferring sIBM susceptibility by a common allele between susceptibility
haplotypes.
6.4.8 Conclusion
This study sought to test the hypotheses that sIBM susceptibility was conferred by an
allele common to multiple sIBM susceptibility haplotypes. A common susceptibility
allele was supported by the presence of rs2050189 on the 8.1AH, 7.2AH and 52.1AH.
However genotyping revealed that the occurrence of this allele was inconsistent in
patients with these haplotypes, thus compromising its potential as an sIBM
susceptibility allele. These results thus favour the alternative hypothesis of the 8.1AH
conferring susceptibility independently of the other sIBM-associated haplotypes.
The possibility of a common susceptibility allele outside of gene promoter or exonic
regions between the 8.1AH and other susceptibility haplotypes remains to be
investigated. The presence of a common susceptibility allele between the 52.1AH,
7.2AH and/or 35.2AH also warrants further investigation. This could be achieved
through either fine mapping of alleles across the entire MHC region, or recombination
130
mapping to define a common susceptibility region as done previously with the 8.1AH
(Kok et al., 1999; Price et al., 2004). In any case, the existence of a susceptibility allele
common to multiple sIBM-associated haplotypes remains a viable hypothesis.
The next possible approach is to investigate sIBM susceptibility in each haplotype
independently. Recombination mapping has shown some success in defining
susceptibility for the 8.1AH to part of the MHC (Kok et al., 1999; Price et al., 2004).
sIBM susceptibility for the 8.1AH could be further defined using this approach. This
would allow the selection of possible sIBM-associated genes and alleles to be further
restricted.
131
CHAPTER SEVEN
7 IDENTIFICATION AND CHARACTERISATION OF MHC POLYMORPHISMS FOR RECOMBINATION MAPPING
132
7.1 Abstract
Polymorphic markers were identified that could be used for recombination mapping of
the 8.1AH within sIBM patients. Polymorphisms found in a cell line carrying the 8.1AH
were selected from sequence data detailing the region from RNF5 to HLA-DRA. These
polymorphisms were then characterised in 26 10IHW cell lines. Markers capable of
distinguishing the sIBM-associated haplotypes were identified, and a subset prioritised
for use in recombination mapping.
7.2 Introduction
Strong linkage disequilibrium within the MHC is a major hurdle to the proof of
individual genetic variants as disease-susceptibility loci. Traditional association studies
within the MHC are only effective in narrowing disease association to a broad region,
usually in linkage disequilibrium with the regularly studied HLA alleles. Similarly,
comparing the relative risks associated with multiple alleles will only succeed in
determining their specificity to the respective disease-associated haplotype, rather than
to the disease itself. An allele playing a direct role in a disease is thus very difficult to
differentiate from any co-inherited allele.
One approach to identifying alleles for disease susceptibility is recombination mapping
(Kok et al., 1999; Cheong et al., 2001; Broeckel and Schork, 2004; Price et al., 2004),
also known as positional cloning (Collins, 1995). Recombination mapping uses markers
across multiple chromosomes within a single family or pedigree to isolate alleles on the
genome that are co-inherited with a specific trait or disease (Collins, 1995; Broeckel and
Schork, 2004). Recombination during meiosis ensures that not all of the alleles typed
will be common to individuals affected by the disease. Alleles common to all
individuals in a family with the disease are thus likely to be co-inherited with a nearby
genetic susceptibility allele (Broeckel and Schork, 2004). Candidate genes within the
identified susceptibility region can then be assessed by other methods, such as
sequencing, to determine any possible role in the disease (Collins, 1995).
The primary region of interest for sIBM susceptibility, the MHC, is relatively minute
compared to a human chromosome, at 7.6Mb long (Horton et al., 2004), and consists of
multiple conserved polymorphic blocks (Yunis et al., 2003). Together, these reduce the
frequency of recombination events between generations that would subdivide the MHC.
133
Utilising recombination mapping on fIBM patients is thus impractical, due to both rarity
of recombination events within the MHC and the low incidence of familial sIBM
(Naumann et al., 1996; Sivakumar et al., 1997; Amato and Shebert, 1998; Hengstmann
et al., 2000; Tateyama et al., 2003; Ranque-Francois et al., 2005; Mastaglia et al.).
It is therefore necessary that sIBM patients with historical, rather than generational
recombination events are used to define fragmented disease susceptibility haplotypes
within the MHC. For instance, all individuals carrying the sIBM-associated 8.1AH
would have inherited that haplotype through a common, albeit distant, lineage.
Historical recombination events over time result in fragmented regions of the 8.1AH in
some patients, allowing a susceptibility region to be defined by identifying regions of
the disease-associated haplotype common to patients with the disease. By comparing
fragments of the same susceptibility haplotype between patients, a common,
overlapping susceptibility region can be identified.
Past studies have used this approach of small scale recombination mapping to suggest a
genetic susceptibility region for sporadic inclusion body myositis (Kok et al., 1999;
Price et al., 2004), and the same technique was used for mapping susceptibility to Type
I Diabetes Mellitus to the TNF region (Cheong et al., 2001). In order to be able to
reliably define a disease-susceptibility region, effective recombination mapping requires
well characterised polymorphic markers specific to the disease-associated haplotype is
of interest.
A source of alleles completely characterised against a large number of haplotypes, as
would be required for recombination mapping, is not available. Databases such as
dbSNP (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp) are useful in
identifying polymorphisms and showing representative population frequencies, but do
not address haplotypic structure. While several studies involving large-scale sequencing
of MHC haplotypes and alleles have been published, they have generally focussed on
identifying the evolutionary origins of HLA haplotypes and patterns of linkage
disequilibrium (Smith et al., 2006; Traherne et al., 2006b), rather than providing well
characterised markers that might be used in recombination mapping. Work by de
Bakker et al. provides an excellent reference for capturing specific HLA alleles with
between one and three tag SNPs (single nucleotide polymorphisms) (de Bakker et al.,
134
2006), but the focus on identifying HLA alleles limits its use in recombination mapping,
particularly when regions not containing HLA genes are investigated.
Hence, this study sought to identify and characterise markers that may prove useful in
recombination mapping studies involving the 8.1AH and the 7.2AH or 35.2AH,
particularly for the purpose of defining a common sIBM susceptibility region. In order
to achieve this, alleles were genotyped against a selection of cell lines carrying well
defined AHs. Conserved AHs account for 73% of the MHC genetic diversity of a given
Caucasian population (Degli-Esposti et al., 1992). Their strong genetic conservation
between individuals carrying the same haplotype makes them an ideal tool both for
defining disease associations and by extension, characterising markers for use in
recombination mapping.
Despite conferring susceptibility to sIBM in the Japanese, alleles specific to the 52.1AH
were not considered in this study as no patients carried only part of the 52.1AH, which
is necessary for recombination mapping.
Most of the markers were selected on the basis of the rare allele being carried by the
sIBM-associated 8.1AH. The 8.1AH was chosen due to the availability of detailed
sequence data through the Sanger Institute MHC Haplotype Project
(http://www.sanger.ac.uk/HGP/Chr6/MHC/ Accessed 5/11/2007) (Allcock et al., 2002;
Stewart et al., 2004; Traherne et al., 2006b). Detailed sequence data was not available
for the 7.2AH or 35.2AH, so candidate alleles for recombination mapping were instead
located from past literature and existing sequence data obtained from the amplification
of other alleles.
135
7.3 Results
7.3.1 Selection of alleles
Thirty polymorphisms were initially selected from across the investigated region from
RNF5 to HLA-DRA and detailed in Chapter 3. Polymorphisms included both intra-genic
and inter-genic loci at which the allele for COX (8.1AH) was different to that found in
QBL (18.2AH), SSTO (44.1AH) and PGF (7.1AH). These included the 16 loci already
genotyped as part of Chapter 6 (Table 6.3). A co-inherited series of five polymorphisms
on BTNL2, dubbed BTNL2*E6 and originally identified by Stammers et al. (2000),
were included on the basis of their presence on the sIBM-associated 7.2AH and
35.2AH. Five other loci, haplotypic of the 7.2AH and 35.2AH were located within the
amplicons used to sequence the markers selected for the 8.1AH, and so were also
included for further study. A total of 40 loci were included in this study, the details of
which are shown in Table 7.1.
7.3.2 Characterisation of alleles
The selected loci were genotyped in 26 10IHW cell lines, as described in Sections 2.2.5
– 2.2.7. PCR products totalling 2.1kb were sequenced from each of the 10IHW cell lines
(Table 7.2). The sequence data generated allowed the categorisation of a previously
undefined novel SNP haplotypic of the 35.2AH (Figure 7.1). The polymorphism was
labelled T(-790)A and is a T/A SNP that occurs in the promoter region of HLA-DRA
(Table 7.1). The existence of four previously identified SNPs was also confirmed,
where the minor allele was found on the 35.2AH (rs367398, rs6913309, rs6913471,
rs17202155) and all of which were genotyped in the 26 10IHW cell lines.
Of the alleles genotyped, only rs926593 and rs3117109 were haplospecific to the 8.1
AH, being found in the homozygous 8.1 cell line COX and the heterozygous 8.1AH cell
line ‗MAD,MF‘ only. The minor allele of rs9268642 was found in the COX cell line but
not any other cell lines, including the heterozygous 8.1AH cell line ‗MAD,MF‘ (Table
7.2). The population frequency reported in dbSNP for rs9268642 is 0.000, meaning that
it was found in none of the 116 individuals comprising the representative Caucasian
population (Table 7.1). Given that the frequency of the 8.1AH is approximately 10% in
Caucasian populations, this suggests that rs9268642 could be unique to the COX cell
line or a specific subset of the 8.1AH, rather than the 8.1AH as a whole.
136
8.1AH
35.2AH
Figure 6.2: Chromatograms for the 10IHW cell lines COX (8.1AH) and WT100BIS
(35.2AH). The polymorphism T(-790)A is marked at position 40.
T(-790)A
Figure 7.1: Chromatograms for the 10IHW cell lines COX (8.1AH) and WT100BIS (35.2AH). The polymorphism T(-790)A is marked at position 40.
rs no.Associated
Gene
Position Relative
to Gene a
Nucleotide
Change
Population
Frequency b
Amino Acid
Change
rs176095 PBX2 promoter -356 T > C 0.183 -
rs204989 GPSM3 intron C > T 0.133 -
rs422951 NOTCH4 coding A > G 0.367 T-->A
rs915894 NOTCH4 coding A > C 0.310 K-->Q
rs443198 NOTCH4 coding T > C 0.292 G-->G
rs9281675c
NOTCH4 coding 6-12 CTG - 6L-->12L
rs367398 NOTCH4 5' UTR -25 G > A - -
rs693797 - NOTCH4 - C6orf10 A > G 0.308 -
rs9268117 - NOTCH4 - C6orf10 G > C - -
rs926593 C6orf10 intron T > C - -
rs2050189 C6orf10 5' UTR -164 A > G 0.175 -
rs6913309 C6orf10 5' UTR -357 T > A 0.242 -
rs6913471 C6orf10 5' UTR -442 T > A 0.365 -
rs17202155 C6orf10 5' UTR -505 C > T 0.043 -
rs3117110 C6orf12 promoter -523 G > A - -
rs3117109 C6orf10 promoter -1218 G > A - -
rs3129944 C6orf10 promoter -1219 C > G 0.142 -
rs3129950 HCG23 promoter -86 G > C 0.092 -
rs3117099 HCG23 promoter -17 C > T 0.129 -
BTNL2-1d BTNL2 coding C > T - H-->H
BTNL2-2d BTNL2 coding A > C - S-->S
rs28362676d
BTNL2 coding CA > AG - P-->Q
BTNL2-3d BTNL2 coding G > A - M-->I
rs28362678d
BTNL2 coding C > T - P-->L
rs3129959 BTLN2 intron A > T 0.108 -
rs2213580 - BTNL2 - HLA-DRA A > G 0.116 -
rs3135366 - BTNL2 - HLA-DRA A > G 0.125 -
rs9268632 HLA-DRA promoter -1269 C > G - -
rs9268636 HLA-DRA promoter -1070 C > A - -
rs9357142 HLA-DRA promoter -793 G > A - -
T(-790)Ae
HLA-DRA promoter -790 T > A - -
rs9268641 HLA-DRA promoter -777 C > T 0.227 -
rs9268642 HLA-DRA promoter -566 C > T 0.000 -
rs3129872 HLA-DRA promoter -511 A > T 0.233 -
rs2395179 HLA-DRA promoter -362 A > G 0.241 -
rs2395180 HLA-DRA promoter -354 T > G 0.241 -
rs2395181 HLA-DRA promoter -260 G > C 0.233 -
rs3129873 HLA-DRA promoter -231 G > C - -
rs3129874 HLA-DRA promoter -224 T > C - -
rs3129875 HLA-DRA promoter -196 T > C 0.204 -
d - The five BTNL2 coding polymorphisms are inherited as a single 'complex polymorphism'
dubbed BTNL2*E6 by Stammers et al. (2000).
e - A novel polymorphism defined by the current study. There is no rs number assigned by
dbSNP.
Table 7.1: SNPs and microsatellites chosen for characterisation.
a - Distance in bp either upstream of the first exon (for promotor polymorphisms), or
upstream of the start codon (negative value - for 5' UTR polymorphisms).
b - The population frequency is of the minor (second) allele listed under 'Nucleotide change'
is from dbSNP (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp), with the "CEU"
population used as a reference. CEU is a Caucasian population consisting of more than 100
Utah residents with ancestry from northern and western Europe.
c - Also referred to as rs28359855, with a different repeat number. dbSNP lists rs9281675 in
the 3'-5' orientation, as a CAG repeat.
Table 7.2: Haplotypic distribution of 40 selected polymorphisms from telomeric of RNF5 to HLA-DRA in 26 10IHW cell lines.
10IWS no. 9013 9131 9022 9046 9008 9020 9042 9006 9136 9026 9021 9302 9050 9053 9076 9066 9047 9142 9141 9133 9156 9098 9059 9031 9060 9079
Name SCHU KUROIWA COX BH DO208915 QBL TISI WT100BIS SPE, G YAR RSH SSTO MOU HOR T7526 TAB089 PLH HARA HOKKAIDO MAD, MF WON, PY MT14B SLE005 BOLETH CB6B LWAGS
Zygositya
- - Con - - Con Con Con Het Hom - Hom Con - Het - Con Hom Hom Het Hom Con - Con Con Hom
AH 7.1 7.2 8.1 13.1 18.1 18.2 35.1 35.2 18.2/35.3 38.1 42.1 44.1 44.2 44.4 46.1 46.2 47.1 52.1 54.1 57.1/8.1 58.1 60.1 60.3 62.1 62.3 65.1
HLA Ab 0301 24 0101 0201 2501 2601 2402 1101 1101:3002 2601 3001:6802 3201 2902 3303 0206:0207 0207:0201 0301 24 24 1:3 33 3101 0201 0201 0101 3301
HLA Cw 0702 7 0701 0602 1203 0501 0401 0401 4:5 1203 1701 0501 1601 1403 0102:0801 0102 0602 1 3 0304 0304 0304 0303 0802
HLA B 0702 7 0801 1302 1801 1801 3508 3501 18:35 3801 4201 4402 4403 4403 4601 4601 4701 52 54 8:57 58 4001 4001 1501 1501 1402
TNFab a11b4 a2b3 a10b4 a5b5 a2b1 a2b1:a1b5 a10b4 a6b5 a8b4 a6b5 a6b5 a6b5 a10b4 a13b4 a11b4 a2b3:a2b5 a2b3 a11b4 a2b1 a6b5 a2b1
rs176095 T T Cc
C T T T T T T T T C T T C T T C C T T T T T T
rs204989 C C T T C C C C C C C C T C C T C C T C:T C C C C C C
rs422951 A G G G A A G G G:A G A A A G A A A A A G A A A G A A
rs915894 A A C C A A A A A A A A C C C A A C C C A A A C A C
rs443198 T T C C T T T T T T T T C C C T C C C C T T T T T C
rs9281675d
10r 6r 12r 13r 9r 10r 11r 6r 6r:10r 6r 9r 10r 9r 9r 9r 11r 12r 10r 10r 9r:12r 10r 10r 10r 10r 10r 6r
rs367398 G A G G A G G A A:G A A G A A G G G G A A:G G G G G G G
rs693797 A G G G A A G G G:A G A A G A A A G A A G:A G A G A A A
rs9268117 G G C G G G G G G G C G G C G C G G G C G G G G G G
rs926593 T T C T T T T T T T T T T T T T T T T T:C T T T T T T
rs2050189 A G G A A A G A A A A A A A A:G A G G A A:G A A A A A A
rs6913309 T A T A T T T A A:T A T T A A T T A T T A:T A T T T T T
rs6913471 T A T A T T T A A:T A T A A T T T A T T A:T A A T T A T
rs17202155 C T C C C C C T C:T C C C C C C C C C C C C C C C C C
rs3117110 G G A G G G G G G G A G G A G A G G G A:G G G A G G A
rs3117109 G G A G G G G G G G G G G G G G G G G G:A G G G G G G
rs3129944 C C G C C C C C C C G C C G C G C G G C:G C C G C C G
rs3129950 G G C G G G G G G G G G G G G G G G G G:C G G G G G G
rs3117099 C C T C C C C C C C T C C C C T C T T T:C C C C:T C C T
BTNL2-1e
C T C C C C C T C:T C C C C C C C C T T C C C C C C C
BTNL2-2e
A C A A A A A C A:C A A A A A A A A C C A A A A A A A
rs28362676e
CA AG CA CA CA CA CA AG CA:AG CA CA CA CA CA CA CA CA AG AG CA CA CA CA CA CA CA
BTNL2-3e
G A G G G G G A G:A G G G G G G G G A A G G G G G G G
rs28362678e
C T C C C C C T C:T C C C C C C C C T T C C C C C C C
rs3129959 A A T A A A A A A A A A A A A A A A A A:T A A T A A A
rs2213580 A A G A A A A A A A A A A A A A A A A G:A A A G A A A
rs3135366 A A G A A A A A A A A A A A A A A A A G:A A A G A A A
rs9268632 C C G C C C C G C:G C C C C G C C G C C C:G C C G C C C
rs9268636 C C A C C C C C C C C C C A C C C C C A:C C C A C C C
rs9357142 G A A G G G G A G G G G G A G G A G G G G G A G G G
T(-790)Af
T A T T T T T A T T T T T T T T A T T T T T T T T T
rs9268641 C T T C C C C T C:T C C C C T C C T C C C:T C C T C C C
rs9268642 C C T C C C C C C C C C C C C C C C C C C C C C C C
rs3129872 A T T A A A A T A:T A A A A T A A T A A A:T A A T A A A
rs2395179 A G G A A A A G A:G A G A A G A G G A A A:G A A G A A A
rs2395180 T G G T T T T G T:G T G T T G T G G T T T:G T T G T T T
rs2395181 G C C G G G G C G:C G C G G C G C C G G G:C G G C G G G
rs3129873 G C C G G G G C G:C G G G G C G G C G G G:C G G C G G G
rs3129874 T C C T T T T C C:T T T T T C T T C T T C:T T T C T T T
rs3129875 T C C T T T T C C:T T C T T C T C C T T C:T T T C T T T
HLA-DRB1* 1501 0101 0301 0701 1501 0301 1103 0101 0101:0301 0402 0302 0403 0701 1302 0901 0803 0701 1502 0405 0301:07 0301 0404 1302 0401 1301 0102
HLA-DQA1* 0102 0101 0501 0201 0102 0501 0505 0101 0101:0501 0301 0401 03 0201 0102 0302 0103 0201 0103 03 0201:0501 0501 03 0102 0301 0103 0101
HLA-DQB1* 602 0501 0201 0202 0602:0603 0201 0301 0501 0201:0501 0302 0402 201 0604 0303 0601 0202 0601 0401 0201:0303 0201 0302 0302 0603 0501
HLA-DPB1* 0402 0401:0402 0301 0401:1701 0201:2301 0202 0402 0101 0202:0401 0401 0101:0402 0401 0201 0401 1301 0202 1501 0901 0501 0301:0401 0401 0402 0301 0401 1901 0301:0401
a - For cell line zygosity, Con = Consanguineous; Het = Heterozygous, Hom = Homozygous.
b - Typing data for the HLA alleles and TNFab for each cell line originated from the IMGT/HLA database (http://www.ebi.ac.uk/imgt/hla/) and was supplemented by Cattley (2000) when data was not otherwise available.
c - Shaded alleles are the minor (less common) alleles.
d - rs9281675 lists the number of CTG repeats (r) in each cell line.
e - The five polymorphisms are inherited as a single 'complex polymorphism' dubbed BTNL2*E6 by Stammers et al. (2000). Part results are unpublished data from Price et al., 2004.
f - T(-790)A has no rs number assigned by dbSNP
139
The minor alleles for rs3129959, rs2213580 and rs3135366 were common only to the
8.1AH and 60.3AH, and the 12 repeat allele for the microsatellite rs9281675 was common
only to the 8.1AH and 47.1AH. rs9281675 could also differentiate the 13.1AH from other
AHs by the presence of the 13 repeat allele. The alleles comprising BTNL2*E6 ‗complex
polymorphism‘ (BTNL2-1, BTNL2-2, rs28362676, BTNL2-3 and rs28362678) were all
inherited en bloc, either carrying all the minor alleles (7.2AH, 35.2AH, 18.2AH/35.3AH,
52.1AH, 54.1AH), or none of the minor alleles. The minor alleles for rs17202155, T(-
790)A and the BTNL2*E6 complex polymorphism were able to differentiate the 7.2AH
and 35.2AH from most haplotypes (Table 7.2).
The 8.1AH and 60.3AH appear almost identical from the markers rs3129959 to rs3129875,
which spans 32kb (Table 7.2). The observed correlation suggests a common ancestry
between the two haplotypes in this region.
Anomalies were found in several cell lines. Specifically, the 10IHW cell lines T7526 and
SLE005, which appeared homozygous around the investigated region, gave heterozygous
results for rs2050189 and rs3117099 respectively. Furthermore, the 10IHW cell line ‗MAD,
MF‘, which is heterozygous for the 8.1AH, was homozygous for the major, non-8.1AH
allele at rs9357142 (Table 7.2). These discrepancies suggest that a given AH will not be
completely identical in all individuals carrying that haplotype.
140
7.4 Discussion
7.4.1 Summary
A total of 40 alleles were characterised, of which several could specifically identify the
8.1AH within a 270kb region of the MHC. Two markers were unique to the 8.1AH
(rs926593 and rs3117109) and a further four were specific to the 8.1AH and one other
haplotype (rs3129959, rs2213580, rs3135366, rs9281675). Markers were also defined that
show strong specificity to other haplotypes, in particular the 35.2AH but also the 13.1AH,
47.1AH and 60.3AH.
The markers characterised here can be used in recombination mapping studies of the region
from RNF5 to HLA-DRA and in particular for refining the region for susceptibility to sIBM
on the 8.1AH. Several markers were also defined that are capable of identifying the 7.2AH
or 35.2AH within this region. However only two markers, rs2050189 and rs9268632 were
capable of differentiating the 7.2AH from the 35.2AH, which suggests that the two
haplotypes are highly similar across this region. If sIBM susceptibility is conferred by only
one AH (rather than both, then the identification of more alleles capable of differentiating
the 7.2AH and 35.2AH would be essential for recombination mapping within this region.
7.4.2 Commonly inherited alleles
Several instances were observed where a group of alleles appeared to be inherited as a
single block across multiple haplotypes. The most apparent example of this were the alleles
that comprise BTNL2*E6 (BTNL2-1, BTNL2-2, rs28362676, BTNL2-3 and rs28362678).
The results of this chapter suggest that the minor alleles comprising the BTNL2*E6
polymorphism are always inherited together as a single block across all haplotypes
investigated, without exceptions. While the alleles that comprise BTNL2*E6 (BTNL2-1,
BTNL2-2, rs28362676, BTNL2-3 and rs28362678) had been reported previously
(Stammers et al., 2000; Price et al., 2004), the co-inheritance of the minor alleles as a single
block had been assumed, but not conclusively demonstrated (L. A. Santoso, Honours
Thesis 2001, unpublished results). Conversely other groups of minor alleles, such as those
in the HLA-DRA promoter region from rs9268632 to rs3129875, were inherited together as
a single block in most haplotypes investigated, although exceptions were noted where one
141
or more minor alleles were missing in a given AH. Groups of two or three minor alleles
were also commonly inherited across most AHs, such as rs915894 with rs443198 and
rs176095 with rs204989.
Given that the 8.1AH was the focus in selecting possible markers for characterisation,
comparisons can be made as to which AHs are more closely related to the 8.1AH in this
region via a common ancestor. Haplotypes that shared blocks of alleles with the 8.1AH in
this study are likely to have inherited that part of the MHC from a common ancestor. For
instance the 8.1AH and 60.3AH share a commonly inherited region from rs3129959 to
rs3129875, as do the 13.1AH and 8.1AH from rs176095 to around rs693797. Due to the
methodology used in initially identifying most of the alleles for this study, AHs that
showed very few alleles common to the 8.1AH are not necessarily distantly related to the
8.1AH. Such alleles may instead be closely related to the 7.1AH, 18.2AH and 44.1AH,
which were initially used to identify most of the markers characterised. Therefore AHs such
as the 18.1AH, 60.1AH and 62.3AH, which showed very few common alleles with the
8.1AH, may be more closely related to the 7.1AH, 18.2AH or 44.1AH than the 8.1AH.
7.4.3 Variations within and between defined haplotypes
The approach used for this study is based on the assumption that the cell lines utilised were
representative of their respective ancestral haplotypes. This approach has been followed by
numerous research groups and for the most part yields results applicable to haplotypes in
unrelated individuals – the regions defined by an ancestral haplotype exhibit a very high
level of conservation. Despite this, anomalies were found in some of the cell lines
investigated. In particular, heterozygous alleles were present in the T7526 (46.1AH) and
SLE005 (60.3AH) cell lines in the investigated region, which is otherwise homozygous for
the designated AH, and the minor allele for rs9268642 was seemingly unique to COX.
These results could suggest the existence of a small level of variation between individuals
carrying the same haplotype (determined by their HLA alleles. Smith et al. suggested that
these variations within an otherwise conserved haplotype could separate populations into
multiple ‗sub-haplotypes‘ (Smith et al., 2006), which is of particular importance for disease
association studies. In 19 chromosomes carrying the 8.1AH, Smith et al. identified 11 SNPs
142
that differentiated multiple examples of the 8.1AH in 393kb of sequence data amplified
between HLA-A and HLA-DQ. This translated to an average of 3.8 SNPs per pair of
chromosomes over the entire 2.6 Mb region from HLA-A to HLA-DQ (Smith et al., 2006).
A similar observation was also made when IKBL, a gene located further telomeric in the
MHC Class III region, was characterised against multiple 7.1AH cell lines (Allcock et al.,
1999). Not all cell lines carrying the 7.1AH possessed the +738C allele, which is otherwise
characteristic of this haplotype (R. Allcock, unpublished observations). The existence of
sub-haplotypes within a known disease susceptibility AH has considerable implications for
disease association studies. A common assumption of such studies involving AHs is that
the disease susceptibility allele is found in all individuals carrying the associated AH. If the
disease associated allele is specific to a sub-variation of the same AH, then isolating a
disease susceptibility allele is reliant on the ability to differentiate the disease-associated
sub-haplotype.
Smith et al. (2006) expressed some interest in investigating alleles that differentiate sub-
haplotypes of the 8.1AH to identify disease-susceptibility sub-haplotypes in type 1 diabetes
mellitus patients. The same approach could also be used for other MHC-associated diseases
like sIBM, where there has been limited success in isolating the precise MHC-associated
disease susceptibility alleles using more traditional methods. Throughout this thesis there
are two polymorphisms that may be able to differentiate an 8.1AH sub-haplotype; the COX
cell line-specific minor allele for rs9268642, and the rs2050189 minor allele identified in
Chapter 6, the latter of which has been refuted as an sIBM susceptibility allele. Through
recombination mapping, the markers characterised in this chapter can be used to reduce a
disease susceptibility region so that any polymorphisms specific to a sub-haplotype could
be more efficiently screened.
7.4.4 Conclusion
The results of this study provide a group of well defined markers that can be used in
recombination mapping within the region from AGER to HLA-DRA to define fragments of
not only the 8.1AH but also other haplotypes, including the possible sIBM-associated
7.2AH and 35.2AH. This study can also be used as a model for locating and characterising
other markers for use in mapping disease-associated regions within the MHC, in relation to
143
both the 8.1AH and other disease-associated AHs, so long as full sequence data is available
for such AHs.
144
CHAPTER EIGHT
8 RECOMBINATION MAPPING OF SIBM SUSCEPTIBILITY ON THE 8.1AH
145
8.1 Abstract
In this chapter the previously proposed sIBM susceptibility region within the 8.1AH was
refined to a smaller selection of genes through the use of recombination mapping.
Caucasian sIBM patients carrying part of the 8.1AH were genotyped for a selection of the
well defined 8.1AH haplotypic polymorphisms from Chapter 7. The results were used to
define the limits of the 8.1AH in each individual and identify the smallest common disease
susceptibility region between the sIBM patients. This refined region encompassed three
genes - HLA-DRB3, HLA-DRA and part of BTNL2.
8.2 Introduction
Strong linkage disequilibrium within the MHC complicates efforts in elucidating the cause
of the observed sIBM susceptibility. Alleles within a given AH are generally inherited
together, so differentiating the primary disease-associated allele from an allele co-inherited
with the disease association is difficult. One approach to isolate regions for sIBM
susceptibility that has shown some success is recombination mapping, as detailed in
Chapter 7.
Prior to this study, recombination mapping of the 8.1AH in sIBM-affected patients had
refined the source of the 8.1AH-derived sIBM susceptibility to near the border of the Class
II and III regions of the MHC, specifically between the coding genes PBX2 and HLA-DRB1
(Price et al., 2004). In total there are eight protein coding genes known within the proposed
8.1AH susceptibility region – PBX2, GPSM3, NOTCH4, C6orf10, HCG23, BTNL2, HLA-
DRA and HLA-DRB3. Disease associations have been proposed for several of these genes,
such as NOTCH4 with schizophrenia (Wei and Hemmings, 2000; Wang et al., 2006),
BTNL2 with sarcoidosis (Rybicki, 2005; Valentonyte et al., 2005), and HLA-DRB3 with
Graves disease (Chen et al., 1999; Chen et al., 2000) and sarcoidosis (Rossman et al.,
2003). No studies have thus far identified a direct association between sIBM susceptibility
and a specific gene within the susceptibility region.
For this reason, haplotypic markers for the 8.1AH in the previously identified susceptibility
region (Chapter 7) were used in recombination mapping to further define the 8.1AH-
146
derived sIBM susceptibility region. The patients used for this study were selected from
those in the combined Australian, American and German Caucasian cohorts who were
considered to carry part of the 8.1AH.
147
8.3 Results
8.3.1 Selection of Patients
Caucasian sIBM patients from the Australian, American and German cohorts (described in
Sections 2.1.1 – 2.1.3) were screened for individuals potentially recombinant for the
8.1AH. Of the combined pool of 156 patients, 73 carried alleles matching the full 8.1AH as
identified by HLA-B*0801, HLA-DRB1*0301 or serological HLA-B8, HLA-DR3, and 28
individuals carried either HLA-B*0801 (HLA-B8) or HLA-DRB1*0301 (HLA-DR3). Of
these 28 individuals, five also carried HLA-B*1801 (HLA-B18) with HLA-DRB1*0301,
which is suggestive of the 18.2AH (Cattley et al., 2000). Two individuals carried alleles
matching either the 7.2AH (HLA-B*0702, HLA-DRB1*0101 or serological HLA-B7, HLA-
DR1) or the 35.2AH (HLA-B*3501, HLA-DRB1*0101 or serological HLA-B35, HLA-
DR1), prohibiting their use in identifying patients with susceptibility conferred from a
partial 8.1AH. Eight patients were also eliminated for carrying either the full 8.1AH or
none of the 8.1AH across the entire suggested sIBM susceptibility region from PBX2 to
HLA-DRB1. This was concluded from past recombination mapping of these patients by
Price et al. (2004) and preliminary mapping of the German patient samples (results not
shown). Of the remaining 13 patients potentially recombinant for the 8.1AH, DNA was not
available from five, leaving eight individuals for further investigation. A summary of the
combined patient cohort is detailed in Figure 8.1.
148
7.2, 18.2, 35.2
no DNA
Eliminated by past typing
Rec mapped
Full 8.1
Not 8.1
Can't call:Full 8.1AH
73 (46.8%)
No 8.1AH
51 (32.7%)
Unable to Call
4 (2.6%)
7.2AH, 18.2AH
or 35.2AH
7 (4.5%)
Used for Mapping
8 (5.1%)
Full/no 8.1AH
within region
8 (5.1%)
No DNA
5 (3.2%)
Figure 7.1: Summary of the presence of full or partial 8.1AHs in 156 sIBM patients comprising the combined
Australian, American and German cohorts. The number of patients and their percentage of the whole is given
for each category.
Either HLA-B8
or HLA-DR3
28 (17.9%)
Figure 8.1: Summary of full or partial 8.1AHs in 156 sIBM patients comprising the combined Australian, American and German cohorts.
The number of patients and their percentage of the whole is given for each category.
149
8.3.2 Selection of polymorphic markers for recombination mapping
The major (common) allele of a given SNP will generally be found in most haplotypes and
so cannot be reliably used to confirm the presence of a specific AH. Therefore the possible
recombinant 8.1AH sIBM patients were examined for twelve markers characterised in
Chapter 7, where a minor allele was haplotypic of the 8.1AH (rs176095, rs204989,
rs422951, rs9281675, rs693797, rs9268117, rs926593, rs3117109, rs3129944, rs3129959,
rs2213580, rs3135366). After initial patient genotyping, these markers were supplemented
with a further two SNPs (rs1800625 and rs3117103) and four microsatellites (rs9279509,
rs9279556, rs5875354 and rs9279614), which were chosen to reinforce the results of the
existing markers.
The new markers were genotyped in twelve 10IHW cell lines to determine if their minor
(rare) allele was specific to or haplotypic of the 8.1AH and hence if they were suitable for
recombination mapping (Table 8.1). Of the markers genotyped in this chapter, the only
8.1AH minor alleles found in other AHs were for the markers rs1800625 and rs9279509.
The minor (C) allele for rs1800625 was found in three other haplotypes (13.1AH, 54.1AH
and 57.1AH) and the 10r minor allele for rs9279509 was also found on the 13.1AH cell line
sample (Table 8.1).
These 18 polymorphic markers, along with HLA-DRB3 genotyping, were selected for use in
recombination mapping. All of the markers were capable of differentiating the 8.1AH from
other haplotypes, although the majority were not specific to the 8.1AH, being found on a
number of other AHs.
AH10IHW
no.
HL
A-B
b
rs18
00
62
5
C (0
.17
0)
rs17
60
95
G (0
.18
3)
rs20
49
89
A (0
.13
3)
rs92
79
50
9
AT
AA
r c
rs42
29
51
G (0
.36
7)
rs92
81
67
5
CT
Gr
rs69
37
97
C (0
.30
8)
rs92
68
11
7
C
rs92
79
55
6
AT
TT
r
rs58
75
35
4
AT
Mr
rs92
65
93
C
rs31
17
10
9
T
rs31
29
94
4
G (0
.14
2)
rs92
79
61
4
GT
r
rs31
17
10
3
A (0
.09
2)
rs31
29
95
9
T (0
.10
8)
rs22
13
58
0
G (0
.11
6)
rs31
35
36
6
C (0
.12
5)
HL
A-D
RB
3*
b
HL
A-D
R*
b
7.1 9318d
0702 T A G 12r A 10r T G 7r 12r T C C 22r T A A A - 1501
8.1 9022d
0801 C G A 10r G 12r C C 5r 14r C T G 14r A T G G 0101 0301
8.1 9132 8 C G A 10r G 12r C C 5r 14r C T G 14r A T NDe
ND 0101 0301
13.1 9046 1302 C G A 10r G 13r C G 7r 12r T C C 22r T A A A - 0701
18.2 9020d
1801 T A G 11r A 10r T G 7r 10r T C C 21r T A A A 0202 0301
18.2 9018 1801 T A G 11r A 10r T G 7r 10r ND ND ND 21r T ND ND ND 0202 0301
44.1 9302d
4402 T A G 11r A 10r T G 7r 16r T C C 21r T A A A - 0403
44.2 9050d
4403 T G A 12r A 9r C G 7r 12r T C C 17r T A A A - 0701
44.4 9053 4403 T A G 11r G 9r T C 7r 12r T C G 15r T A A A 0301 1302
52.1 9142 5201 T A G 11r A 10r T G 7r 9r T C G 20r T A A A - 1502
54.1 9141 54 C G A 12r A 10r T G 7r 13r T C G 22r T A A A - 0405
57.1 9052d
5701 C G G 8r G 9r T C 7r 15r T C C 21r T A A A - 0701
58.1 9157 5801 T A G 11r A 10r C G 7r 12r T C C 18r T A A A 02 0301
62.1 9091d
1501 T A ND 12r ND ND T ND 7r 13r T C C 21r T A T T - 0401
b - All HLA typing was derived from Cattley et al. (2000).
c - Microsatellites are marked with an 'r' after the repeat unit.
Table 8.1: Characterisation of markers in 10IHW cell lines carrying defined AHs. Alleles common to the 8.1AH are shaded. The markers used are
given with their minor allele and if available, their frequency in an unaffected Caucasian populationa. The markers listed in red are those previously
genotyped in Chapter 7 (Table 7.2).
a - The population frequency of the minor allele is from dbSNP (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp), with the "CEU" population
used as first preference. CEU is a Caucasian population consisting of more than 100 Utah residents with ancestry from northern and western Europe.
d - Genotyping for the 10IWS cell lines 9318, 9022, 9020, 9302, 9052 and part results from 9050 and 9091 were derived from raw sequence data made
available through the Sanger Institute MHC Haplotype Project (http://www.sanger.ac.uk/HGP/Chr6/MHC/).
e - ND = Not determined/unable to determine. All of the undetermined alleles can be predicted from the cell lines genotyped in Table 6.2 using
different cell lines carrying the same AH.
151
8.3.3 Patient Genotyping
The selected markers were genotyped in the eight patients selected for this study (Table
8.2). Alleles for HLA-DRB3 could not be determined in Patient AU_4, although all other
genotyping was successful. The presence of any partial or full 8.1AHs, as well as other
AHs within the investigated region, was determined using the presence of minor alleles for
each AH from Table 8.1.
Contiguous groupings of 8.1AH alleles were used to define the limits of the 8.1AH region
(Figure 8.2). Three of the eight patients tested (AU_1, AU_14, GR_1) carried only part of
the 8.1 AH in the region between PBX2 and HLA-DRB1 (Table 8.2). AU_4 and AU_76
carried the 8.1AH across the entire region investigated, although the absence of HLA-
B*0801 in both individuals suggests a recombination break-point between PBX2 and HLA-
B, which is a region that spans more than 500kb. AU_41, AU_46 and AU_53 carried no
contiguous groupings of 8.1AH alleles and were concluded to carry either the 18.2AH or
58.1AH, based on the presence of minor alleles haplotypic of these AHs (Table 8.2).
In total, five of the eight patients genotyped defined a common overlapping 8.1AH region
from centromeric of rs3129959 to telomeric of HLA-DRB1. The allele rs3129959 lies in the
intron between exons 1 and 2 of BTNL2. The common 8.1AH region is thus a 172kb region
encompassing exon 1 and the promoter region of BTNL2, as well as the entirety of HLA-
DRA and HLA-DRB3 (Figure 8.2).
The 14r allele for the microsatellite rs5875354, despite appearing to be specific for the
8.1AH, was found in several patients who did not otherwise appear to carry the 8.1AH
within that region. It is likely that the 14r allele at rs5875354 is not specific to the 8.1AH,
but is also found on another haplotype not defined in Table 8.1.
AHs within
region c
AU_1 p8.1 and 18.2 18 27 T T T T C C 11r 11r A A 10r 14r A A G G 7r 7r 14r 10r T T G G C C 21r 21r T T A A G A G A 01010210 3 3
AU_4 8.1 and p60.3 40 40 C T C T T C 10r 11r G A 12r 9r G A C C 5r 7r 14r 15r C T A G G C 14r 26r A T T A G G G G 3 13
AU_14 p8.1 7 51 T T T T C C 12r 12r G A 9r 10r G A G G 7r 7r 12r 12r T T A G G C 14r 17r A T T A G A G A 0101 - 3 7
AU_41 p18.2 or p58.1 3901 1501 T T T T C C 11r 11r A A 9r 9r A A G G 7r 7r 13r 15r T T G G G C 13r 22r T T A A A A A A 0202 - 03 16
AU_46 18.2 and p44.2 5101 5101 T T T T C C 11r 12r G A 9r 10r G A G G 7r 7r 10r 12r T T G G C C 17r 21r T T A A A A A A 0202 - 03010701
AU_76 8.1 3501 4501 C T C T T C 10r 12r G A 12r 10r G A C G 5r 7r 14r 14r C T A G G C 14r 21r A T T A G A G A 0101020203011301
AU_53 18.2 07 51 T T T T C C 11r 12r A A 10r 10r G A G G 7r 7r 14r 12r T T G G C C 18r 21r T T A A A A A A 0201020203011301
GR_1b
p8.1 35 35 T T T T C C 11r 11r A A 10r 10r A A G G 7r 7r 14r 11r T T A G G C 14r 19r A T T A G A G A 0101 - 03 04
b - GR_1 is an sIBM patient genotyped from the Germany cohort.
c - Partial AHs from RNF5 to HLA-DRB1 are noted with a 'p'.
e - Microsattelites are marked with an 'r' after the repeat unit.
d - Serological typing results (1-2 digit numbers) were only used for HLA-B and HLA-DRB1 where sequence-based typing was
unavailable.
rs3
11
71
03
A (0
.09
2)
rs3
12
99
59
T (0
.10
8)
rs9
27
95
56
AT
TT
r
rs5
87
53
54
AT
Mr
rs3
11
71
09
A
rs3
12
99
44
G (0
.14
2)
rs9
27
96
14
GT
r
rs9
27
95
09
e
AT
AA
r
rs4
22
95
1
G (0
.36
7)
a - The population frequency of the minor allele is from dbSNP (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp), with the
"CEU" population used as a reference. CEU is a Caucasian population consisting of more than 100 Utah residents with ancestry from
northern and western Europe.
HL
A-
DR
B1
* c
Table 8.2: Fine mapping of candidate sIBM patients for carriage of the 8.1AH between PBX2 and HLA-DRB3 . Alleles potentially
belonging to the 8.1AH were shaded and minor alleles known to be carried by another AH were marked in red. The markers used are
given with their minor allele and if available, their frequency in an unaffected Caucasian populationa.
HL
A-B
* d
rs1
80
06
25
C (0
.17
0)
rs1
76
09
5
C (0
.18
3)
rs2
04
98
9
T (0
.13
3)
rs9
28
16
75
CT
Gr
rs6
93
79
7
G (0
.30
8)
rs9
26
81
17
C
rs9
26
59
3
C
rs2
21
35
80
G (0
.11
6)
rs3
13
53
66
C (0
.12
5)
HL
A-
DR
B3
*
153
AGER
PBX2GPSM3
NOTCH4 C6orf10 HCG23
BTNL2
HLA-DRA HLA-DRB3 HLA-DRB1
HLA-B
rs18
00
62
5
rs17
60
95
rs20
49
89
rs92
79
50
9
rs42
29
51
rs92
81
67
5
rs69
37
97
rs92
68
11
7
rs92
79
55
6
rs58
75
35
4
rs92
65
93
rs31
17
10
9
rs31
29
94
4
rs92
79
61
4
rs31
17
10
3
rs31
29
95
9
rs22
13
58
0rs3
13
53
66
Figure 7.2: The region spanning from BTNL2 to HLA-DRB3 is the most probable location for a genetic susceptibility allele affecting sIBM in
patients with the 8.1AH. Carriage of alleles identified as potentially or definitely belonging to the 8.1AH are marked by the filled diamonds ( ).
Open diamonds ( ) indicate adjacent alleles discordant with the 8.1AH and represent the boundary of the 8.1AH and thus the sIBM
susceptibility region. Predicted boundaries for the 8.1AH in each patient as well as the predicted susceptibility region is highlighted red.
AU38
AU_53
AU_41
AU_46
AU_1
AU_14
GR_1
Patient 9
AU_76
AU_4
Telo
mere
Cen
trom
ere
HL
A-D
RB
3
Figure 8.2: Recombination mapping of the region spanning from PBX2 to HLA-DRB1. Carriage of alleles identified as potentially or
definitely belonging to the 8.1AH are marked by the filled diamonds. Open diamonds indicate alleles discordant with the 8.1AH. Predicted
boundaries for the 8.1AH in each patient as well as the predicted susceptibility region is highlighted red.
154
8.4 Discussion
8.4.1 Summary
Two previous studies have used recombination mapping to refine the known sIBM
susceptibility region in the MHC first to between C4 and HLA-DRB1 (Kok et al., 1999)
and then to between PBX2 and HLA-DRB1 (Price et al., 2004). This study sought to
utilise recombination mapping to further refine the 8.1AH-derived sIBM susceptibility
region using a larger cohort and an increased, more completely defined set of markers.
The probable sIBM susceptibility region was redefined to a minimum suggested 172kb
region from BTNL2 to telomeric of HLA-DRB1, containing three coding genes; HLA-
DRB3, HLA-DRA and part of BTNL2.
The absence of part or all of the 8.1AH in some Caucasian sIBM patients (Figure 8.1,
Figure 8.2) indicates that the 8.1AH is neither necessary, nor sufficient to cause sIBM.
The 8.1AH should thus be considered to increase the risk of sIBM, rather than being a
required factor for disease pathogenesis. The implication of this for recombination
mapping is that any inference of susceptibility based on the absence of part of the
8.1AH should be viewed with some caution. It is possible that susceptibility in some of
the 8.1AH-recombinant patients was not conferred by the minimal region of the 8.1AH.
Thus the susceptibility region may extend further than defined in Figure 8.2. While the
region defined in this study is the most likely source of sIBM susceptibility as conferred
by the 8.1AH, genes outside of this region should not be disregarded completely.
8.4.2 Previous recombination mapping studies
A comparison of this present study with other recombination mapping studies is shown
in Table 8.3.
155
Table 8.3: Summary of the patients and markers used in previous recombination
mapping studies.
Study Disease Total patients
in cohort
Patients used
for mapping
Markers
useda
Kok et al. (1999) sIBM 18 18 3
Cheong et al. (2001) Type I
Diabetes 607 94 8
Price et al. (2004) sIBM 42 42 7
Camp et al. (2007) Prostate
cancer 1213 54 36
(This study) sIBM 156 8 19
a – Markers used do not include HLA-B or HLA-DR, which were previously known for all patients in
each study.
The largest studies in Table 8.3, published by Cheong et al. (2001) and Camp et al.
(2007), utilised many more patients or pedigrees (n= 607 and n=1213 respectively) than
this study and previous recombination mapping studies in sIBM. This is a reflection of
the much higher prevalence of these diseases compared to sIBM. Specifically, in
Caucasian populations the disease prevalence is at 0.2-0.4% for type 1 diabetes (Todd,
1990) and 0.2% for prostate cancer (SEER: http://seer.cancer.gov/csr/1975_2005/),
compared to 0.0013% for sIBM (Needham and Mastaglia, 2007). A cohort as large as
that used in Cheong et al. (2001) or Camp et al. (2007) would be ideal for
recombination mapping of sIBM susceptibility, although the rarity of sIBM makes it
very difficult to collect such a large cohort. Despite this, the cohort collected for this
present study is the largest cohort of sIBM patients assembled.
Although the sIBM patient cohort used in this study was more than three times the size
of those in Kok et al. (1999) or Price et al. (2004), only eight patients were appropriate
for recombination mapping compared to more than double that number for other sIBM
studies (Table 8.3). This is largely a result of the selection criteria used in each study to
choose patients for recombination mapping. Whereas Kok et al. (1999) and Price et al.
(2004) both simply genotyped all of the patients available for the chosen markers, the
study by Cheong et al. (2001) selected patients with part of the 8.1AH on the basis of
carriage of either HLA-B8 or HLA-DR3, but not both alleles.
156
The criteria used for this present study were far more stringent. Carriage of either HLA-
B8 or HLA-DR3 was a requirement for selection of sIBM patients for investigation, as
was the absence of other possible sIBM associated AHs. The previous results of those
patients in the cohort also investigated by Price et al. (2004) were also used to eliminate
patients carrying either the full or no part of the 8.1AH in the region of interest. After
taking into account patients without available DNA, only eight individuals fulfilled
these criteria. Had this study used the same criteria for patient selection as Cheong et al.
(2001), then 30 of the possible 156 individuals would have been used for recombination
mapping. However any results arising from the larger cohort would have been less
reliable, particularly given the presence of any other sIBM-associated haplotypes in the
examined patients.
8.4.3 Allele specificity in recombination mapping
Re-defining the susceptibility region in this study was the result of utilising a selection
of well-characterised markers capable of differentiating the 8.1AH from other
haplotypes. In particular, knowledge of which AHs carried each marker enabled the
differentiation of the 8.1AH from other AHs that may carry the same minor allele. For
the same reason, major (common) alleles carried in the 8.1AH were not used for
recombination mapping. This was because the presence of major alleles on most other
haplotypes would have greatly increased the risk of incorrectly assigning such an allele
as defining presence of the 8.1AH.
The only minor alleles known to be haplospecific to the 8.1AH were rs926593 and
rs3129959. All of the other markers used were either found in other AHs, or had not
been genotyped on enough haplotypes to confirm their specificity. The lack of
specificity of most alleles to the 8.1AH thus introduced a risk of markers being
incorrectly identified as representing the 8.1AH. In such instances, consecutive nearby
markers were able to confirm or refute the presence of the 8.1AH. While a single
marker carrying the minor allele could be mistakenly assigned to the 8.1AH, this is a
less likely occurrence where multiple consecutive markers carry the minor allele.
157
8.4.4 The candidate sIBM susceptibility genes
The sIBM susceptibility region re-defined in this study encompasses three protein-
coding genes – the first and second exons of BTNL2, as well as HLA-DRA and HLA-
DRB3. Based on the results of this study, these are the most likely candidate genes for
conferring susceptibility to sIBM on the 8.1AH
8.4.4.1 BTNL2
BTNL2 is related to the immunoglobulin gene superfamily of cell surface receptors,
specifically the B7.1 and B7.2 costimulatory receptors (Rhodes et al., 2001; Sharpe and
Freeman, 2002) that bind to the CD28 expressed on T-cells to allow optimal activation
(Shahinian et al., 1993; Krinzman et al., 1996). Despite morphological similarities,
BTNL2 does not bind to the same B7 family of receptors and instead interacts with an
unknown receptor expressed on the endothelium of the Peyer‘s patch and liver (Arnett
et al., 2007). BTNL2 is known to act as a negative regulator of CD4+ T-cell
proliferation and cytokine production (Nguyen et al., 2006; Arnett et al., 2007).
Structurally, BTNL2 consists of a leader sequence containing the signal peptide, two
IgV-like domains, two IgC-like domains, a heptad linker sequence, a transmembrane
domain and a cytoplasmic domain. Each domain is coded by a separate exon, giving a
total of eight exons (Arnett et al., 2007). The sIBM susceptibility region defined in this
study encompasses only the promoter region, the leader sequence and a V-like
immunoglobulin domain for BTNL2. Mutations in the BTNL2 promoter may affect the
expression of the gene, while any polymorphism within the extracellular V-like
immunoglobulin domain could influence the binding affinity of the BTNL2 protein to
its receptor.
Other disease association studies with BTNL2 have focussed on a truncating mutation in
exon 5 (rs2076530). These studies have not identified a direct association between any
of the investigated immune-related diseases (sarcoidosis, multiple sclerosis, type 1
diabetes, rheumatoid arthritis, and systemic lupus erythmatosis) and either rs2076530 or
BTNL2 (Orozco et al., 2005; Rybicki et al., 2005; Valentonyte et al., 2005; Traherne et
al., 2006a). The allele rs2076530 also lies outside of the minimum defined sIBM
susceptibility region, reducing the likelihood of its involvement in sIBM.
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BTNL2 is normally expressed at low levels in multiple cell types including the thymus
and leukocytes (Valentonyte et al., 2005) but aside from an initial observation in mice
(Stammers et al., 2000), normal skeletal muscle does not express the gene. The
expression of BTNL2 in sIBM-affected muscle tissue and leukocytes has never been
assessed. BTNL2 expression is thus a possible approach for further investigation of a
role for BTNL2 in sIBM.
8.4.4.2 HLA-DRA and HLA-DRB3
The region between HLA-DRA and HLA-DRB1 is unusual in that the gene content
varies between haplotypes (Andersson et al., 1994). Coding genes and pseudogenes
labelled HLA-DRB2 through to HLA-DRB9 are not found in all AHs and there are
normally only one or two coding genes between HLA-DRA and HLA-DRB1 in any
given haplotype. The 8.1AH contains one coding gene within the region, HLA-DRB3,
which along with HLA-DRA are two of the three coding genes within the sIBM
susceptibility region defined in this study.
HLA-DRA and HLA-DRB3, respectively encode the α and β subunits of the MHC Class
II molecule HLA-DR, although HLA-DRB1 is normally expressed as a β subunit
preferentially over HLA-DRB3 (Berdoz et al., 1987; Emery et al., 1993; Andersson et
al., 1994). The complete heterodimer contains a peptide binding groove, which is used
to anchor an extracellular 10-25 amino acid peptide. The HLA-DR/peptide complex
then presents the peptide on the cell surface for recognition by CD4+ T-cells.
Recognition by the T-cell receptor converts the attached thymocyte to a mature CD4+
T-cell specific to the peptide presented by the HLA-DR complex (Klein and Sato,
2000). Like all class II HLA complexes, HLA-DR is normally expressed by activated
CD4+ T-cells, thymic epithelial cells, B-cells, macrophages and dendritic cells. Other
cells can express class II HLA genes in the presence of interferon-γ (Klein and Sato,
2000).
HLA-DRA alleles have not been directly associated with any diseases and HLA-DRA
appears to show only minor genetic variation between individuals, with only three
recognised alleles (Marsh et al., 2005). Conversely, HLA-DRB3 shows much higher
genetic variation with 41 recognised alleles (Marsh et al., 2005). HLA-DRB3 is
associated with susceptibility to multiple other autoimmune diseases including
sarcoidosis (Rossman et al., 2003) and Graves disease (Chen et al., 2000). The
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mechanisms by which HLA-DRB3 or any alleles linked with HLA-DRB3 might
contribute to these diseases remain unknown.
8.4.5 The sIBM susceptibility genes and pathogenesis
The two defining components of sIBM pathology are the degenerative component,
characterised by intracellular inclusions (Askanas and Engel, 2006), and the
inflammatory component, which consists primarily of CD8+ T-cells and macrophages
(Arahata and Engel, 1984). It is unclear as to which of these components are involved in
the primary pathogenesis of sIBM (Dalakas, 2004) and none of the potential sIBM
susceptibility genes identified in this study, BTNL2, HLA-DRA, or HLA-DRB3, have
been directly associated with either component. A role for disease susceptibility in the
identified susceptibility genes is thus dependent on which component of sIBM
pathology, if either, is the initial mechanism for pathogenesis.
8.4.5.1 The degenerative component in sIBM pathogenesis
The protein aggregates that form the intracellular inclusions are thought to be the result
of misfolded and unfolded polypeptides that interfere with the binding of normal
proteins (Ellis and Pinheiro, 2002; Askanas and Engel, 2006). Polymorphisms affecting
the overall protein structure could potentially result in an aberrant or misfolded variation
of BTNL2, HLA-DRA, or HLA-DRB3 that could encourage oxidative stress and
contribute to the intracellular inclusions. Neither BTNL2 nor HLA-DR proteins have
been identified in intracellular inclusions, which consist of whole or fragmented β-
amyloid and APP, along with many other proteins. Therefore any investigation of this
possibility would first require the identification of BTNL2 or HLA-DR protein
fragments in the intracellular inclusions.
8.4.5.2 The immune component in sIBM pathogenesis
Both BTNL2 and HLA-DR have functions related to CD4+ T-cells, with BTNL2
regulating CD4+ T-cell proliferation and HLA-DR presenting peptides for recognition
by CD4+ T-cells. Conversely it is the CD8+ T-cells that appear to play a central role in
the immune response in sIBM, as evidenced by their prevalence as a major component
of the inflammatory infiltrate and the presentation of MHC Class I molecules on
affected skeletal muscle. Assuming that the CD8+ T-cells are a central component in
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sIBM pathology, the likely role for BTNL2 or HLA-DR would be in influencing the
interaction of CD4+ T- helper cells with CD8+ T-cells.
8.4.6 mRNA expression of the sIBM susceptibility genes
Thus far there has been only one mRNA expression study (Greenberg et al., 2002) that
has analysed any of the genes within the sIBM susceptibility region defined by Price et
al. (2004). BTNL2 and HLA-DRB3 expression were not assessed, although HLA-DRA
showed a six-fold increase in sIBM as compared to controls. This was only marginally
higher than the increase found in polymyositis patients, another inflammatory
myopathy, and was not considered significant within the limits of the published study
(Greenberg et al., 2002). While increased expression of HLA-DRA can suggest an
involvement with sIBM pathology, a more comprehensive approach to the expression
pattern and functional analysis of the gene would be necessary to differentiate whether
the observed expression is indicative of a key upstream process that directly influences
sIBM pathogenesis, or a secondary downstream process unrelated to pathogenesis.
Further such analysis would be warranted for HLA-DRA, given that the gene is within
the refined sIBM susceptibility region.
8.4.7 Other susceptibility haplotypes
In addition to the 8.1AH, three other defined haplotypes may confer susceptibility to
sIBM; the 7.2AH in Caucasians (HLA-B*0702, DRB1*0101, DQB1*0501; Chapter 5),
the 35.2AH in Caucasians (HLA-B*3501, DRB1*0101, DQB1*0501) (Price et al., 2004;
O'Hanlon et al., 2005) and the 52.1AH in the Japanese (HLA-B*5201, DRB1*1502;
Chapter 5). Of the three genes within the 8.1AH-derived sIBM susceptibility region,
BTNL2 and HLA-DRA, but not HLA-DRB3 are present in the 7.2AH, 35.2AH and
52.1AH (Andersson et al., 1994). A hypothetical sIBM susceptibility allele common to
the 8.1AH and the 7.2AH, 35.2AH or 52.1AH would thus be likely to localise with
BTNL2 or HLA-DRA.
Recombination mapping could be used to further define the sIBM susceptibility region
for the 7.2AH, 35.2AH or 52.1AH, but this is currently prevented by the unavailability
of well characterised markers that would differentiate these haplotypes from other AHs.
Any prospect of mapping the 52.1AH is further complicated by very few patients
carrying only part of the haplotype. In the only statistically significant study of sIBM in
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a Japanese patient cohort, only one individual carried HLA-B*5201 but not HLA-
DRB1*1502 (Chapter 5, Table 5.8).
8.4.8 Genes outside the sIBM susceptibility region
Despite lying outside of the most likely sIBM susceptibility region, other genes such as
AGER and NOTCH4 may still be affected by polymorphisms within the susceptibility
region through enhancers or locus control regions. An enhancer or locus control region
for a specific gene may exist several hundred kb upstream or downstream of the gene
itself, acting as nucleoprotein complexes that modify the chromatin structure and
interact with the basal machinery to alter the expression of the target gene (Arnosti and
Kulkarni, 2005).
The hypothesis that enhancers affect expression of one or more nearby genes in sIBM
patients would be best addressed through mRNA and protein expression studies. The
mRNA expression study of sIBM patients by Greenberg et al. did find that the nearby
genes PBX2 and GPSM3 showed a 4-fold and 6-fold increase in expression
respectively, compared to controls, although the authors did not consider these to be
significant changes (Greenberg et al., 2002). Another recent study has identified
increased expression of RNF5, an E3 ligase implicated in muscle organisation, in sIBM
patient muscle fibres (Delaunay et al., 2008). RNF5 is located directly telomeric of
AGER, which places it in close proximity to the sIBM susceptibility region defined in
this study. RNF5 is thus a candidate for regulation by enhancers localised within the
sIBM susceptibility region defined by the 8.1AH.
8.4.9 Conclusion
This study suggests that the source of the 8.1AH-derived susceptibility to sIBM most
likely originates from a 172kb section of the Class II MHC region that encompasses part
of BTNL2, HLA-DRA and HLA-DRB3, the latter of which comprise the alpha and beta
subunits of HLA-DR. Given the unknown pathogenesis of sIBM it is difficult to
hypothesise a precise role for BTNL2 or HLA-DR in sIBM. The mechanisms by which
BTNL2 or HLA-DR could contribute to sIBM susceptibility remain unclear and warrant
further investigation. Protein and mRNA expression studies of each gene, including
functional studies of protein variants of the genes in sIBM patients could assist in
elucidating such a mechanism. Sequencing of either the genes themselves or the entire
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172kb region in sIBM patients with multiple appropriate AH controls may also uncover
a key susceptibility allele and by extension, a mechanism through which it confers
susceptibility. HLA-DRA is of particular interest for further investigation, given its
increased expression in sIBM patients. Consideration should also be given to the
possibility of an enhancer sequence within this region and the nearby genes it may
affect.
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CHAPTER NINE
9 GENERAL DISCUSSION
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9.1 Current ‘state of play’ of MHC disease association
In more than 40 years of research, no single polymorphism within the MHC has been
assigned direct responsibility for a complex, immunological disease. Studies have
identified genes or alleles associated with various diseases (Sollid et al., 1989; Horton et
al., 2004; Ciclitira et al., 2005), but a single disease-causing allele has remained elusive.
The nature of the MHC is such that the high gene density, the high level of
polymorphism and especially the strong linkage disequilibrium all act to complicate
efforts in locating a single allele directly associated with sIBM (Horton et al., 2004;
Shiina et al., 2004).
Dissecting disease associations within the MHC to a single allele requires analysis of
sequence data at a very high level of detail, as well as an understanding of the MHC,
particularly linkage disequilibrium and how conserved haplotypes, or AHs, interact over
time. It was with this emphasis of highly detailed analysis that the molecular genetics of
sIBM susceptibility was investigated.
The central hypothesis of this thesis was that susceptibility to sIBM is conferred by a
single allele found within a region defined using the 8.1AH and carried by multiple
haplotypes associated with sIBM. The present study thus set out to examine
polymorphisms and genes within the susceptibility region defined by Price et al. (2004),
and refining this region. This would clarify the possible source of the observed genetic
susceptibility to sIBM, in both the 8.1AH and in other sIBM susceptibility haplotypes.
9.2 Overview of the Study
The location and nature of polymorphisms within the sIBM susceptibility region were
catalogued by aligning sequence data from cell lines carrying the 8.1AH and several
other haplotypes. Given the possible association of NOTCH4 with sIBM, coding region
polymorphisms within the gene were then assessed and screened against sIBM patients.
Several alleles were identified as markers for sIBM susceptibility in Caucasians,
although strong linkage disequilibrium throughout the MHC complicated efforts to
identify any as playing a direct role in conferring sIBM susceptibility.
sIBM patient cohorts were genotyped to assess HLA allele and haplotype frequencies
relative to past research. In Caucasians, carriage of sIBM was increased in individuals
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carrying alleles that match the 8.1AH. However the 7.2AH was also increased, as
opposed to the 35.2AH previously reported (Price et al., 2004; O'Hanlon et al., 2005). In
the Japanese, alleles matching the 52.1AH were associated with sIBM, while the allele
HLA-DPB1*0901, normally common to the Japanese population, was absent in patients,
suggesting a possible protective effect against sIBM.
Coding and promoter region polymorphisms within the sIBM susceptibility region
defined by Price et al. (2004) were genotyped against the four sIBM susceptibility
haplotypes; the 8.1AH, 7.2AH, 35.2AH and 52.1AH. Of the alleles genotyped, none
were unique to all four haplotypes although one located in C6orf10 (rs2050189) was
common to the 8.1AH, 7.2AH and 52.1AH. Further investigation in Caucasian sIBM
cohorts showed that rs2050189 was not consistently present in the 8.1AH and 52.1AH
carried by sIBM patients, and was possibly absent in the 7.2AH carried by sIBM
patients. There was thus insufficient evidence for the rs2050189 minor allele acting as
an sIBM susceptibility allele in multiple haplotypes. The HLA-DRA promoter region
was also identified as having a high level of sequence similarity between the 8.1AH,
7.2AH, 35.2AH. However all of the polymorphisms in this promoter region were also
found in haplotypes that were not increased in sIBM patients. It is thus unlikely that
these particular polymorphisms are involved in sIBM susceptibility.
Using characterised markers, recombination mapping was carried out for patients
carrying part of the 8.1AH to identify a common, overlapping sIBM susceptibility
region. The 389kb 8.1AH-defined sIBM susceptibility region reported by Price et al.
(2004) was refined to a minimum region of 172kb encompassing three genes; BTNL2,
HLA-DRA and HLA-DRB3. Susceptibility to sIBM in Caucasians, as derived from the
8.1AH, is most likely to originate from one of these three genes. Further investigation
into polymorphisms related to each gene and their role in sIBM pathogenesis is thus
warranted.
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9.3 Considerations
The approaches used throughout this study to analyse the MHC generated a number of
significant considerations. These can be divided into four points of discussion;
1. The relationship between the 7.2AH, the 35.2AH and sIBM susceptibility
2. The Japanese association with sIBM, particularly in regards to the 7.2AH and
the concept of ‗sub-haplotypes‘.
3. The rs2050189 allele, common to the 8.1AH, 7.2AH and 52.1AH.
4. The use of recombination mapping in sIBM patients.
9.3.1 The 7.2AH and the 35.2AH
Defined AHs are not mutually exclusive and can show a degree of overlap, where
regions inherited from a common lineage are preserved between multiple AHs. This
concept was integral in defining the 8.1AH-derived sIBM susceptibility region by Price
et al. (2004). Specifically, the centromeric limit of the sIBM susceptibility region was
originally defined by the near-identical, commonly inherited region between the
18.2AH and the sIBM-associated 8.1AH spanning from HLA-DRB1 to HLA-DQB1
(Price et al., 2004; Traherne et al., 2006b). The concept of commonly inherited regions
between AHs was demonstrated in the present study when observing two proposed
susceptibility haplotypes; the 7.2AH and the 35.2AH.
Detailed SNP genotyping in Chapter 7 indicates that the 7.2AH and 35.2AH are almost
completely identical at the alleles investigated from PBX2 to HLA-DRA. These results
suggest that the 7.2AH and 35.2AH share a commonly inherited region on the border of
the MHC Class II and III regions, which may also extend as far as the commonly
carried allele HLA-DQB1*0501 and further into the MHC class II region (Cattley et al.,
2000). The results of Chapter 5 suggested two possibilities with regards to these
haplotypes and sIBM susceptibility. The first was that the 7.2AH and the 35.2AH confer
susceptibility via a commonly inherited region. Alternatively, it may be that only the
7.2AH is associated with sIBM and thus confers disease susceptibility in Caucasians,
rather than the 35.2AH as reported in previous studies (Price et al., 2004; O'Hanlon et
al., 2005). The significance of the region common to the 7.2AH and the 35.2AH is
dependent on whether one or both haplotypes confer susceptibility to sIBM.
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If both the 7.2AH and 35.2AH confer susceptibility to sIBM, then the two haplotypes
may confer susceptibility to sIBM via the same allele within the commonly inherited
region. Given that the common region between the 7.2AH and 35.2AH overlaps with
the 8.1AH-derived susceptibility region, it is also possible that the 7.2AH, 8.1AH and
35.2AH all confer sIBM susceptibility either through alleles affecting the same gene, or
through an allele common to all three haplotypes. If this were the case, then the
recombination mapping results in Chapter 8 suggests that the prime candidate genes are
BTNL2 or HLA-DRA. HLA-DRB3 is not present in haplotypes carrying HLA-
DRB1*0101 (such as the 7.2AH or 35.2AH) and so could not be responsible for
conferring susceptibility for these AHs.
Conversely, it is possible that only one of the two haplotypes is associated with sIBM.
The sIBM association observed in Chapter 5 was with HLA-DRB1*0101 rather than any
HLA-B allele, suggesting a disease susceptibility allele on the 7.2AH or 35.2AH is in
stronger linkage disequilibrium with HLA-DRB1*0101. Aside from this and without a
functional link between the disease pathogenesis and a specific gene, there is little
indication as to where a proposed susceptibility allele for the 7.2AH or 35.2AH could
lie.
If the susceptibility allele lies within the highly similar region between the 7.2AH and
35.2AH, from PBX2 to HLA-DRA, it could be identified by directly comparing
sequence data from the two haplotypes for discordant variations. An example of one
such variation is the minor allele for rs2050189, which was located on C6orf10 in the
7.2AH, but not the 35.2AH (Chapter 6).
It is equally possible that a 7.2AH or 35.2AH susceptibility allele is located in a region
not commonly inherited by both haplotypes. Assuming that the two haplotypes retain
their common identity from PBX2 into the MHC Class II region, the most likely source
of 7.2AH or 35.2AH-associated sIBM susceptibility allele would be within the Class III
MHC region, telomeric of PBX2.
The determination of whether 7.2AH, the 35.2AH or both haplotypes confer sIBM
susceptibility is an essential step before the location of a possible susceptibility allele
for either of these haplotypes can be investigated. Once susceptibility in either or both
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haplotypes is confirmed, the common region between the 7.2AH and 35.2AH could be
used to help deduce candidate susceptibility alleles.
9.3.2 sIBM in the Japanese, the 7.2AH and ‘sub-haplotypes’
The prevalence of sIBM appears to be increasing amongst the Japanese (Professor
Ichizo Nishino, personal communication). While an increase in the prevalence of
environmental factors predisposing individuals to sIBM may be to blame, it could also
be the result of improved guidelines for diagnosing sIBM. Since its initial
characterisations in 1967 and 1971 (Chou, 1967; Yunis and Samaha, 1971), sIBM has
been misdiagnosed in patients as other diseases such as polymyositis or motor neuron
disease (Dabby et al., 2001; Amato and Griggs, 2003), due in part to poorly defined
diagnostic criteria. In recent years this trend has declined as improved diagnostic criteria
are adopted, and so any increase in disease prevalence may be a reflection of this.
The HLA genotyping of the Japanese sIBM patients (Chapter 5) resulted in three key
findings. These were;
1. the 52.1AH was significantly increased in patients,
2. HLA-DPB1*0901 was significantly decreased in patients,
3. alleles matching the 7.2AH showed no change in allele frequency.
The latter point is of particular interest, considering that the alleles matching the 7.2AH
were increased in Caucasian patients. In Chapter 5, it was suggested that the
‗Caucasian‘, sIBM-associated 7.2AH and the ‗Japanese‘ 7.2AH may be distinct sub-
haplotypes of what is generally considered the 7.2AH. The only 7.2AH-carrying cell
line available for genotyping alleles, KUROIWA, is of Asian ethnicity, which implies
that this cell line is more closely associated with the non-sIBM associated ‗Japanese‘
7.2AH.
The relationship between the Japanese and Caucasian 7.2AH is the same consideration
as addressed with the 8.1AH and its own possible sub-haplotypes (Chapter 6). While
there is no guarantee that the KUROIWA cell line carries the sIBM-associated allele, it
is likely that a sub-haplotype of a given AH will still be highly similar, with only minor
variations. Therefore detailed genotyping can be utilised with the KUROIWA cell line
to at least assist in defining a susceptibility region for the Caucasian 7.2AH. Patient
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DNA carrying the disease-associated sub-haplotype might then be used to identify an
allele directly associated with the observed disease susceptibility.
9.3.3 The rs2050189 allele
The hypothesis addressed in Chapter 6 was that an allele common to multiple sIBM
susceptibility haplotypes confers disease susceptibility. Genotyping of the 8.1AH
coding and promoter regions from PBX2 to HLA-DRA revealed one allele, designated
rs2050189, that was found in the 8.1AH, 7.2AH and 52.1AH. However when genotyped
in Caucasian patients, the rs2050189 minor allele was absent in multiple individuals
otherwise confirmed to carry the 8.1AH, as well as some individuals predicted to carry
the 52.1AH and most individuals predicted to carry the 7.2AH. Furthermore, the
suggested redefined sIBM susceptibility region (Chapter 8) does not encompass
rs2050189 or its associated gene C6orf10. These observations suggest that the presence
of rs2050189 in the 8.1AH, 7.2AH and 52.1AH is not related to susceptibility to sIBM.
It is thus unlikely that the rs2050189 minor allele could be an sIBM susceptibility allele,
irrespective of its occurrence on multiple haplotypes.
9.3.4 Recombination Mapping
Recombination mapping of patients carrying part of the 8.1AH was successful in re-
defining 8.1AH-derived susceptibility to a region encompassing BTNL2, HLA-DRA and
HLA-DRB3. Ideally, the markers used for recombination mapping could have been
more evenly distributed across the entire region from PBX2 to HLA-DRB1, particularly
between HLA-DRA and HLA-DRB1. Further recombination mapping with markers
between HLA-DRA and HLA-DRB1 may refine the sIBM susceptibility region more
precisely, although it is not likely to change the selection of possible candidate genes
within the 8.1AH.
One of the restrictions for selecting patients used in recombination mapping is that they
could not carry a full copy of the 8.1AH or any other susceptibility haplotype. The
reasoning for this was that the presence of any fragment of the 8.1AH would be
irrelevant to the patient‘s susceptibility to sIBM if they already carried a full, disease
associated, haplotype. Of the patients identified as possibly carrying part of the 8.1AH,
one from the German cohort also carried the 35.2AH and another (AU_75) carried
alleles matching the 7.2AH from HLA-B to HLA-DRB1. Therefore if an association
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between sIBM and either the 7.2AH or the 35.2AH can be refuted, then additional
individuals from the patient cohorts could be utilised for recombination mapping.
Given that recombination mapping was successfully used to further define the 8.1AH-
derived sIBM susceptibility region in Caucasians, a logical extension of the study would
be to use the same approach to map sIBM susceptibility in the 7.2AH, 35.2AH and
52.1AH. Recombination mapping of these haplotypes is hampered by either a lack of
available individuals carrying only part of a susceptibility haplotype, or the absence of
available markers that could reliably differentiate the sIBM-associated haplotype from
others. Within the Japanese cohort there were only two individuals identified as
potentially carrying part of the 52.1AH between HLA-B and HLA-DRB1 (JAP_4 and
JAP_16; Table 5.8). Of these, one also carried the full 52.1AH, thus precluding any
possibility of identifying susceptibility from a partial haplotype.
Of the Caucasian sIBM cohorts, a total of 21 patients carried either HLA-B*0702, HLA-
B*3501 or HLA-DRB1*0101 and are thus candidates for carrying part of the 7.2AH or
35.2AH (Table 5.1, Table 5.5). However most also appeared to carry another sIBM
susceptibility haplotype, specifically the 8.1AH, 7.2AH or 35.2AH, from HLA-B to
HLA-DRB1. This leaves eight Caucasian patients that would be suitable for
recombination mapping. While this could be sufficient for a recombination mapping
study, detailed sequence data on the order of that available for the 8.1AH is not
currently available for the 7.2AH or the 35.2AH. This complicates efforts in identifying
alleles that can effectively characterise the 7.2AH, 35.2AH. The same hurdle also
applies to the Japanese 52.1AH. Instead, suitable alleles need to be acquired from either
past research or sequence data flanking other alleles genotyped in the region. It was
through these approaches that some alleles characteristic of the 7.2AH and 35.2AH
were located, of which the markers rs17202155, BTNL2*E6 and T(-790)A could
potentially be used to confidently define the presence of the 7.2AH or 35.2AH (Chapter
7). In order to confidently and precisely define an sIBM susceptibility region for the
7.2AH and 35.2AH to the detail that was achieved in Chapter 8, more alleles
characteristic of the two susceptibility haplotypes would need to be identified, possibly
by complete sequencing of these AHs, as was done for the 8.1AH.
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9.4 RNF5 and sIBM
A very recent paper reported that protein expression of RNF5, an E3 ligase implicated
in muscle organisation, is elevated and mislocalised to the cytoplasmic aggregates of
sIBM patient muscle fibres. Deregulation of RNF5 was also observed in animal models
for the physiologically similar disease hIBM, and overexpression of RNF5 in a mouse
model was found to promote a phenotype similar to that of sIBM (Delaunay et al.,
2008). The results of Delaunay et al. (2008) suggest that RNF5 may play a role in sIBM
pathogenesis.
Of particular interest is that RNF5 itself is located just telomeric of AGER in the MHC
class III region. This places RNF5 directly adjacent to the region investigated over the
course of this thesis, but outside of the susceptibility region defined in Chapter 8. There
are three possible explanations for the close proximity between RNF5 and the 8.1AH-
defined susceptibility region;
1. RNF5 alone is responsible for sIBM susceptibility,
2. both RNF5 and the 8.1AH-defined region are involved in sIBM pathogenesis,
3. RNF5 expression is linked with a downstream pathological mechanism, rather
than the initial pathogenesis of sIBM.
If RNF5 is responsible for sIBM susceptibility, then the genetic source of the
susceptibility could lie within the 8.1AH-defined susceptibility region as an enhancer,
or locus control region. As stated, an enhancer for a specific gene may exist several
hundred kb upstream or downstream of the gene itself (Arnosti and Kulkarni, 2005).
Thus a variation in an enhancer within the 8.1AH-defined susceptibility region could
affect the expression of RNF5.
If a genetic variation in the RNF5 gene was found to play a role in susceptibility to
sIBM, then that result would be discordant with the results of Price et al. (2004) and
Chapter 8. However while Price et al. (2004) did not account for the presence of alleles
in other haplotypes, the results were still sufficient to define the sIBM susceptibility
region to between PBX2 and HLA-DRB1. Furthermore, recombination mapping in
Chapter 8 reinforced the results of Price et al. (2004). A more stringent and robust
methodology was used that accounted for alleles present on other haplotypes, as well as
eliminating patients with other potential susceptibility haplotypes and using a much
wider selection of markers.
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An alternative explanation for RNF5 genetic variations in sIBM susceptibility is that it
may instead confer susceptibility independently of the 8.1AH-defined susceptibility
region. The existence of multiple susceptibility alleles lying near each other has been
observed previously. For instance, susceptibility to murine systemic lupus
erythematosus was found to originate from variations in a cluster of four separate
susceptibility genes, Sle1a, Sle1b and Sle1c (Morel et al., 2001).
Like -amyloid and APP (Askanas and Engel, 2006), RNF5 overexpression may be
involved in a downstream mechanism in sIBM pathology, rather than playing a central
role in the disease pathogenesis. Thus, RNF5 may instead be triggered by another
upstream element more directly involved in pathogenesis such as a gene within the
susceptibility region defined in Chapter 8. Hence, the close proximity of RNF5 may
thus be co-incident to any genetic susceptibility to sIBM within the region from BTNL2
to HLA-DRB3. An important consideration is that there is currently no more evidence
that RNF5 directly confers susceptibility to sIBM than there is for -amyloid and APP.
However, a pathogenic mechanism would be far more likely if any sIBM-associated
genetic variation could be correlated with RNF5.
Genetic variations in RNF5 in relation to sIBM have not been investigated. However
after using the same methodology detailed in Chapter 6.3.1 three RNF5 coding region
SNPs, three promoter SNPs and three intronic SNPs that are all haplotypic of the 8.1AH
where identified. (Table A1.2 - http://www.waimr.uwa.edu.au/docs/Appendix-Table-
A1p2.pdf). These variations could be investigated using the same approaches detailed in
this thesis, by genotyping them against patients (Chapter 4) and conserved AH cell lines
(Chapter 6). Given that the gene itself spans 2.4kb, the entire gene could feasibly be
sequenced in both patients and cell lines. Had Delaunay et al. (2008) been published
earlier, such an approach would have been within the scope of this thesis.
9.5 sIBM susceptibility from multiple haplotypes
When considering the refined susceptibility region with respect to all of the identified
sIBM-associated haplotypes, the 8.1AH, 7.2AH, 35.2AH and 52.1AH, there are three
possible mechanisms by which they may confer disease susceptibility (Figure 9.1);
1. Multiple AHs confer sIBM susceptibility through a common allele,
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2. each AH confers sIBM susceptibility through an independently acquired allele,
3. sIBM susceptibility is conferred by independently acquired alleles that exist on
sub-haplotypes of AHs traditionally considered to be associated with the disease.
Each of these mechanisms were considered over the course of the thesis and have
implications for any future investigation into the sIBM susceptibility region.
Common Haplotype Ancestor
Haplotype 3
Haplotype 1
Haplotype 2
Sub-haplotype
3B
Sub-haplotype
3A
Common
Susceptibility allele
Independent
susceptibility allele
Sub-haplotype
susceptibility
allele
Independent
susceptibility allele
Figure 8.1: The three possible scenarios by which an AH can have developed an sIBM
susceptibility allele relative to other susceptibility haplotypes. A common susceptibility
allele would develop in an ancestor common to multiple susceptibility haplotypes, while
independent and sub-haplotype susceptibility alleles would develop after diverging into
their respective haplotypes and sub-haplotypes.
Recombination or
Gene Conversion
Common
Susceptibility allele
Figure 9.1: Three possible scenarios by which an AH can have developed an sIBM
susceptibility allele relative to other susceptibility haplotypes. A common susceptibility
allele would develop in an ancestor common to multiple susceptibility haplotypes or
through recombination/gene conversion. Independent and sub-haplotype susceptibility
alleles would develop after diverging into their respective haplotypes and sub-
haplotypes.
9.5.1 A common susceptibility allele
The prospect of a common susceptibility allele between the 8.1AH and one or more of
the other disease susceptibility haplotypes is less likely given the results of this thesis.
Allele genotyping between cell lines in Chapter 6 revealed no coding or promoter
region alleles that were specific to the 8.1AH and at least one of the other possible
sIBM susceptibility haplotypes. The allele that was closest to being specific to the sIBM
susceptibility haplotypes was rs2050189. However its inconsistent occurrence in
patients carrying a susceptibility haplotype cast doubt on its role in sIBM susceptibility
174
(Chapter 6). It is possible that a common polymorphism may exist in the intronic or
intergenic regions in the 8.1AH-defined susceptibility region from BTNL2 to HLA-
DRB3. An investigation of this would require characterising all such alleles against the
8.1AH, 7.2AH, 35.2AH, and 52.1AH between BTNL2 and HLA-DRB3, using the same
approach described in Chapter 6. If any such polymorphism can be located, a plausible
mechanism of action, such as that of an enhancer (Arnosti and Kulkarni, 2005) as
proposed in Chapter 8, would still be required before it could be considered to directly
confer susceptibility to sIBM. Without a mechanism of action, an allele common to
multiple susceptibility haplotypes may instead be in linkage disequilibrium with the
source of the observed disease susceptibilities.
9.5.2 Independent susceptibility alleles
An 8.1AH-specific disease-susceptibility allele remains a possibility within the refined
sIBM susceptibility region. The investigation of NOTCH4 coding alleles in Chapter 4,
both in prevalence amongst patients and possible function, yielded no results that were
congruent with a susceptibility region that excludes NOTCH4. While the methodology
used for NOTCH4 could also be applied to BTNL2, HLA-DRA or HLA-DRB3, a more
informative approach would be to investigate the expression pattern and function of
each of these three genes in muscle tissue from sIBM patients, after which the alleles
within the gene of interest could be assessed for their potential role in the disease. HLA-
DRB3 in particular is a prime candidate for conferring 8.1AH-derived susceptibility to
sIBM, given that it is found in only a few other haplotypes (Andersson et al., 1994).
Even between haplotypes carrying HLA-DRB3, such as the 8.1AH and 18.2AH, the
allele composition can vary markedly (Traherne et al., 2006b).
9.5.3 Alleles specific to a sub-haplotype
Sub-haplotypes were a concept highlighted by the observation of allelic variations
between individuals carrying the 8.1AH in the Caucasian cohorts, and with the
―Japanese‖ and ―Caucasian‖ 7.2AHs. In particular, the COX-specific allele for
rs9268642 and the minor allele for rs2050189 could be indicators of sub haplotypes.
Should an allele conferring susceptibility to sIBM exist within a sub-haplotype of the
8.1AH, then there is no guarantee that the 8.1AH-carrying cell lines used for this study
carry the sIBM susceptibility allele. In this case, cell lines carrying defined AHs could
not be used to identify potential susceptibility alleles, although they would still be
175
useful in defining the probable susceptibility region (Chapter 8). If a SNP that defines
an sIBM-associated sub-haplotype could be located, then a conserved cell line with the
same sub-haplotype could be identified using this SNP and analysed further for disease
susceptibility using the approaches discussed in this thesis. Otherwise, multiple patients
would need to be sequenced throughout the disease susceptibility region to identify
potential disease-susceptibility alleles.
The fragment of BTNL2 that lies within the sIBM susceptibility region has not been
genotyped in patients and neither has HLA-DRA. The method that was used in the
routine genotyping of HLA-DRB3 only sequences the peptide binding region of exon 2
(personal communication – Dr. Campbell Witt, Royal Perth Hospital). Alleles within
HLA-DRA and located outside of the peptide binding groove in HLA-DRB3 would
therefore remain undetected in sIBM patients. All of these genes are thus prime
candidates for sequencing in sIBM patients.
9.6 Future work
9.6.1 Susceptibility genes outside the MHC region
Like many other studies pertaining to the genetics of sIBM, this thesis focussed on
elucidating the genetic associations within the MHC region. While there is undoubtedly
a definite genetic association between sIBM and parts of the MHC, research into genetic
susceptibility derived from elsewhere on the human genome has been limited.
One study proposed a possible association between sIBM and the Val122Ile mutation in
the -amyloid related gene transthyretin which, when in the presence of an
overexpressing APP gene, greatly increased aspects of the sIBM phenotype in muscle
fibres cultured in vivo from an sIBM patient (Askanas et al., 2003). Another study found
that the basic Helix-Loop-Helix B3 gene, which is known to inhibit myogenic
differentiation (Azmi et al., 2004), is also over expressed in sIBM patient
mesoangioblasts (Morosetti et al., 2006). Greenberg et al. (2002) used Affymetrix
GeneChip microarrays to measure the expression of approximately 10,000 genes across
the human genome in the muscle specimens from six sIBM patients, identifying several
highly up-regulated genes. Studies that analyse the expression pattern or observed effect
of a gene could be used to hypothesise a role in conferring susceptibility to sIBM.
However without some understanding of the pathogenic mechanisms of sIBM, any
176
altered expression of a gene in sIBM patients may be the result of a downstream process
in the disease pathology, rather than an upstream pathogenesis. Further study would
thus be required before any of these genes could be considered part of an upstream
mechanism in sIBM pathology.
Another presently untested approach to investigating sIBM susceptibility outside of the
MHC is to utilise genome-wide linkage analysis. This approach uses the same principle
as was used in recombination mapping. Microsatellite markers or SNPs are genotyped
across the entire human genome in affected sibling pairs to locate common
susceptibility regions between individuals and by extension, potential susceptibility
alleles for further investigation. The primary difficulty in utilising this tool for sIBM is
that large numbers of affected sibling pairs are needed for sufficient statistical power.
For instance, sufficient statistical power for a linkage analysis study of Type I diabetes
was only achieved after combining one cohort (225 families) with the results of two
previous studies (187 and 356 families) for a total of 767 families (Cox et al., 2001).
An alternative approach to linkage analysis would be to use genome-wide association
studies. This approach utilises chip and/or bead technology to analyse hundreds of
thousands of individual SNPs across the human genome, at a relatively low cost to
identify disease susceptibility SNPs from cohorts of unrelated individuals. This
approach has shown some success in recent years, with the identification of disease
susceptibility alleles for myocardial infarction and coronary artery disease, for example
(Helgadottir et al., 2007; McPherson et al., 2007; Samani et al., 2007). The advantage
over linkage analysis is that affected siblings are not required, although very large
numbers of affected individuals and controls are necessary.
The primary hurdle to a genome-wide linkage or association study of sIBM patients is
in obtaining a large enough cohort. The present combined cohort of Caucasian sIBM
patients consists of 156 individuals, which is currently the largest cohort collected for
any sIBM study. Given the number of patients used in genome-wide linkage or
association studies, obtaining enough patients and unaffected siblings for sufficient
statistical power would prove to be difficult.
177
9.6.2 Investigation of other sIBM susceptibility AHs
Studies on the genetics of sIBM have consistently shown the strongest association with
alleles matching the 8.1AH (Garlepp et al., 1994; Garlepp et al., 1998; Koffman et al.,
1998b; Lampe et al., 2003; Badrising et al., 2004; Price et al., 2004; O'Hanlon et al.,
2005). However this and other studies have also found an association with the 35.2AH
(Price et al., 2004; O'Hanlon et al., 2005), the 7.2AH and the 52.1AH (Chapter 5).
There remains the possibility that the 7.2AH, 35.2AH and/or 52.1AH may share a
hypothetical susceptibility allele elsewhere in the MHC. Identifying such an allele is
complicated by detailed sequence data being unavailable for any of the three
haplotypes. If this can be overcome, then the identification of a common susceptibility
allele between the 7.2AH, 35.2AH and 52.1AH could be achieved using the same
approach detailed in Chapter 6, by characterising alleles found in one of the
susceptibility haplotypes against other AHs. Given that susceptibility for the 7.2AH,
35.2AH and 52.1AH could originate from any point on the MHC, some degree of
recombination mapping would be recommended to first define a smaller region in which
to investigate potential common susceptibility alleles.
Assuming a disease susceptibility region can be defined through recombination
mapping, the possibility of an independently conferred susceptibility allele, or an allele
within a sub-haplotype, can be addressed for the 7.2AH, 35.2AH or 52.1AH. This could
be achieved by sequencing potential susceptibility genes in either AH-carrying cell lines
or sIBM patients, depending on whether the possibility of a disease-causing sub-
haplotype is taken into account. Such an approach would have the advantage of not
requiring existing detailed sequence data for the sIBM-associated haplotypes. However
any recombination mapping of the 7.2AH, 35.2AH or 52.1AH would require a source of
well defined markers, whether they originate from detailed sequence data or from other
sources such as past literature or sequence data originally utilised for other work in the
region. In any case, the contribution of the 7.2AH, 35.2AH and 52,1AH to sIBM
susceptibility warrants further investigation, both to confirm their association with
sIBM and to define the source of the observed susceptibility.
178
9.7 The next logical step
This thesis has clarified the difficulties associated with defining the precise causes of
the MHC susceptibility to sIBM and laid groundwork for the discovery of the cause in
the future. Several possible directions for future work have been discussed, and the most
immediate focus for sIBM genetics should remain on the 8.1AH-derived sIBM
susceptibility region.
Current technology is on the verge of allowing the sequencing of large numbers of
patients at an affordable price (Okou et al., 2007). It is also now possible to isolate and
sequence distinct MHC haplotypes from an individual, thus allowing the sequencing of
just the 8.1AH, for instance, in an 8.1AH /18.2AH heterozygous individual (Guo et al.,
2006; Albert et al., 2007). As these advances come within reach, the immediate
application for sIBM susceptibility should be in complete sequencing of the disease
susceptibility region in the 8.1AH, as carried by both sIBM patients and healthy
controls. This will enable the identification of any disease-specific 8.1 sub-haplotypes,
found in sIBM patients but not 8.1AH controls. The possibility of alleles common to
multiple sIBM-associated AHs (the 8.1AH, 7.2AH, 35.2AH and 52.1AH) and
independently conferred disease susceptibility alleles could be addressed by sequencing
10IHW cell lines and patients carrying the susceptibility AHs. Thus, finally, the
technology may now be available to identify the precise basis of disease susceptibilities
in the MHC. This thesis has clarified the region of the MHC and the haplotypes in
which to look for the basis of susceptibility to sIBM with these new technologies in the
future.
179
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APPENDICIES
10IHW
no.Name AH HLA A
a HLA-B (serological)
HLA B* TNFabHLA-DR
(serological)
HLA-
DRB1*
HLA-
DQB1*
9013 SCHU 7.1 0301 7 0702 15 or 2 1501 0602
9131 KUROIWA 7.2 24 7 0702 a11b4 1 0101 0501
9022 COX 8.1 0101 8 0801 a2b3 3 or 17 0301 0201
9046 BH 13.1 0201 13 1302 7 0701 0201
9008 DO208915 18.1 2501 18 1801 a10b4 15 or 2 1501 06029020 QBL 18.2 2601 18 1801 a1b5 3 or 17 0301 0201
9042 TISI 35.1 2402 35 3508 a5b5 11 or 5 1103 0301
9006 WT100BIS 35.2 1101 35 3501 a2b1 1 0101 0501
37.1 37 a9b4 10 1001 0501
9026 YAR 38.1 2601 38 or 16 3801 a10b4 4 0402 0302
9021 RSH 42.1 3001:6802 42 4201 a6b5 3 or 18 0302 0402
9302 SSTO 44.1 3201 44 or 12 4402 a6b5 4 0401 0301
9050 MOU 44.2 2902 44 or 12 4403 a8b4 7 0701 0201
9053 HOR 44.4 3303 44 or 12 4403 a6b5 13 or 6 1302 0604
9076 T7526 46.1 0206:0207 46 4601 a6b5 9 0901 0303
9066 TAB089 46.2 0207:0201 46 4601 a6b5 8 0803 0601
9047 PLH 47.1 0301 47 4701 a10b4 7 0701 0201
50.1 50 or 21 a5b7 7 07
51.1 51 or 5 4 0404 0302
9142 HARA 52.1 24 52 or 5 a13b4 15 or 2 1502 0601
9141 HOKKAIDO 54.1 24 54 or 22 a11b4 4 0405 0401
DANZO, L 55.1 55 or 22 a10b4 14 or 6 1401 0501
9133 MAD, MF 57.1 1:3 57 or 17 5701 a2b5 7 0701 0303
9156 WON, PY 58.1 33 58 or 17 5801 a2b3 3 or 17 0301 0201
58.2 58 or 17 5801 13 or 6
59.1 59 5901 9 0901 0303
9098 MT14B 60.1 3101 60 or 40 4001 a11b4 4 0404 0302
60.2 60 or 40 a2b1 8 0801 0402
9059 SLE005 60.3 0201 60 or 40 4001 13 or 6 1302 0604
61.1 61 or 40 9 0901 0303
9031 BOLETH 62.1 0201 62 or 15 1501 a2b1 4 0401 0302
9060 CB6B 62.3 0101 62 or 15 1501 a6b5 13 or 6 1301 0603
64.1 64 1401 a4b7 7 0201
9079 LWAGS 65.1 3301 65 or 14 1402 a2b1 1 0102 0501
65.2 65 or 14 13 or 6 1303 0604
a - Serological specificities for HLA-A are only given if sequence-based alleles are unavailable.
Table A1.1: Allele assignments used to identify ancestral haplotypes. Results were adapted from Cattley et al (2000) and
updated with genotyping results from the IMGT/HLA database (http://www.ebi.ac.uk/imgt/hla/), where available using cell
lines considered to carry the relevant AH by Cattley et al (2000).
Table A1.2: Polymorphisms identified between four cell lines (QBL, SSTO, PGF and COX) from telomeric of RNF5 to centromeric of HLA-DRA .
Positiona rs no.b Typec Gene Gene regiond QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
1069 SNP RNF5 promoter -957 C C C T Yes1571 SNP RNF5 promoter -455 C C A C Yes1857 SNP RNF5 promoter -69 C C C G Yes1863 SNP RNF5 promoter -163 C C C G Yes2356 SNP RNF5 intron +65 C C C A Yes2508 SNP RNF5 intron C C C T Yes2861 SNP RNF5 intron A A A G Yes3560 SNP RNF5 exon G G G A Yes3625 SNP RNF5 intron -25 C C T C Yes3895 SNP RNF5 exon A A A G Yes4267 SNP RNF5 exon G G G C Yes5401 SNP AGER intron -127 C C C G Yes5680 SNP AGER intron T T T C Yes6160 SNP AGER intron +49 A C C C Yes7086 SNP AGER intron -55 G A G G Yes7798 SNP AGER intron +14 A A A G Yes7858 SNP AGER exon T T A T Yes8251 SNP (AGER) promoter +364 A T A A Yes8306 rs1800625 SNP (AGER) promoter +419 A A A G Yes9170 1bp MS PBX2 exon 9A 9A 12A 9A Yes9270 SNP PBX2 exon A C C A9273 SNP PBX2 exon A C A A Yes9340 1bp MS PBX2 exon 11A 12A 11A 11A Yes
10150 SNP PBX2 intron -34 A A A G Yes10868 SNP PBX2 intron +21 C C C T Yes11446 SNP PBX2 intron -22 A A A G Yes12348 1bp MS PBX2 intron +10 9A 8A 8A 8A Yes12774 SNP PBX2 intron G G G A Yes13505 SNP PBX2 exon T C C C Yes14185 rs176095 SNP (PBX2) promoter +356 A A A G Yes15822 rs3134605 SNP GPSM3 exon T T T C Yes16900 SNP GPSM3 intron -133 T T C T Yes17232 SNP GPSM3 intron T T T C Yes17262 SNP GPSM3 intron G G T G Yes17296 SNP GPSM3 intron C C C A Yes17718 rs204989 SNP GPSM3 intron G G G A Yes20532 1bp MS NOTCH4 intron +35 1T 2T 2T 2T Yes20735 SNP NOTCH4 intron -20 G C G G Yes20740 SNP NOTCH4 intron -25 C A C C Yes21310 SNP NOTCH4 intron -73 A A A G Yes21449 SNP NOTCH4 intron G A G G Yes21463 1bp MS NOTCH4 intron 18T 19T 18T 19T22876 SNP NOTCH4 intron -86 T T G T Yes23351 5bp MS NOTCH4 intron 5CAAAA 5CAAAA 3CAAAA 5CAAAA Yes23870 1bp MS NOTCH4 intron 12T 13T 12T 12T Yes24649 rs3134942 SNP NOTCH4 exon G G G T Yes25452 SNP NOTCH4 intron T C T T Yes25499 SNP NOTCH4 intron T A T A26285 SNP NOTCH4 intron -31 G C C C Yes26311 SNP NOTCH4 intron -57 C T C T26343 indel NOTCH4 intron -88 G - G -26953 SNP NOTCH4 intron A A A G Yes27013 1bp MS NOTCH4 intron 1A 1A 1A 2A Yes27562 SNP NOTCH4 intron -24 T C T C27944 SNP NOTCH4 exon G G T G Yes28872 SNP NOTCH4 intron C C C T Yes29117 SNP NOTCH4 intron T C T T Yes29136 SNP NOTCH4 intron G A G A29204 1bp MS NOTCH4 intron 25A 25A 24A 26A Yes Yes30838 SNP NOTCH4 intron T C T C31212 SNP NOTCH4 intron G G G A Yes31287 1bp MS NOTCH4 intron 10C 9C 11C 9C Yes Yes31662 1bp MS NOTCH4 intron 18A 16A 20A 14A Yes Yes Yes Yes32089 SNP NOTCH4 intron G G G C Yes32092 SNP NOTCH4 intron G A G A32393 SNP NOTCH4 intron G A G A32663 SNP NOTCH4 intron G G G T Yes33144 SNP NOTCH4 intron A A G A Yes33310 SNP NOTCH4 intron C T C C Yes33495 SNP NOTCH4 intron T C T T Yes33506 SNP NOTCH4 intron C A C C Yes33552 indel NOTCH4 intron G - G G Yes33552 SNP NOTCH4 intron G A G G Yes33553 1bp MS NOTCH4 intron 11A 10A 11A 10A33761 SNP NOTCH4 intron G C G G Yes33781 SNP NOTCH4 intron T C T T Yes34655 SNP NOTCH4 intron -61 T C T C35255 rs9279509 4bp MS NOTCH4 intron 11ATAA 11ATAA 12ATAA 10ATAA Yes Yes35319 SNP NOTCH4 intron G G G A35777 SNP NOTCH4 intron C T C C Yes36027 SNP NOTCH4 intron G G A G Yes36504 SNP NOTCH4 exon A C C C Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
38144 2bp MS NOTCH4 intron 3CA 4CA 3CA 4CA38292 1bp MS NOTCH4 intron 14T 14T 14T 13T Yes39058 SNP NOTCH4 intron -13 G G G A Yes39848 SNP NOTCH4 intron G A A A Yes39949 SNP NOTCH4 intron G G G T Yes39977 SNP NOTCH4 intron G G G A Yes40104 SNP NOTCH4 intron G G G A Yes40588 SNP NOTCH4 intron -17 A G G A41806 indel NOTCH4 intron -38 AG AG AG - Yes41933 SNP NOTCH4 intron G G G A Yes42030 SNP NOTCH4 intron C C C A Yes42147 SNP NOTCH4 intron T T T C Yes42231 SNP NOTCH4 intron T C C C Yes42609 SNP NOTCH4 intron G G G A Yes42906 SNP NOTCH4 intron A A A G Yes43085 SNP NOTCH4 intron T T T C Yes43488 SNP NOTCH4 intron -42 A A A G Yes43604 SNP NOTCH4 intron AC AC AC TT Yes44266 rs422951 SNP NOTCH4 exon T T T C Yes45724 SNP NOTCH4 intron T T T G Yes45804 SNP NOTCH4 intron A A A G Yes45874 3bp MS NOTCH4 intron 2TCT 2TCT 2TCT 1TCT Yes45911 SNP NOTCH4 intron G G A G Yes46100 SNP NOTCH4 intron +71 T T T C Yes46273 rs915894 SNP NOTCH4 exon T T T G Yes46289 rs443198 SNP NOTCH4 exon A A A G Yes46367 SNP NOTCH4 exon A G G G Yes46754 SNP NOTCH4 intron -8 A T T T Yes46924 SNP NOTCH4 intron G G G A Yes47001 SNP NOTCH4 intron A G G G Yes47340 SNP NOTCH4 intron A G G G Yes47503 SNP NOTCH4 intron +13 C C C T Yes47544 rs9281675 3bp MS NOTCH4 exon 10CAG 10CAG 10CAG 12CAG Yes47996 SNP (NOTCH4) promoter +263 G C C C Yes48220 SNP (NOTCH4) promoter +487 G A A G48325 SNP (NOTCH4) promoter +592 G A A A Yes48506 SNP (NOTCH4) promoter +773 C T T T Yes48867 SNP (NOTCH4) promoter +1134 A T T T Yes49108 rs3130295 SNP (NOTCH4) promoter +1375 CG CA CA TA Yes Yes49193 rs9279514 1bp MS (NOTCH4) promoter +1460 21T 18T 18T 16T Yes Yes49341 SNP C T T T Yes49455 SNP T C C C Yes49590 SNP T A A A Yes49837 SNP T G G G Yes49969 SNP G T T T Yes49975 SNP G T T T Yes50151 SNP C A A A Yes50200 SNP T C C C Yes50231 SNP T C C C Yes50501 SNP G A A A Yes50522 SNP G G G C Yes50632 SNP T C C C Yes50643 SNP C T T T Yes50746 SNP A G G G Yes51143 SNP C T T C51250 SNP TA AG AG AG Yes51642 SNP T C C C Yes51740 1bp MS 13A 17A 17A 16A Yes Yes51827 SNP C T T T Yes52461 SNP A G G G Yes52467 SNP G T T G52520 SNP A G G G Yes52533 SNP A G G G Yes52540 SNP A G G G Yes52564 SNP T C C C Yes52570 1bp MS 24A 19A 18A 21A Yes Yes Yes Yes52595 indel - TA TA -52838 SNP T C C C Yes53117 SNP G T T T Yes53361 SNP G A A A Yes54227 SNP T C C C Yes54372 SNP C T T C54713 1bp MS 22A 26A 25A 23A Yes Yes Yes Yes54766 SNP C C C A Yes54835 SNP G G G A Yes54847 SNP C T T T Yes54860 SNP A T T T Yes54880 SNP C C C T Yes55043 SNP A C C A55251 SNP T C C T55953 SNP A G G G Yes55985 1bp MS 18T 21T 21T 20T Yes Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
56046 SNP G C C C Yes56401 2bp MS 23A 27A 27A 15A Yes Yes56569 SNP G A A G56653 SNP T C C C Yes56926 SNP C T T T Yes57047 SNP C C C T Yes57048 1bp MS 15T 12T 12T 29T Yes Yes57123 SNP T C C C Yes57167 SNP T A A A Yes57185 SNP A C C C Yes57195 SNP G G G C Yes57202 SNP T C C C Yes57251 SNP A G G G Yes57355 SNP T C C C Yes57442 SNP A A A G Yes57448 1bp MS 12T 13T 14T 13T Yes Yes57507 SNP A G G G Yes57676 3bp MS 11ATT 10ATT 10ATT 12ATT Yes Yes57818 SNP T A A A Yes57821 1bp MS 13T 14T 14T 14T Yes57901 SNP C T T T Yes58008 SNP G G T G Yes58115 SNP G C C C Yes58131 SNP T A A C Yes58137 SNP T A A A Yes58143 SNP T A A T58149 indel - TTT TTT TTT Yes58157 SNP A G G G Yes58173 SNP G A A A Yes58207 SNP T C C C Yes58625 2bp MS 1CT 2CT 2CT 2CT Yes58739 SNP T C C T58857 SNP C T T C59041 SNP T G G T59042 1bp MS 14T 29T 30T 13T Yes Yes Yes Yes59269 SNP A G G G Yes59513 SNP G G G A Yes59528 SNP T C C C Yes59530 SNP C T T C59798 SNP A A A G Yes59799 1bp MS 14A 10A 10A 10A Yes60133 SNP G T T G60198 1bp MS 24A 22A 22A 19A Yes Yes60361 rs693797 SNP T T T C Yes60585 SNP G G G A Yes60612 SNP G G G T Yes60697 SNP G A A A Yes60748 1bp MS 4G 4G 4G 3G Yes60854 SNP C T T C60880 SNP A G G A60973 SNP A G G G Yes61000 SNP T C C C Yes61038 SNP C T T C61199 SNP G T T G61267 SNP T C C T61365 SNP A G G A61501 2bp MS 2AT 2AT 2AT 3AT Yes61793 SNP A C C A61797 SNP A A A G Yes61872 SNP C C C T Yes61979 SNP A G G G Yes62033 SNP G C C G62173 SNP C C C T Yes62204 1bp MS 14A 14A 14A 10A Yes62305 1bp MS 1A 1A 1A 2A Yes62317 1bp MS 10T 10T 10T 23T Yes62343 SNP A T T A62409 SNP G G G A Yes62483 SNP C C C T Yes62954 SNP A A G G63125 SNP G G G A Yes63337 SNP T G G T63903 SNP C T T C64035 1bp MS 25A 21A 21A 21A Yes64272 SNP T C C T64614 1bp MS 1G 2G 2G 3G Yes Yes64645 SNP CA TG TG CA64975 SNP C T T T Yes65210 SNP C T T T Yes65360 SNP C T T T Yes65399 SNP G T T T Yes65510 SNP C T T T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
65809 SNP T C C T65911 SNP C T T T Yes66167 complex indel - - - - Yes Yes Yes Yes66835 SNP G A A A Yes67101 SNP A G G G Yes67121 SNP G T T G67254 SNP G A A G68269 SNP A G G A68273 SNP G T T G68277 SNP C T T C68300 SNP G A A A Yes68496 indel CTTT - - - Yes68503 1bp MS 15T 16T 16T 14T Yes Yes68695 SNP C T C C Yes68734 SNP G A G G Yes68739 SNP C C T C Yes68746 1bp MS 1G 2G 1G 1G Yes69049 SNP A G G G Yes69093 SNP A T A A Yes69161 1bp MS 2ATA 1ATA 1ATA 1ATA Yes69196 SNP G G A G Yes69682 SNP A G A A Yes69832 SNP A A G G69853 SNP CC CC TG TG69875 SNP T T A A70103 SNP C C G G70237 SNP A A G G70407 SNP C T T T Yes70475 SNP G G A A70515 1bp MS 14A 14A 15A 15A70661 SNP C C A A71108 SNP A A G G71233 SNP C C T T71243 SNP T T G G71297 SNP T T G G71337 SNP A A C C71359 SNP T T C C71517 SNP G G A A71815 SNP G C G G Yes71841 SNP G G T T71921 SNP A A G G72009 SNP C C T T72838 SNP G T T T Yes72895 SNP A A T T72936 SNP G G T T72956 SNP G G C C72985 indel - A A A Yes73008 SNP T T C C73027 1bp MS 9T 9T 8T 8T73064 SNP C C G G73092 SNP T T C C73138 SNP C C T T73206 SNP G G A A73231 SNP C C T T73278 SNP G G A A73283 SNP A G G G Yes73413 SNP G G A A73459 SNP C C T T73482 SNP G G A A73499 SNP G G A A73640 SNP T T C C73892 SNP A A G G74001 SNP A A G G74107 SNP G G A A74110 complex indel - - - - Yes Yes74265 SNP A A T T74307 SNP A G G G Yes74311 SNP CG TG CG CA Yes Yes74390 SNP A G A A Yes74517 SNP G T G G Yes75035 SNP G G A A75351 SNP T T C C75374 SNP C G G G Yes75512 SNP G T G G Yes75578 1bp MS 24A 23A 21A 21A Yes Yes76061 SNP AAT AAT TGA TGA76066 5bp MS 1AATTT 1AATTT 2AATTT 2AATTT76093 SNP G G G A Yes76098 2bp MS 2TG 2TG 3TG 3TG76173 SNP C T T T Yes76592 SNP A A G A Yes76679 SNP G G C C
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
76880 SNP A A G G77113 SNP G G A A77423 SNP C C T T77541 SNP A A G G77542 1bp MS 6A 6A 5A 5A77609 SNP A A T T77748 SNP G A G G Yes77978 SNP C C A A77993 1bp MS 10T 10T 12T 12T78130 SNP A G A A Yes78902 SNP G G A A79180 complex indel - - - - Yes79335 SNP A A A G Yes79484 SNP C C T T79644 SNP C C C T Yes79757 SNP A C A A Yes79858 SNP G G G A Yes79997 SNP T T T C Yes80001 SNP A A A G Yes80011 SNP G G G C Yes80056 SNP A A A T Yes80151 SNP T T T C Yes80173 SNP T T T A Yes80365 SNP G G G A Yes80545 SNP G G G T Yes80614 SNP A A C A Yes80665 SNP G G G A Yes80671 SNP A A A G Yes80682 SNP AG AG AG CA Yes80689 SNP T T T C Yes80715 SNP G G G A Yes80991 1bp MS 15T 16T 14T 16T Yes Yes81020 SNP G G G A Yes81056 SNP G G G C Yes81115 indel - C C C Yes81116 1bp MS 10T 13T 12T 11T Yes Yes Yes Yes81166 SNP A A A G Yes81279 SNP T T T C Yes81301 SNP T T T G Yes81426 SNP T T T C Yes81485 SNP C C C T Yes81500 SNP A A A T Yes81576 SNP G G G A Yes81577 2bp MS 2TG 2TG 2TG 3TG Yes81704 SNP G G G A Yes82357 SNP T T T C Yes82487 SNP A A A G Yes82583 SNP C C C T Yes82622 1bp MS 7T 7T 7T 6T Yes82702 SNP A A A G Yes82712 SNP A A A G Yes82738 SNP A A A G Yes82751 SNP T T T G Yes83055 SNP A A A C Yes83313 SNP G G G A Yes83343 SNP C C C T Yes83489 SNP GC GC GC AG Yes83493 SNP C C C G Yes83719 SNP A G A A Yes83737 SNP G G G T Yes84070 SNP A A A T Yes84081 SNP G G G T Yes84144 indel G - G G Yes84916 1bp MS 9T 9T 8T 9T Yes85150 SNP C T T T Yes85470 SNP T T T C Yes85674 SNP G G G A Yes85763 SNP G G G A Yes85768 1bp MS 13T 13T 13T 11T Yes85804 SNP C C T C Yes85863 SNP T C C C Yes85887 SNP C T C C Yes85953 SNP G G G A Yes86058 SNP C C C T Yes86222 indel G G G - Yes86288 SNP C C C T Yes86329 SNP C C C G Yes86440 SNP G G G A Yes86446 SNP T T T C Yes86488 SNP T T T G Yes86576 SNP T T T A Yes86586 SNP G G A A
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
86840 SNP T T T C Yes86890 SNP C C C G Yes86896 SNP CA CG CG TG Yes Yes86910 SNP C C C T Yes86964 SNP C C C T Yes87011 SNP A A A G Yes87056 SNP A A A G Yes87246 SNP G A G G Yes87317 SNP C C C G Yes87354 1bp MS 6A 6A 6A 5A Yes87545 SNP T T T C Yes87639 SNP G G G A Yes87715 SNP C C C T Yes87779 SNP A A A T87959 1bp MS 11T 11T 11T 12T88129 1bp MS 11T 11T 12T 11T Yes88357 SNP T T T C Yes88591 SNP C C T C Yes88642 SNP T C C C Yes88885 SNP G G C G Yes Yes88991 SNP T T T C Yes89210 SNP T T T C Yes89333 SNP G G G T Yes89606 SNP A A A G Yes89694 SNP G C C C Yes89780 SNP A G A A Yes89871 SNP T T T A Yes90047 SNP T C C C Yes90119 SNP G G G C Yes90248 SNP G G G A Yes90276 indel - - - A Yes90287 indel A A A - Yes90432 SNP C C C T Yes90576 SNP G G G T Yes90579 SNP C C C T Yes90585 4bp MS 6ATTT 5ATTT 5ATTT 5ATTT Yes90633 SNP A A A G Yes90650 SNP A A G A Yes Yes90718 SNP G G G C Yes90750 SNP C C C T Yes91191 SNP G T G G Yes91231 SNP A A A G Yes91247 SNP T T T G Yes91305 1bp MS 12T 12T 12T 13T Yes91335 SNP A A A C Yes91416 SNP A A A G Yes91546 1bp MS 16T 33T 20T 20T Yes Yes91636 SNP G C C C Yes91849 SNP A A A G Yes92112 SNP C C C G Yes92291 SNP G G G A Yes92306 SNP T G G G Yes92394 SNP G G G T Yes92722 SNP A A A G Yes92819 1bp MS 17T 18T 17T 22T Yes Yes92865 SNP CA CA CA TG Yes92965 1bp MS 3C 3C 3C 2C Yes93233 SNP T A A A Yes93415 1bp MS 15T 15T 16T 14T Yes Yes93478 SNP C C C T Yes93517 SNP A A A G Yes93579 SNP G G G A Yes93720 SNP T T T A Yes93765 SNP A A A G Yes93871 SNP G G G A Yes93902 SNP C G G G Yes93956 indel - - - C Yes94003 SNP C C C T Yes94006 SNP G G G A Yes94061 4bp MS 6AATT 6AATT 6AATT 5AATT Yes94184 SNP C C T C Yes94271 SNP T T T C Yes94477 SNP G G G A Yes94524 SNP C T C C Yes94538 SNP A A G A Yes94556 SNP G G G A Yes94686 SNP C C C T Yes94769 SNP G G G A Yes94775 SNP G G G A Yes94796 SNP T T T C Yes94938 SNP A A A G Yes95050 SNP T C T T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
95282 SNP A A A C Yes95308 SNP A A A C Yes95572 SNP G G G A Yes95599 SNP C C C T Yes95685 SNP G G G A Yes95816 SNP A C A A Yes95909 SNP C C C T Yes96330 SNP T T T A Yes96869 SNP A A A G Yes96927 4bp MS 4CAAA 4CAAA 4CAAA 5CAAA Yes96976 indel - - - A Yes97076 SNP G G G A Yes97138 SNP A G A A Yes97466 SNP G G G A Yes97983 SNP G G G A Yes98755 SNP T T T G Yes98939 SNP G A A G99024 SNP A A A G Yes99101 SNP A A A G Yes99351 SNP G A A A Yes99370 SNP G A A A Yes99373 SNP A A A C Yes99392 SNP T T T C Yes99418 SNP G G G A Yes
100347 4bp MS 4ATAC 2ATAC 2ATAC 3ATAC Yes Yes100363 2bp MS 29AT 15AT 26AT 24AT Yes Yes Yes Yes100904 SNP T T T C Yes101647 SNP G G A G Yes102104 SNP C C C T Yes102433 SNP C C C T Yes102481 1bp MS 6A 5A 5A 5A Yes103197 SNP G G A G Yes103342 SNP T T T C Yes103393 SNP A A T A Yes103580 SNP G G A G Yes103593 SNP C C C T Yes103783 SNP G G G T Yes103988 SNP T T T G Yes104049 SNP G G G A Yes104268 SNP G G A G Yes104444 SNP G C G G Yes104454 SNP C C C T Yes104495 1bp MS 24A 21A 23A 22A Yes Yes Yes Yes104643 SNP C T C C Yes105456 SNP A A A G Yes105803 rs9268117 SNP G G G C Yes106266 SNP C C T C Yes107160 SNP T T T C Yes107416 SNP G A A A Yes107714 SNP G G G C Yes108003 indel - - - A Yes108223 SNP A G G G Yes108412 SNP A A A G Yes108554 SNP A G A A Yes108681 SNP T T T A Yes108787 SNP A A A G Yes108958 SNP T T T C Yes109129 indel - - - T Yes109382 1bp MS 8T 8T 7T 8T Yes109807 1bp MS 4G 4G 4G 3G Yes109826 SNP C T T T Yes109841 SNP T T T C Yes109954 indel GA GA GA - Yes110007 rs9279556 4bp MS 7ATTT 7ATTT 7ATTT 5ATTT Yes110166 SNP T T C T Yes110507 SNP G C G G Yes110543 SNP T A A A Yes110545 2bp MS 13AT 5AT 5AT 27AT Yes Yes110638 SNP A A A C Yes110778 SNP A A A G Yes110980 SNP A G A A Yes111320 SNP A G G G Yes111326 SNP G T T G111556 SNP A A A G Yes111565 indel A A - A Yes111567 SNP A A G A Yes111596 SNP G G G A Yes111737 SNP G G G A Yes111781 SNP G G A G Yes111834 SNP A A A G Yes111921 SNP A A A C Yes112459 SNP G A G G Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
112587 SNP C C C G Yes112745 SNP T T T C Yes112800 SNP A A A G Yes113134 SNP C C C T Yes113362 SNP C C C T Yes113526 SNP T T T C Yes113610 SNP T G T T Yes113664 SNP A G A A Yes113693 SNP T T T C Yes113771 SNP C C G C Yes113772 indel C C - C Yes113894 SNP A A G A Yes114371 SNP G G G A Yes114416 SNP A A A G Yes114462 4bp MS 1ACAA 1ACAA 1ACAA 2ACAA Yes114589 indel - - - A Yes115856 SNP A A G A Yes116112 1bp MS 7T 8T 7T 7T Yes116600 SNP C G G G Yes116680 SNP T T T C Yes116889 SNP C6orf10 exon A G A A Yes117582 rs7775397 SNP C6orf10 exon T T T G Yes117837 rs3749966 SNP C6orf10 exon T T T C Yes118101 SNP C6orf10 exon A G A A Yes118736 SNP C6orf10 intron G G A G Yes119429 SNP C6orf10 intron C C T C Yes119443 2bp MS C6orf10 intron 11CA 8CA 8CA 12CA Yes Yes119466 1bp MS C6orf10 intron 9C 22C 20C 15C Yes Yes Yes Yes119798 SNP C6orf10 intron T T T G Yes119960 1bp MS C6orf10 intron 18T 19T 19T 17T Yes Yes120003 SNP C6orf10 intron C C C T Yes120519 SNP C6orf10 intron C C C T Yes122018 SNP C6orf10 intron T A A A Yes122022 SNP C6orf10 intron A A A G Yes122050 SNP C6orf10 intron A C A A Yes122361 SNP C6orf10 intron A A T A Yes122650 SNP C6orf10 intron C C T C Yes122875 SNP C6orf10 intron G A G G Yes122934 indel C6orf10 intron - CAAA CAAA CAAA Yes123135 SNP C6orf10 intron G G G A Yes124420 SNP C6orf10 intron C C C T Yes124841 SNP C6orf10 intron -24 A T A A Yes125041 SNP C6orf10 intron T T T G Yes125139 indel C6orf10 intron - - - TTTG Yes125324 SNP C6orf10 intron A G A A Yes125562 SNP C6orf10 intron C C C G Yes125674 1bp MS C6orf10 intron 11A 11A 11A 12A Yes125704 SNP C6orf10 intron T T G T Yes125802 SNP C6orf10 intron C C C T Yes125828 1bp MS C6orf10 intron 4T 4T 4T 5T Yes125833 1bp MS C6orf10 intron 14A 14A 15A 12A Yes Yes125937 complex indel C6orf10 intron - - - CCATAG Yes126091 indel C6orf10 intron - - CATCATCAT - Yes126101 rs5875354 3bp MS C6orf10 intron 9ATA 8ATA 13ATA 15ATA Yes Yes Yes Yes126468 SNP C6orf10 intron C C C T Yes126656 SNP C6orf10 intron +122 G G G A Yes126736 SNP C6orf10 intron +22 A A A T Yes126873 SNP C6orf10 intron -94 A G A A Yes127248 SNP C6orf10 intron C C C T Yes127465 1bp MS C6orf10 intron 12T 11T 11T 10T Yes Yes127599 complex indel C6orf10 intron - - - TTTCTTT Yes127644 SNP C6orf10 intron A A A T Yes127651 1bp MS C6orf10 intron 9T 9T 9T 8T Yes127824 SNP C6orf10 intron C C C G Yes127831 SNP C6orf10 intron A T T T Yes128055 SNP C6orf10 intron A A A T Yes128188 SNP C6orf10 intron G G G T Yes128336 SNP C6orf10 intron C C C T Yes128351 4bp MS C6orf10 intron 4AAGA 5AAGA 5AAGA 5AAGA Yes128528 1bp MS C6orf10 intron 9T 9T 9T 11T Yes128710 SNP C6orf10 intron A A A G Yes128816 SNP C6orf10 intron T T T C Yes128820 SNP C6orf10 intron C C C A Yes128893 SNP C6orf10 intron C C C T Yes129005 indel C6orf10 intron A A A - Yes129090 SNP C6orf10 intron A A A G Yes129094 SNP C6orf10 intron A A A G Yes129443 SNP C6orf10 intron A G A A Yes129460 SNP C6orf10 intron T T T C Yes129541 SNP C6orf10 intron G C G G Yes129581 SNP C6orf10 intron A A A T Yes129870 SNP C6orf10 intron G G G A Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
130148 SNP C6orf10 intron A A A G Yes130450 SNP C6orf10 intron G G G A Yes130450 SNP C6orf10 intron G G G A Yes130462 SNP C6orf10 intron C C C T Yes130462 SNP C6orf10 intron C C C T Yes131199 indel C6orf10 intron - - - GATT Yes131199 indel C6orf10 intron - - - GATT Yes131269 SNP C6orf10 intron C C C A Yes131269 SNP C6orf10 intron C C C A Yes131414 SNP C6orf10 intron C C C T Yes131414 SNP C6orf10 intron C C C T Yes131581 SNP C6orf10 intron G G G A Yes131581 SNP C6orf10 intron G G G A Yes131770 indel C6orf10 intron - - - ATTT Yes131770 indel C6orf10 intron - - - ATTT Yes131946 SNP C6orf10 intron G T G G Yes131946 SNP C6orf10 intron G T G G Yes131947 1bp MS C6orf10 intron 13T 14T 14T 14T Yes131947 1bp MS C6orf10 intron 13T 14T 14T 14T Yes132012 SNP C6orf10 intron C C C T Yes132012 SNP C6orf10 intron C C C T Yes132020 SNP C6orf10 intron C C C T Yes132020 SNP C6orf10 intron C C C T Yes132232 SNP C6orf10 intron C C C T Yes132232 SNP C6orf10 intron C C C T Yes132400 SNP C6orf10 intron T T T C Yes132400 SNP C6orf10 intron T T T C Yes132418 SNP C6orf10 intron T T T G Yes132418 SNP C6orf10 intron T T T G Yes132468 1bp MS C6orf10 intron 6T 6T 6T 8T Yes132468 1bp MS C6orf10 intron 6T 6T 6T 8T Yes132562 SNP C6orf10 intron A G A A Yes132562 SNP C6orf10 intron A G A A Yes132565 SNP C6orf10 intron G G G A Yes132565 SNP C6orf10 intron G G G A Yes132596 SNP C6orf10 intron G G G A Yes132596 SNP C6orf10 intron G G G A Yes132693 SNP C6orf10 intron G A G G Yes132693 SNP C6orf10 intron G A G G Yes132744 SNP C6orf10 intron G G T G Yes132744 SNP C6orf10 intron G G T G Yes132768 1bp MS C6orf10 intron 20A 22A 20A 15A Yes Yes132768 1bp MS C6orf10 intron 20A 22A 20A 15A Yes Yes132789 indel C6orf10 intron T T T - Yes132789 indel C6orf10 intron T T T - Yes132897 SNP C6orf10 intron A G A A Yes132897 SNP C6orf10 intron A G A A Yes132944 SNP C6orf10 intron T T T C Yes132944 SNP C6orf10 intron T T T C Yes133130 indel C6orf10 intron - - - C Yes133130 indel C6orf10 intron - - - C Yes133131 1bp MS C6orf10 intron 17T 16T 18T 16T Yes Yes133131 1bp MS C6orf10 intron 17T 16T 18T 16T Yes Yes133154 SNP C6orf10 intron G G G A Yes133154 SNP C6orf10 intron G G G A Yes133191 SNP C6orf10 intron C C C T Yes133191 SNP C6orf10 intron C C C T Yes133421 SNP C6orf10 intron C C C A Yes133421 SNP C6orf10 intron C C C A Yes133526 indel C6orf10 intron AT AT AT - Yes133526 indel C6orf10 intron AT AT AT - Yes133607 SNP C6orf10 intron C C C T Yes133607 SNP C6orf10 intron C C C T Yes133759 indel C6orf10 intron CTT CTT CTT - Yes133759 indel C6orf10 intron CTT CTT CTT - Yes133767 SNP C6orf10 intron A A A C Yes133767 SNP C6orf10 intron A A A C Yes133924 SNP C6orf10 intron A A A - Yes133944 SNP C6orf10 intron G G G A Yes133951 SNP C6orf10 intron C C C A Yes134230 SNP C6orf10 intron C C C T Yes134330 SNP C6orf10 intron C C C A Yes134393 SNP C6orf10 intron C C C T Yes134394 indel C6orf10 intron AGCTT AGCTT - TGTCAGCTT Yes Yes134429 2bp MS C6orf10 intron 7GT 7GT 8GT 7GT Yes134587 SNP C6orf10 intron C C C T Yes134666 SNP C6orf10 intron A G A A Yes134923 2bp MS C6orf10 intron 9TA 8TA 8TA 10TA Yes Yes134943 indel C6orf10 intron - - - T Yes135040 SNP C6orf10 intron A A G A Yes135075 SNP C6orf10 intron C C C T Yes135197 SNP C6orf10 intron C C C T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
135689 SNP C6orf10 intron G G G A Yes135745 SNP C6orf10 intron C C C T Yes135840 SNP C6orf10 intron A A A C Yes135905 SNP C6orf10 intron C C C T Yes136027 SNP C6orf10 intron G G G T Yes136221 SNP C6orf10 intron G G G A Yes136343 SNP C6orf10 intron G G A G Yes136357 SNP C6orf10 intron A A A G Yes136587 SNP C6orf10 intron A A A G Yes136749 SNP C6orf10 intron A A A G Yes136867 SNP C6orf10 intron C C C T Yes136996 SNP C6orf10 intron T T T C Yes137021 indel C6orf10 intron T T T - Yes137025 SNP C6orf10 intron A A A C Yes137099 SNP C6orf10 intron T T T C Yes137447 SNP C6orf10 intron C C C G Yes137449 SNP C6orf10 intron G G G A137765 SNP C6orf10 intron T T T C Yes137915 SNP C6orf10 intron A A A T Yes138026 SNP C6orf10 intron A A A G Yes138081 SNP C6orf10 intron G G G A Yes138093 SNP C6orf10 intron C C C T Yes138189 SNP C6orf10 intron A G G G Yes138194 SNP C6orf10 intron T T T C Yes138229 indel C6orf10 intron G G G - Yes138363 SNP C6orf10 intron C C C T Yes138424 SNP C6orf10 intron A A A C Yes138438 SNP C6orf10 intron G A G G Yes138473 SNP C6orf10 intron A A G A Yes138486 SNP C6orf10 intron A A A G Yes138871 SNP C6orf10 intron A A A G Yes138876 SNP C6orf10 intron A A A G Yes139030 complex indel C6orf10 intron - - - - Yes139259 SNP C6orf10 intron A G A A Yes139384 SNP C6orf10 intron A A A G Yes139519 SNP C6orf10 intron C C C A Yes139619 SNP C6orf10 intron C C C T Yes139799 SNP C6orf10 intron G A A A Yes Yes139899 SNP C6orf10 intron G G G A Yes140104 SNP C6orf10 intron A A A G Yes140104 SNP C6orf10 intron T T T G Yes140513 SNP C6orf10 intron C C C T Yes140745 SNP C6orf10 intron A T A A Yes140828 SNP C6orf10 intron C C C G Yes141315 SNP C6orf10 intron T A T T Yes141355 SNP C6orf10 intron G G G A Yes141633 SNP C6orf10 intron G A G A141730 SNP C6orf10 intron T C C C Yes141753 SNP C6orf10 intron C C G C Yes141767 SNP C6orf10 intron C C C T Yes141947 SNP C6orf10 intron G G A G Yes142284 SNP C6orf10 intron A G G G Yes142507 SNP C6orf10 intron T A T T Yes142657 SNP C6orf10 intron A G G G Yes142967 SNP C6orf10 intron T C C C Yes143085 SNP C6orf10 intron G A G G Yes143166 SNP C6orf10 intron G T T T Yes143389 SNP C6orf10 intron T G T T Yes143520 1bp MS C6orf10 intron 3T 2T 3T 2T143524 SNP C6orf10 intron G A G A143734 SNP C6orf10 intron C T C C Yes143807 SNP C6orf10 intron C C C A Yes143901 SNP C6orf10 intron A G A A Yes143972 SNP C6orf10 intron A A G A Yes144017 SNP C6orf10 intron C T T T Yes144160 SNP C6orf10 intron T T T C144281 SNP C6orf10 intron G T T T Yes144446 SNP C6orf10 intron T C T T Yes144494 SNP C6orf10 intron T T C T Yes144590 SNP C6orf10 intron T C T T Yes144969 SNP C6orf10 intron T G T T Yes145210 SNP C6orf10 intron T C T T Yes145337 SNP C6orf10 intron T A T T Yes145357 SNP C6orf10 intron G G G A Yes145645 SNP C6orf10 intron C T C C Yes145697 SNP C6orf10 intron A G G G Yes145723 SNP C6orf10 intron T C T T Yes145763 SNP C6orf10 intron G G G A Yes145795 SNP C6orf10 intron C C A C Yes145999 SNP C6orf10 intron G A A A Yes146169 SNP C6orf10 intron C T C C Yes146613 SNP C6orf10 intron +55 C C C T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
147055 SNP C6orf10 intron C T T T Yes147100 complex indel C6orf10 intron - - - - Yes147115 SNP C6orf10 intron A A G A Yes147160 SNP C6orf10 intron A G A A Yes147338 SNP C6orf10 intron -12 T T G T Yes147365 SNP C6orf10 intron -39 A G A A Yes147601 SNP C6orf10 intron G A A A Yes147684 indel C6orf10 intron +94 AG - AG AG Yes147770 SNP C6orf10 intron +9 G G T G Yes147953 SNP C6orf10 intron -150 T T C T Yes148054 SNP C6orf10 intron T C C T148248 SNP C6orf10 intron G T G G Yes148495 SNP C6orf10 intron C T C C Yes148607 SNP C6orf10 intron A C A A Yes148804 indel C6orf10 intron AACT AACT - AACT Yes148976 1bp MS C6orf10 intron 10T 9T 10T 10T Yes148986 SNP C6orf10 intron T A T T Yes149130 SNP C6orf10 intron G A G G Yes149233 SNP C6orf10 intron A C C C Yes149371 SNP C6orf10 intron C C T C Yes149567 SNP C6orf10 intron A G A A Yes149670 SNP C6orf10 intron C G G C149849 SNP C6orf10 intron A C A A Yes149947 SNP C6orf10 intron C C T C Yes149985 SNP C6orf10 intron G A G G Yes149993 SNP C6orf10 intron C G C C Yes150013 SNP C6orf10 intron A T A A Yes150086 SNP C6orf10 intron G A G G Yes150356 SNP C6orf10 intron G G G C Yes150432 SNP C6orf10 intron T C T T Yes150607 SNP C6orf10 intron G A G G Yes150964 SNP C6orf10 intron A A A T Yes150978 SNP C6orf10 intron G G T G Yes150981 SNP C6orf10 intron G A G G Yes151127 SNP C6orf10 intron A G A A Yes151258 SNP C6orf10 intron T T C T Yes151407 SNP C6orf10 intron G A G G Yes151765 SNP C6orf10 intron G A G G Yes151772 SNP C6orf10 intron G A G G Yes151834 SNP C6orf10 intron C C A C Yes151851 complex indel C6orf10 intron - - - - Yes151878 indel C6orf10 intron T T - T Yes151989 SNP C6orf10 intron G C G G Yes152012 1bp MS C6orf10 intron 11T 12T 11T 11T Yes152089 SNP C6orf10 intron T T T C Yes152131 SNP C6orf10 intron A G A A Yes152181 SNP C6orf10 intron A A T A Yes152184 SNP C6orf10 intron T A T T Yes152265 SNP C6orf10 intron A G A A Yes152311 SNP C6orf10 intron T C C T152315 SNP C6orf10 intron A G G A152402 SNP C6orf10 intron C C T C Yes152466 SNP C6orf10 intron T G T T Yes152494 SNP C6orf10 intron C T C C Yes152554 SNP C6orf10 intron C C T C Yes152753 SNP C6orf10 intron C T C C Yes152812 SNP C6orf10 intron G A G G Yes152992 SNP C6orf10 intron G C G G Yes153217 SNP C6orf10 intron C T C C Yes153279 SNP C6orf10 intron C G C C Yes153453 indel C6orf10 intron A - A A Yes153561 SNP C6orf10 intron A T A A Yes153593 SNP C6orf10 intron T C T T Yes153765 SNP C6orf10 intron G A G G Yes153774 SNP C6orf10 intron T C T T Yes153778 SNP C6orf10 intron G A G G Yes153854 SNP C6orf10 intron G A G G Yes154081 indel C6orf10 intron A - A A Yes154085 complex indel C6orf10 intron - - - - Yes154097 SNP C6orf10 intron G C G G Yes154127 SNP C6orf10 intron C T C C Yes154237 indel C6orf10 intron CTTT - CTTT CTTT Yes154338 SNP C6orf10 intron G G A G Yes154343 SNP C6orf10 intron G G T G Yes154392 SNP C6orf10 intron G A G G Yes154810 SNP C6orf10 exon A G A A Yes154850 2bp MS C6orf10 intron -27 21AC 21AC 20AC 19AC Yes Yes154923 SNP C6orf10 intron -100 T G G T155087 SNP C6orf10 intron A G A A Yes155253 SNP C6orf10 intron A C C A155381 SNP C6orf10 intron A A G A Yes155419 1bp MS C6orf10 intron 2C 4C 2C 2C Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
155966 indel C6orf10 intron A A A - Yes156033 SNP C6orf10 intron A G G A156156 SNP C6orf10 intron +96 G A G G Yes156263 SNP C6orf10 exon A G G A156314 SNP C6orf10 intron -42 G T G G Yes156593 SNP C6orf10 intron C T T C156815 SNP C6orf10 intron T G T T Yes156911 SNP C6orf10 intron T G T T Yes157079 SNP C6orf10 intron T C C T157250 SNP C6orf10 intron G G A G Yes157289 SNP C6orf10 intron T C T T Yes157730 SNP C6orf10 intron T C T T Yes157763 SNP C6orf10 intron C T C C Yes157813 indel/SNP? C6orf10 intron ACCT CT-A ACCT ACCT Yes157893 SNP C6orf10 intron C G C C Yes157955 SNP C6orf10 intron G A A G158245 SNP C6orf10 intron G C G G Yes158351 SNP C6orf10 intron A G G A158486 SNP C6orf10 intron A C A A Yes158508 SNP C6orf10 intron C T C C Yes158548 indel C6orf10 intron GT GT GT - Yes158823 SNP C6orf10 intron C C C T158980 SNP C6orf10 intron A G A A Yes158982 SNP C6orf10 intron T G T T Yes159113 SNP C6orf10 intron G G G A Yes159169 SNP C6orf10 intron T G T T Yes159182 SNP C6orf10 intron G T G G Yes159198 SNP C6orf10 intron G A G G Yes159217 SNP C6orf10 intron G A A A Yes159509 SNP C6orf10 intron +146 G A G G Yes159952 SNP C6orf10 intron G A G G Yes160133 rs1265754 SNP C6orf10 exon T T T A Yes160289 SNP C6orf10 intron -139 G A G G Yes160472 SNP C6orf10 intron G A G G Yes160663 SNP C6orf10 intron C G C C Yes161192 indel C6orf10 intron G - G G Yes161470 SNP C6orf10 intron T A T T Yes161566 SNP C6orf10 intron C T C C Yes161583 indel C6orf10 intron CC TG CC CC Yes161811 SNP C6orf10 intron T G T T Yes161985 rs926593 SNP C6orf10 intron A A A G Yes162099 SNP C6orf10 intron A C C A162131 SNP C6orf10 intron C A C C Yes162420 SNP C6orf10 intron T T G T Yes162463 SNP C6orf10 intron G A G G Yes162531 SNP C6orf10 intron G A G G Yes162703 SNP C6orf10 intron T C T T Yes162860 SNP C6orf10 intron T C C T163411 SNP C6orf10 intron A A C A Yes163449 indel C6orf10 intron G G - G Yes163579 SNP C6orf10 intron T C T T Yes163702 SNP C6orf10 intron +117 T G T T Yes163824 SNP C6orf10 exon G A G G Yes163888 SNP C6orf10 intron -31 C C T C Yes163974 SNP C6orf10 intron -117 G G G A Yes164311 SNP C6orf10 intron T C T T Yes164504 SNP C6orf10 intron A G A A Yes164548 SNP C6orf10 intron G C G G Yes164787 SNP C6orf10 intron T G T T Yes164907 SNP C6orf10 intron C C A C Yes165024 1bp MS C6orf10 intron 12T 12T 11T 11T165085 SNP C6orf10 intron G A G G Yes165133 SNP C6orf10 intron A G A A Yes165177 SNP C6orf10 intron A G A A Yes165213 SNP C6orf10 intron G A G G Yes165446 SNP C6orf10 intron A T A A Yes165723 SNP C6orf10 intron A A G A Yes165739 SNP C6orf10 intron C G C C Yes165766 SNP C6orf10 intron C T C C Yes165795 SNP C6orf10 intron T C T T Yes165829 SNP C6orf10 intron G A A A Yes165877 SNP C6orf10 intron T C T T Yes166281 indel C6orf10 intron - C - - Yes166308 SNP C6orf10 intron C T C C Yes166355 SNP C6orf10 intron T C C T166391 1bp MS C6orf10 intron 14T 13T 13T 13T Yes166548 SNP C6orf10 intron G A G G Yes166564 SNP C6orf10 intron T T T G Yes166639 SNP C6orf10 intron A G G A166656 SNP C6orf10 intron G G A G Yes166841 SNP C6orf10 intron G G A G Yes166860 SNP C6orf10 intron G G C G Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
167129 SNP C6orf10 intron G A G G Yes167248 SNP C6orf10 intron G A G G Yes167256 SNP C6orf10 intron C A A C167308 SNP C6orf10 intron T T T C Yes167412 SNP C6orf10 intron C T C C Yes167431 SNP C6orf10 intron C G C C Yes167593 SNP C6orf10 intron C G C C Yes167904 SNP C6orf10 intron A G G A168316 SNP C6orf10 intron T A T T Yes168320 SNP C6orf10 intron T A T T Yes168487 SNP C6orf10 intron C A C C Yes168497 complex indel C6orf10 intron - - TCCACC - Yes168527 SNP C6orf10 intron G G A G Yes168796 SNP C6orf10 intron T C C T168798 SNP C6orf10 intron T C C T168940 SNP C6orf10 intron G A A A Yes169055 SNP C6orf10 intron G G A G Yes169082 SNP C6orf10 intron GG GG TT GG Yes169095 SNP C6orf10 intron C G G C169185 SNP C6orf10 intron C A C C Yes169241 SNP C6orf10 intron A G A A Yes169328 SNP C6orf10 intron C T C C Yes169406 complex indel C6orf10 intron - - - - Yes169455 SNP C6orf10 intron CT TC CT CT Yes169542 SNP C6orf10 intron T C T T Yes169581 SNP C6orf10 intron C T C C Yes169588 SNP C6orf10 intron A C A A Yes169769 1bp MS C6orf10 intron 14T 11T 11T 14T169909 SNP C6orf10 intron G T G G Yes169979 SNP C6orf10 intron C A C C Yes169998 SNP C6orf10 intron C T T C170101 SNP C6orf10 intron C C G C Yes170107 SNP C6orf10 intron G G G A Yes170232 complex indel C6orf10 intron - - - - Yes170633 indel C6orf10 intron G - - G170760 complex indel C6orf10 intron - - - -170932 SNP C6orf10 intron CA CG TG CA Yes Yes171043 SNP C6orf10 intron T C C T171081 indel C6orf10 intron G - G G Yes171125 SNP C6orf10 intron G A G G Yes171187 SNP C6orf10 intron C C T C Yes171326 SNP C6orf10 intron G A A G171392 1bp MS C6orf10 intron 14T 14T 16T 12T Yes Yes171550 SNP C6orf10 intron G G A G Yes171622 SNP C6orf10 intron T C T T Yes171665 SNP C6orf10 intron G A G G Yes171949 SNP C6orf10 intron G G A G Yes171956 SNP C6orf10 intron C C A C Yes171960 SNP C6orf10 intron T T T G Yes172006 SNP C6orf10 intron T C T T Yes172042 SNP C6orf10 intron C G C C Yes172103 SNP C6orf10 intron C G G C172176 SNP C6orf10 intron C C T C Yes172424 SNP C6orf10 intron T T C T Yes172465 SNP C6orf10 intron G G T G Yes172530 SNP C6orf10 intron A C C A172689 SNP C6orf10 intron T T G T Yes172761 SNP C6orf10 intron C T T C172838 SNP C6orf10 intron T T C T Yes172864 SNP C6orf10 intron C T T C173053 SNP C6orf10 intron T C C T173064 SNP C6orf10 intron G A A G173253 SNP C6orf10 intron C G G C173422 1bp MS C6orf10 intron 15T 17T 17T 16T Yes Yes173576 SNP C6orf10 intron G A G G Yes173664 SNP C6orf10 intron T C T T Yes173675 indel C6orf10 intron CTTAT CTTAT CTTAT - Yes173725 SNP C6orf10 intron T C T T Yes173916 SNP C6orf10 intron +50 C T T C173920 SNP C6orf10 intron A C A A Yes174084 SNP C6orf10 intron -29 A G G A174308 SNP C6orf10 intron C T T C174377 indel C6orf10 intron TTCT - TTCT TTCT Yes174422 SNP C6orf10 intron G A A G174485 SNP C6orf10 intron A G A A Yes175059 SNP C6orf10 intron A A G A Yes175178 SNP C6orf10 intron A G A A Yes175813 SNP C6orf10 intron T C C C Yes175836 SNP C6orf10 intron T T C T Yes176086 SNP C6orf10 intron G A G G Yes176602 SNP C6orf10 intron A A G A Yes177564 SNP C6orf10 intron C A C A
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
177721 SNP C6orf10 intron A A C A Yes177874 indel C6orf10 intron AAAT - AAAT -178046 SNP C6orf10 intron G A A A Yes178321 SNP C6orf10 intron T C T C178423 indel C6orf10 intron - ACATA ACATA ACATA Yes178842 SNP C6orf10 intron C T C T178882 SNP C6orf10 intron C C T C Yes178919 SNP C6orf10 intron T T C T Yes179978 SNP C6orf10 intron -83 A G A G180504 SNP C6orf10 intron C C A C Yes180531 1bp MS C6orf10 intron 10T 9T 9T 9T Yes180904 SNP C6orf10 intron A A G A Yes180951 1bp MS C6orf10 intron 11A 10A 10A 10A Yes180971 SNP C6orf10 intron C C T C Yes180995 SNP C6orf10 intron G A A A Yes181092 SNP C6orf10 intron G A A A Yes181268 SNP C6orf10 intron T C C C Yes181396 SNP C6orf10 intron A G G G Yes181589 SNP C6orf10 intron G A A A Yes181743 SNP C6orf10 intron C C A C Yes181850 SNP C6orf10 intron C T T T Yes182013 SNP C6orf10 intron G G G A Yes182070 indel C6orf10 intron - TGAG TGAG TGAG Yes182158 SNP C6orf10 intron C A C A182161 SNP C6orf10 intron G A G A182286 SNP C6orf10 intron T T C T Yes182496 SNP C6orf10 intron G A G A182616 SNP C6orf10 intron A G G G Yes182691 SNP C6orf10 intron G A G A182697 SNP C6orf10 intron G G T G Yes182791 SNP C6orf10 intron A A G A Yes182951 indel C6orf10 intron - CCAT - CCAT182986 SNP C6orf10 intron T C T T Yes183108 SNP C6orf10 intron C T C T183144 3bp MS C6orf10 intron 11TAT 6ATA 8TAT 7TAT Yes Yes Yes Yes183311 SNP C6orf10 intron A C C C Yes183359 SNP C6orf10 intron G C C C Yes183385 SNP C6orf10 intron C C T C Yes184191 SNP C6orf10 intron C T C T184245 SNP C6orf10 intron C T C T184303 SNP C6orf10 intron G A A A Yes184433 SNP C6orf10 intron T C C C Yes184625 2bp MS C6orf10 intron 8GT 8GT 9GT 8GT Yes184701 SNP C6orf10 intron T A A A Yes184760 SNP C6orf10 intron T C T C184867 SNP C6orf10 intron C T C T185125 1bp MS C6orf10 intron 9T 10T 9T 10T185360 SNP C6orf10 intron G A G A185429 SNP C6orf10 intron T C T C185880 SNP C6orf10 intron C C T C Yes186063 SNP C6orf10 intron G G A G Yes186109 SNP C6orf10 intron C T C T186486 SNP C6orf10 intron A G G G Yes186500 SNP C6orf10 intron T C C C Yes186531 1bp MS C6orf10 intron 19A 23A 17A 23A Yes Yes186563 SNP C6orf10 intron T C C C Yes186624 SNP C6orf10 intron T C T T Yes186635 SNP C6orf10 intron C G C C Yes186639 SNP C6orf10 intron C C G C Yes186645 SNP C6orf10 intron A G A A Yes186777 SNP C6orf10 intron G A A A Yes186901 SNP C6orf10 intron T C C C Yes186948 SNP C6orf10 intron A A C A Yes187122 SNP C6orf10 intron C T C C Yes187176 SNP C6orf10 intron T T A T Yes187239 SNP C6orf10 intron A A G A Yes187365 SNP C6orf10 intron A A G G187408 SNP C6orf10 intron G A A A Yes187473 SNP C6orf10 intron T T C C187540 SNP C6orf10 intron T C T T Yes187680 SNP C6orf10 intron A T T A187900 SNP C6orf10 intron C A C C Yes187937 1bp MS C6orf10 intron 7A 6A 7A 7A Yes188287 SNP C6orf10 intron T C C C Yes188295 SNP C6orf10 intron A G A A Yes188308 SNP C6orf10 intron C T C C Yes188312 SNP C6orf10 intron G A G G Yes188398 SNP C6orf10 intron C G C C Yes188469 SNP C6orf10 intron A G G G Yes188664 1bp MS C6orf10 intron 13T 15T 15T 14T Yes Yes188704 indel C6orf10 intron G - G G Yes188735 SNP C6orf10 intron G G G A Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
188793 SNP C6orf10 intron G G G A Yes189035 SNP C6orf10 intron C T T T Yes189156 1bp MS C6orf10 intron 6T 7T 6T 7T189165 SNP C6orf10 intron A G G G Yes189237 SNP C6orf10 intron G G G A Yes189262 SNP C6orf10 intron C A C A189263 SNP C6orf10 intron C C C T Yes189295 SNP C6orf10 intron A A G A Yes189310 1bp MS C6orf10 intron 16T 15T 14T 16T Yes Yes189394 SNP C6orf10 intron T C C C Yes189470 SNP C6orf10 intron C G C C Yes189567 SNP C6orf10 intron A G A G189572 SNP C6orf10 intron C T C T189669 SNP C6orf10 intron A G A G189717 SNP C6orf10 intron A G G G Yes189773 SNP C6orf10 intron C C C T Yes189815 SNP C6orf10 intron A G A A Yes189884 SNP C6orf10 intron A C A A Yes189893 SNP C6orf10 intron G G G A Yes189899 SNP C6orf10 intron T C C C Yes189913 SNP C6orf10 intron T G G G Yes189954 SNP C6orf10 intron T T T C Yes190016 SNP C6orf10 intron G A A A Yes190301 SNP C6orf10 intron +120 A A A C Yes190314 3bp MS C6orf10 intron +94 4CTT 4CTT 3CTT 4CTT Yes190432 SNP C6orf10 exon T C T T Yes190701 SNP C6orf10 intron -145 C G C C Yes190718 SNP C6orf10 intron T T G T Yes190735 SNP C6orf10 intron G T G G Yes190879 SNP C6orf10 intron C G G G Yes190881 SNP C6orf10 intron G G A G Yes190938 SNP C6orf10 intron G A A A Yes190966 SNP C6orf10 intron G A G G Yes191011 SNP C6orf10 intron T C C C Yes191017 1bp MS C6orf10 intron 21A 28A 24A 27A Yes Yes Yes Yes191311 2bp MS C6orf10 intron 18GT 13GT 13GT 12GT Yes Yes191531 SNP C6orf10 intron A G G G Yes191533 SNP C6orf10 intron G G A G Yes191535 SNP C6orf10 intron G A G G Yes191537 2bp MS C6orf10 intron 4GA 6GA 5GA 14GA Yes Yes Yes Yes191713 SNP C6orf10 intron G G G A Yes191856 SNP C6orf10 intron G G G A Yes192025 SNP C6orf10 intron T T C T Yes192068 2bp MS C6orf10 intron +138 5AG 5AG 3AG 5AG Yes192141 SNP C6orf10 intron +74 T A A A Yes192291 1bp MS C6orf10 intron -44 2A 2A 3A 2A Yes192587 SNP C6orf10 intron C T C C Yes192640 SNP C6orf10 intron C C G C Yes192674 SNP C6orf10 intron G G G A Yes192700 SNP C6orf10 intron C C T C Yes192718 SNP C6orf10 intron A A A G Yes192724 SNP C6orf10 intron G G A G Yes192877 SNP C6orf10 intron C C C A Yes193008 SNP C6orf10 intron +64 A A T A Yes193030 SNP C6orf10 intron +42 G A A A Yes193034 indel C6orf10 intron +38 G - G G Yes193099 SNP C6orf10 exon A G A A Yes193279 SNP C6orf10 intron A A A G Yes193576 1bp MS C6orf10 intron 12T 13T 12T 1T Yes Yes193589 indel C6orf10 intron AAACT AAACT AAACT - Yes193665 1bp MS C6orf10 intron 17T 17T 15T 28T Yes Yes193761 SNP C6orf10 intron G A G G Yes193894 SNP C6orf10 intron T G T T Yes193919 SNP C6orf10 intron T C C C Yes193924 SNP C6orf10 intron C C T C Yes193974 indel C6orf10 intron - - - ATCT Yes194161 SNP C6orf10 intron +44 G A G A194217 SNP C6orf10 exon G G A G Yes194386 1bp MS C6orf10 intron +95 8T 8T 7T 8T Yes194481 complex indel C6orf10 intron - - - - Yes194716 2bp MS C6orf10 intron 1GT 6GT 1GT 1GT Yes194728 2bp MS C6orf10 intron 10AT 17AT 18AT 10AT Yes Yes194825 SNP C6orf10 intron T G G T194928 SNP C6orf10 intron G C G G Yes194942 SNP C6orf10 intron T T C T Yes195163 1bp MS C6orf10 intron 9A 9A 8A 9A Yes195177 SNP C6orf10 intron G C G G Yes195179 2bp MS C6orf10 intron 9GA 7GA 6GA 9GA Yes Yes195244 SNP C6orf10 intron G A A G195450 SNP C6orf10 intron T T A T Yes195506 1bp MS C6orf10 intron 9T 9T 10T 9T Yes195535 SNP C6orf10 intron C T C C Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
195625 SNP C6orf10 intron A A A G Yes195897 SNP C6orf10 intron +123 C T C T196097 SNP C6orf10 exon G A G A196196 rs2050189 SNP C6orf10 exon T T T C Yes196446 SNP (C6orf10) promoter +241 C T C T196474 rs6913471 SNP (C6orf10) promoter +269 T A T T Yes196617 indel (C6orf10) promoter +412 - TGT - TGT196621 indel (C6orf10) promoter +416 GCC - GCC -196658 SNP (C6orf10) promoter +453 A G A A Yes196728 rs3117110 SNP (C6orf10) promoter +523 C C C T Yes196788 SNP (C6orf10) promoter +583 G A G G Yes197206 SNP (C6orf10) promoter +1001 G A G G Yes197423 rs3117109 SNP (C6orf10) promoter +1218 C C C T Yes197424 rs3129944 SNP (C6orf10) promoter +1219 C C C G Yes197870 SNP A G A A Yes197905 SNP G A G G Yes198025 SNP T C T T Yes198271 SNP C T C C Yes198571 rs9279614 2bp MS 21GT 21GT 22GT 14GT Yes Yes198639 SNP C T C C Yes198681 SNP C T C C Yes198718 SNP T C T T Yes199089 SNP G G G A Yes199191 SNP A C A A Yes199243 SNP C A C C Yes199374 SNP C G C G199570 SNP T A T T Yes199647 SNP TG CA TG TG Yes199788 SNP A A A G Yes199819 SNP G C G G Yes199891 SNP G G G A Yes199921 SNP T T T C Yes199936 SNP A G A A Yes200168 SNP A G A A Yes200238 SNP T C T T Yes200266 SNP T C T C200348 SNP C T C C Yes200421 SNP A G A A Yes200425 SNP G A G G Yes200434 SNP C T C C Yes200537 SNP T C T T Yes200928 SNP C T C C Yes201283 SNP A G A A Yes201360 SNP C T C C Yes201525 SNP G T G G Yes201560 3bp MS 3AAG 2AAG 3AAG 3AAG Yes201604 SNP A G A A Yes201981 SNP C A A A Yes201995 SNP G T G G Yes202066 SNP T G T T Yes202147 SNP C G C C Yes202219 SNP A G A A Yes202241 SNP T T T G Yes202443 SNP T G T T Yes202960 SNP T A T T Yes202964 indel TGAT - TGAT TGAT Yes203004 SNP A T A A Yes203020 indel GTGTTTT GTGTTTT GTGTTTT - Yes203043 SNP G A G G Yes203189 SNP A G A A Yes203214 SNP AT TG AT AT Yes203253 SNP G A G G Yes203324 SNP A G A G203346 SNP A C A A Yes203568 SNP A G A A Yes203624 2bp MS 4TA 4TA 4TA 3TA203832 SNP C T C C Yes204042 SNP C T C C Yes204084 SNP CA TG CA CA Yes204301 SNP A G A A Yes204383 SNP T C T T Yes204449 SNP C T C C Yes204650 SNP C A C C Yes204697 SNP A G A A Yes204861 SNP T A T A204977 3bp MS 3TTAA 4TTAA 3TTAA 3TTAA Yes205019 SNP C G C C Yes205023 SNP G A G G Yes205246 SNP G A G G Yes205642 SNP T C T T Yes206050 SNP A G A A Yes206113 rs3117103 SNP A A A T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
206127 SNP T C T T Yes206267 SNP A G A A Yes206328 SNP C T C C Yes206502 SNP C A C C Yes206592 SNP A G A A Yes206663 SNP C T C C Yes206940 SNP C A C C Yes207332 SNP G A G G Yes207424 SNP A C A A Yes207839 SNP T C T T Yes208457 SNP C A C C Yes208529 1bp MS 10T 11T 11T 11T Yes208547 SNP C A C C Yes208643 SNP G G C G Yes208776 SNP G G A G Yes209124 SNP T C T C209152 1bp MS 6C 7C 6C 6C Yes209173 SNP C C C T Yes209201 1bp MS 7C 6C 7C 7C Yes209222 SNP C T C C Yes209294 SNP A C A C209723 SNP A G A G210147 SNP G G G A Yes210251 SNP T C T T Yes210421 SNP G G G A Yes210432 1bp MS 5G 3G 5G 5G Yes210469 SNP G A G A210475 SNP A A G A Yes210484 complex indel - - - - Yes Yes Yes Yes210985 SNP A G A A Yes211201 SNP C A C A211281 1bp MS 18T 20T 18T 18T Yes212164 SNP G A G G Yes212242 SNP A G A A Yes213724 SNP (HCG23) promoter -1122 T C T T Yes214760 rs3129950 SNP (HCG23) promoter -86 G G G C Yes214790 SNP (HCG23) promoter -56 C T C C Yes214829 rs3117099 SNP (HCG23) promoter -17 G G G A Yes214845 SNP (HCG23) promoter -1 T C T T Yes214974 1bp MS HCG23 exon 4A 5A 4A 4A Yes215073 SNP HCG23 exon G A G A215249 SNP HCG23 intron A A A G Yes215502 SNP HCG23 intron T A T T Yes215681 SNP HCG23 intron G A G G Yes216323 SNP HCG23 intron G C G G Yes216818 SNP HCG23 intron G A G G Yes216841 1bp MS HCG23 intron 23A 24A 23A 17A Yes Yes216876 SNP HCG23 intron A G A A Yes216877 1bp MS HCG23 intron 10A 10A 11A 9A Yes Yes
217672 SNP HCG23 BTNL2 intron exon C T C C Yes
218382 rs3129953 SNP BTNL2 exon C C C T Yes218977 SNP BTNL2 intron +105 T G T G219776 SNP BTNL2 intron T T T C Yes220088 SNP BTNL2 intron C T C C Yes220377 SNP BTNL2 exon T C T T Yes220405 SNP BTNL2 exon C T C C Yes220516 SNP BTNL2 exon T C T T Yes220917 SNP BTNL2 intron A G A A Yes221228 SNP BTNL2 intron G G A G Yes221453 indel BTNL2 intron CA - CA CA Yes222141 SNP BTNL2 intron A G A G222401 SNP BTNL2 intron T C T C223259 1bp MS BTNL2 intron 9T 11T 9T 9T Yes223580 SNP BTNL2 intron A A G A Yes224285 SNP BTNL2 intron A G A A Yes224340 SNP BTNL2 intron A T A A Yes224358 SNP BTNL2 intron G T G G Yes224410 SNP BTNL2 intron T C T T Yes224560 SNP BTNL2 intron T A T T Yes224650 SNP BTNL2 intron T C T T Yes224877 SNP BTNL2 intron C A C C Yes224998 indel BTNL2 intron C - C C Yes224999 SNP BTNL2 intron A T A A Yes225002 indel BTNL2 intron A - A A Yes225025 SNP BTNL2 intron G G G A Yes225076 SNP BTNL2 intron C T C C Yes225091 complex indel BTNL2 intron - - - - Yes225134 SNP BTNL2 intron T T C C225136 SNP BTNL2 intron CA TG CA CA Yes225169 SNP BTNL2 intron A G A A Yes225266 1bp MS BTNL2 intron 14A 14A 14A 16A Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
225287 SNP BTNL2 intron A G G G Yes225563 1bp MS BTNL2 intron 33A 30A 37A 20A Yes Yes Yes Yes226066 SNP BTNL2 intron +74 G A G G Yes227194 SNP BTNL2 intron +96 T C T T Yes227262 SNP BTNL2 intron +38 A G A A Yes227413 SNP BTNL2 exon T C T T Yes227757 SNP BTNL2 intron G C G G Yes227847 SNP BTNL2 intron C T C C Yes228197 SNP BTNL2 intron A G A A Yes228493 SNP BTNL2 intron C T C C Yes230117 1bp MS BTNL2 intron 7T 6T 7T 7T Yes230163 1bp MS BTNL2 intron 10T 8T 10T 11T Yes Yes230175 1bp MS BTNL2 intron 10T 7T 10T 10T Yes230185 complex indel BTNL2 intron - - - - Yes Yes Yes Yes230288 SNP BTNL2 intron G T G G Yes230391 SNP BTNL2 intron T G T T Yes230721 SNP BTNL2 intron C G C C Yes230880 1bp MS BTNL2 intron 12T 11T 12T 12T Yes231185 SNP BTNL2 intron A A A G Yes231212 SNP BTNL2 intron A T A A Yes231870 SNP BTNL2 intron C G C C Yes231920 SNP BTNL2 intron G A G G Yes231942 SNP BTNL2 intron A C A A Yes231961 SNP BTNL2 intron A T A A Yes231964 SNP BTNL2 intron G A G G Yes232014 SNP BTNL2 intron G A G G Yes232021 SNP BTNL2 intron C T T T Yes232238 indel BTNL2 intron CA - CA CA Yes232285 SNP BTNL2 intron G A G G Yes232335 SNP BTNL2 intron G A G G Yes232386 rs3129959 SNP BTNL2 intron A A A T Yes232563 SNP BTNL2 intron C A C C Yes232766 SNP BTNL2 intron C T C C Yes232938 SNP BTNL2 intron G A G G Yes233107 SNP BTNL2 intron C T C C Yes233208 SNP BTNL2 intron +117 C T C C Yes233336 SNP BTNL2 exon C T C C Yes233378 SNP BTNL2 promoter +16 C T C C Yes233472 SNP BTNL2 promoter +110 T G T T Yes233522 SNP BTNL2 promoter +190 C T C C Yes233651 SNP BTNL2 promoter +289 C T C C Yes233706 SNP BTNL2 promoter +344 C G C C Yes233998 SNP BTNL2 promoter +636 T A T T Yes234060 SNP BTNL2 promoter +698 C T C C Yes234129 SNP BTNL2 promoter +767 A G A A Yes234178 SNP BTNL2 promoter +816 T A T T Yes234311 indel BTNL2 promoter +949 CATG - CATG -234414 SNP BTNL2 promoter +1052 C C C G Yes234420 SNP BTNL2 promoter +1058 T C T T Yes234437 complex indel BTNL2 promoter +1075 - - - - Yes234476 complex indel BTNL2 promoter +1114 - - - - Yes Yes Yes Yes235235 indel A - A A Yes235238 1bp MS 13A 5A 11A 13A Yes Yes235275 indel AACA - AACA AACA Yes235340 2bp MS 7GT 9GT 7GT 7GT Yes235383 SNP T C T T Yes235430 SNP T C T T Yes235462 SNP T G T T Yes235473 SNP C T C C Yes235536 SNP C T C T235541 SNP T A T T Yes235578 SNP A G A A Yes235607 SNP A G A A Yes235627 SNP G A G G Yes235643 SNP G A G G Yes235697 SNP T C T T Yes235835 SNP A G A A Yes235891 SNP G C G G Yes235912 complex indel - - - - Yes235926 SNP GA AG GA GA Yes235929 SNP C G C C Yes235993 SNP G G G A Yes236055 SNP T C T T Yes236099 SNP C T C C Yes236292 SNP T C T T Yes236350 SNP T C C C Yes236800 SNP G A G G Yes236818 SNP A A A G Yes236872 SNP A G A A Yes237010 indel TA - TA -237325 SNP C T C C Yes237327 SNP C G C G
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
237392 SNP T A T T Yes237395 SNP G A G G Yes237428 SNP A G A A Yes237436 SNP G A G G Yes237440 SNP G G G C Yes237470 SNP C A C C Yes237651 SNP C G C C Yes237820 SNP T C T T Yes237880 indel - C - - Yes237891 SNP G G G C Yes237985 SNP G C G G Yes238054 SNP A T A A Yes238072 SNP T C C T238083 SNP C T T C238347 SNP T A T T Yes238464 1bp MS 3A 3A 3A 1A Yes238550 SNP T T T C Yes238898 indel - - - GGAAAGAA Yes238983 indel G G G - Yes239228 SNP C C C G Yes239257 SNP T T T C Yes239368 SNP A A A G Yes239485 1bp MS 4A 4A 4A 3A Yes239490 5bp MS 3AAAAT 3AAAAT 2AAAAT 3AAAAT Yes239674 SNP G G A G Yes239732 SNP G G A A239832 SNP G G G T Yes239847 SNP T T T C Yes239870 SNP T T T G Yes239873 SNP T T T C Yes239880 SNP C C A C Yes239931 SNP T T T G Yes239965 SNP A A A C Yes239984 SNP G G G A Yes240034 SNP G G G T Yes240065 SNP T T T G Yes240112 SNP T T T A Yes240257 SNP G G G C Yes240461 SNP G G G A Yes240482 SNP G G G T Yes240701 SNP C C C T Yes240967 SNP G G G A Yes241124 SNP C C C T Yes241151 SNP C T T T Yes241301 SNP A A A C Yes241345 SNP G G A A241425 SNP A T A A Yes241524 SNP T T T C Yes241723 SNP G G G A Yes242023 SNP G G A G Yes242077 SNP A A G G242094 SNP A A A G Yes242197 SNP G G G A Yes242229 SNP C C C A Yes242277 SNP A A A G Yes242374 SNP C C T T242406 SNP C C C A Yes242497 SNP C C C T Yes242685 SNP C C C T Yes243007 SNP A A A G Yes243042 1bp MS 10T 10T 10T 11T Yes243096 SNP G G A G Yes243120 SNP T T T C Yes243131 SNP T T T C Yes243179 SNP T T C C243244 SNP C C T C Yes243268 SNP G G G A Yes243324 SNP A A A G Yes243332 SNP T T T C Yes243589 SNP C C T T243846 SNP G G G A Yes243903 SNP T T T A Yes244001 SNP A G A A Yes244005 SNP GA AG GA GA Yes244008 indel AAGG - AAGG AAGG Yes244057 SNP G G G A Yes244377 SNP A A A C Yes244405 SNP G G G T Yes244434 SNP T C T T Yes244485 SNP C C C T Yes244769 SNP T T C T Yes244900 SNP T T C T Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
244933 SNP C C C T Yes245171 SNP C C T C Yes245199 rs2213580 SNP T T T C Yes245334 rs3135366 SNP T T T C Yes245880 SNP A A C A Yes245930 SNP C C T T246000 SNP T C C C Yes246016 SNP G A A A Yes246137 SNP G G C C246170 SNP A A A G Yes246273 SNP A A A G Yes246372 SNP T T T G Yes246622 SNP T T C T Yes246821 SNP T T T C Yes246957 SNP C C C T Yes247026 1bp MS 21A 24A 13A 20A Yes Yes Yes Yes247050 indel C C C - Yes247214 SNP C C T C Yes247384 SNP C C C T Yes247540 SNP A A G G247761 1bp MS 12A 11A 12A 20A Yes Yes247781 2bp MS 14TA 13TA 24TA 24TA Yes Yes247836 SNP T T T C Yes247954 indel AA AA AA - Yes248160 SNP G G G A Yes248913 1bp MS 9T 9T 9T 10T Yes248936 SNP G G G A Yes248937 1bp MS 11A 11A 11A 25A Yes249202 SNP T T T C Yes249250 SNP T T T C Yes249320 SNP T T C C249536 SNP C C C T Yes249565 SNP A A C A Yes249604 SNP C C C A Yes249640 SNP T T C T Yes249894 SNP C C G C Yes250618 SNP T T T C Yes250660 indel - - - G Yes250687 SNP A A A G Yes250720 SNP T T T C Yes250758 SNP G G A G Yes250890 1bp MS 17A 17A 15A 16A Yes Yes250975 SNP A A A C Yes251199 SNP C C C T Yes251247 SNP C C C T Yes251507 SNP G G G A Yes251575 SNP G G G A Yes251698 SNP T T C T Yes252127 SNP T T T G Yes252230 SNP T T G G252303 SNP C T T T Yes252318 SNP A A A T Yes252360 SNP A A A T Yes252388 SNP A A A G Yes252497 SNP A A A G Yes252604 SNP T C C C Yes252719 SNP G G A A252771 1bp MS 5C 5C 6C 5C Yes252939 SNP A A A G Yes252975 SNP C C C T Yes253112 SNP A A G G253137 SNP A A A G Yes253168 SNP A A A G Yes253277 SNP G G G T Yes253345 complex indel - - - -253567 SNP C C G G253592 SNP G A G G Yes253626 SNP T T C C253711 SNP G G G A Yes253928 SNP G G T T253971 SNP G G A G Yes254065 SNP G G T T254238 SNP T T C C254239 SNP 14AC 14AC 2AC 11AC Yes Yes254398 SNP A A A C Yes254470 SNP A A G A Yes254480 SNP G G C C254888 SNP A A G G255249 SNP A A C C255334 SNP G G G A Yes255361 SNP A A T T255434 SNP A A C A Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
255467 SNP C C G C Yes255483 indel - - GTTAA GTTAA255527 SNP A A A G Yes255540 1bp MS 6A 6A 5A 6A Yes255559 SNP T T T G Yes255614 complex indel - - - - Yes Yes255663 SNP C C C T Yes255710 SNP A A A G Yes255780 SNP A A G G255846 SNP CC CC CT TC Yes Yes255875 SNP C A C C Yes255933 SNP G A G G Yes255949 SNP C C C G Yes256025 SNP T T T C Yes256473 SNP A A A G Yes256521 SNP A A G G256530 SNP T T C C256758 SNP A A G G256776 SNP T T C T Yes257208 SNP G G G A257226 SNP G G A A257522 1bp MS 6T 6T 7T 7T257553 SNP T T C C257627 SNP G G G C Yes257767 SNP G G A G Yes257905 SNP T T C T Yes257949 SNP A A G G257951 SNP C C T T258220 SNP T T T A Yes258222 SNP C C C T Yes258517 SNP A A G A Yes258533 SNP G G C G Yes258578 SNP A A G G258684 SNP T T G G258805 1bp MS 8G 8G 7G 7G258914 SNP C C T T259129 SNP G G A A259153 SNP C C T T259375 SNP T T C T Yes259381 SNP T T C T Yes259467 SNP T G T T Yes259930 1bp MS 4T 4T 4T 5T Yes260088 indel C C - C Yes260089 2bp MS 6AC 9AC 2AC 8AC Yes Yes Yes Yes260360 SNP T T T G Yes260639 SNP C C C T Yes260646 SNP T T A T Yes260722 2bp MS 7AC 7AC 6AC 6AC260750 SNP A A A G Yes260755 SNP C C G C Yes260772 SNP C C G C Yes260800 SNP T T C C260842 SNP A A A G Yes260920 SNP C C C T Yes260927 SNP C C G C Yes261084 SNP C C A C Yes261566 SNP G G A G Yes261585 SNP T T T G Yes261733 SNP G A G G Yes261751 SNP C G G G Yes261769 SNP G G G T Yes261783 SNP G G G C Yes261899 SNP G G T G Yes262069 SNP C C G C Yes262378 SNP C C A C Yes262400 1bp MS 4A 4A 5A 5A262528 SNP T C T T Yes262572 SNP C A A A Yes262755 1bp MS 17A 22A 31A 19A Yes Yes Yes Yes262792 SNP T G G G Yes262807 SNP C C C T Yes262953 1bp MS (HLA-DRA) promoter -1435 8A 8A 9A 8A Yes263049 SNP (HLA-DRA) promoter -1339 C C A C Yes263119 rs9268632 SNP (HLA-DRA) promoter -1269 C C C G Yes263180 SNP (HLA-DRA) promoter -1208 G G A G Yes263237 SNP (HLA-DRA) promoter -1151 A A G G263286 SNP (HLA-DRA) promoter -1102 C C T C Yes263318 rs9268636 SNP (HLA-DRA) promoter -1070 C C C A Yes263411 SNP (HLA-DRA) promoter -977 G G T G Yes263514 SNP (HLA-DRA) promoter -874 A A G G263550 SNP (HLA-DRA) promoter -838 T T C T Yes263555 1bp MS (HLA-DRA) promoter -833 22A 20A 23A 40A Yes Yes Yes Yes
Table A1.2 : Continued.
Positiona rs no.b Type Gene Gene regionc QBL (18.2AH)
SSTO (44.1AH)
PGF (7.1AH)
COX (8.1AH)
QBL Only?
SSTO Only?
PGF Only?
COX Only?
263595 rs9357142 SNP (HLA-DRA) promoter -793 G G G A Yes263611 rs9268641 SNP (HLA-DRA) promoter -777 C C C T Yes263822 rs9268642 SNP (HLA-DRA) promoter -566 C C C T Yes263877 rs3129872 SNP (HLA-DRA) promoter -511 A A A T Yes264026 rs2395179 SNP (HLA-DRA) promoter -362 A A A G Yes264034 rs2395180 SNP (HLA-DRA) promoter -354 T T T G Yes264128 rs2395181 SNP (HLA-DRA) promoter -260 G G G C Yes264157 rs3129873 SNP (HLA-DRA) promoter -231 G G G C Yes264164 rs3129874 SNP (HLA-DRA) promoter -224 T T T C Yes264192 rs3129875 SNP (HLA-DRA) promoter -196 T T T C Yes264433 SNP HLA-DRA exon A A C C264736 SNP HLA-DRA intron G G G A Yes264768 SNP HLA-DRA intron C C A A264932 1bp MS HLA-DRA intron 9A 9A 11A 9A Yes265221 SNP HLA-DRA intron A A A G Yes265251 SNP HLA-DRA intron G G C C265321 SNP HLA-DRA intron G G G A Yes265459 SNP HLA-DRA intron A A A C Yes265566 SNP HLA-DRA intron A A A G Yes265631 SNP HLA-DRA intron G G G A Yes265641 SNP HLA-DRA intron C C T C Yes265770 SNP HLA-DRA intron A G G G Yes265780 SNP HLA-DRA intron G G A G Yes265782 SNP HLA-DRA intron C C T C Yes265784 SNP HLA-DRA intron G G G A Yes265913 1bp MS HLA-DRA intron 10A 10A 10A 9A Yes265966 SNP HLA-DRA intron C C C A Yes266029 SNP HLA-DRA intron G G A A266208 SNP HLA-DRA intron C C C T Yes266254 SNP HLA-DRA intron G A G A266380 SNP HLA-DRA intron A A G G266505 SNP HLA-DRA intron T T C C266511 SNP HLA-DRA intron C C T T266861 SNP HLA-DRA intron +88 C C T C Yes266934 SNP HLA-DRA intron +15 T T T C Yes266939 SNP HLA-DRA intron +10 T T T C Yes267300 SNP HLA-DRA intron -106 C C T C Yes267415 SNP HLA-DRA intron G G G A Yes267440 SNP HLA-DRA intron A A G G267665 SNP HLA-DRA intron +21 C C T T267711 SNP HLA-DRA exon G G A G Yes267759 SNP HLA-DRA exon C C A A268031 SNP HLA-DRA intron -54 C C C T Yes268100 SNP HLA-DRA intron T T T G Yes268247 SNP HLA-DRA intron -10 C C T T268370 SNP HLA-DRA exon G G T T268450 SNP HLA-DRA intron -28 A A G A Yes268557 SNP HLA-DRA intron T T C C268570 SNP HLA-DRA intron G G C G Yes268719 complex indel HLA-DRA intron - - - - Yes269004 complex indel HLA-DRA intron - - - -269120 SNP HLA-DRA intron +41 G G T T269127 SNP HLA-DRA intron +34 A A C A Yes269130 SNP HLA-DRA intron +31 T T C C269212 SNP HLA-DRA exon A A G G269271 SNP HLA-DRA exon G G A A269298 rs1131541 SNP HLA-DRA exon T T T A Yes269303 SNP HLA-DRA exon T T A T Yes269312 SNP HLA-DRA exon C C T C Yes269324 rs1051336 SNP HLA-DRA exon G G G A Yes269542 SNP HLA-DRA exon T T T A Yes
a - Relative position is given as the distance in bp from the start of the alignment, 2,025bp telomeric of RNF5 . This number is only used as a reference, and the precise value will vary between individuals according to the presence and size of indels and microsatellite alleles.
b - rs numbers are given for polymorphisms investigated in this study.
d - The values given for promoter and intron polymorphisms are in bp either upstream (negative value) or downstream (positive value) of the nearest exon and relative to the sequence alignment. Values are only given for polymorphisms up to 1500bp (for the promoter) or 150bp (for the intron) from the nearest exon.
c - SNP: Single nucleotide polymorphism, MS: Microsatellite (number of repeats are given), indel: insertion or deletion, complex indel: large (>5bp) insertion or deletion.
Sporadic inclusion body myositis in Japanese is associated
with the MHC ancestral haplotype 52.1
Adrian Phillip Scott a,*, Richard James Nigel Allcock a, Frank Mastaglia b,
Ichizo Nishino c, Ikuya Nonaka c, Nigel Laing d
a School of Surgery and Pathology, M504, UWA, Stirling Highway, Nedlands, WA 6009, Perth WA, Australiab Australian Neuromuscular Research Institute, Centre for Neuromuscular and Neurological Disorders, University of Western Australia, Perth, Australia
c National Centre of Neurology and Psychiatry (NCNP), Tokyo, Japand West Australian Institute for Medical Research, Centre for Medical Research, University of Western Australia, B Block, QEII Medical Centre,
Nedlands 6009, Perth WA, Australia
Received 26 October 2005; received in revised form 27 January 2006; accepted 8 February 2006
Abstract
In Caucasians, sporadic inclusion body myositis has been associated with the MHC ancestral haplotypes; HLA-A1, B8, DR3 (8.1AH) and
HLA-B35, DR1 (35.2AH). It is not known whether these haplotypes carry susceptibility for the disease in other ethnic groups. We report here
the results of HLA-B and -DRB1 typing using a high-resolution sequence-based technique in a cohort of 31 Japanese patients with definite
sIBM. Patient allele frequencies were 40.3% for HLA-B*5201 (10.7% in controls: p!0.001) and 37.1% for HLA-DRB1*1502 (10% in
controls: p!0.001). Both alleles were found together as part of a conserved haplotype (52.1AH) at a frequency of 37.1% in patients (8.4% in
controls: p!0.001). This is the first description of a haplotypic MHC association with sporadic inclusion body myositis in Japanese patients.
These findings indicate that different MHC ancestral haplotypes are associated with sIBM in different ethnic groups and further emphasize
the importance of genetic factors in this condition.
q 2006 Elsevier B.V. All rights reserved.
Keywords: Major histocompatibility complex; Sporadic inclusion body myositis; Japanese; MHC; sIBM
1. Introduction
Sporadic inclusion body myositis (sIBM) is the most
common myopathy over the age of 50 years and is more
prevalent in Caucasians than in other ethnic groups [1,2]. In
Caucasian populations sIBM is associated with alleles of the
human leukocyte antigen (HLA) class II genes, found within
the major histocompatibility complex (MHC) on human
chromosome 6. One characteristic feature of the MHC
region is the strong linkage disequilibrium that exists
between different loci, blocks of which are inherited
together as a series of ancestral haplotypes (AHs) [3,4].
While there are a number of diseases that show an
association with specific HLA alleles [5], this does not
0960-8966/$ - see front matter q 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.nmd.2006.02.002
* Corresponding author. Tel.: C61 8 9346 2734; fax: C61 8 9346 2891.
E-mail address: [email protected] (A.P. Scott).
necessarily imply a direct role for those alleles in the
development of the disease. Instead, the associations may
arise from linkage disequilibrium between the HLA alleles
and linked disease susceptibility alleles in the MHC region.
As sIBM is most prevalent in Caucasian populations,
most studies have focused on this ethnic group [2]. Garlepp
et al. (1994) [6] found that in a Caucasian cohort of Western
Australian sIBM patients, the condition was associated with
HLA-DR3 and with the extended 8.1AH (HLA-A1, B8,
DRB3*0101, DRB1*0301, DQB1*0201). A number of
other studies have since confirmed the association between
sIBM and alleles characteristic of the 8.1AH, including
HLA-DRB3*0101, DQB1*0201 and DRB1*0301 [7–10].
More recently, the 35.2AH, characterized by HLA-A11,
B35, DRB1*0101, DQB1*0501, has also been shown to be
associated with sIBM in Caucasians [7].
Studies on the genetic association of sIBM in other
ethnic groups are rare. In the Japanese, research has so far
been limited to case studies of individual patients [11,12].
In one case study of two Japanese sisters with sIBM, it
Neuromuscular Disorders 16 (2006) 311–315
www.elsevier.com/locate/nmd
Table 1
HLA-B Allele frequencies for Japanese sIBM patients and a healthy
population
Alleles % Frequency (n) p-value OR (95%CI)
Patients
(2nZ62)
Controlsa
(2nZ742)
0702 3.2 (2) 6.5 (48) 0.419 0.48 (0.11–2.03)
1301 1.6 (1) 1.5 (11) 1 1.09 (0.14–8.57)
1501 3.2 (2) 8.7 (65) 0.155 0.35 (0.08–1.45)
1518 1.6 (1) 1.5 (11) 1 1.09 (0.14–8.57)
3501 9.7 (6) 7.6 (56) 0.465 1.24 (0.51–3.00)
3901 3.2 (2) 4.4 (33) 0.123 0.72 (0.17–3.06)
4001 1.6 (1) 4.2 (31) 0.504 0.38 (0.05–2.80)
A.P. Scott et al. / Neuromuscular Disorders 16 (2006) 311–315312
was found that both patients carried HLA-DRB1*1502
and 0405. However, because of the small sample size and
familial relationship of the patients it was impossible to
draw any conclusions regarding HLA-associations from
this study [12].
In the present study, we have carried out HLA-B and
-DRB1 typing in a larger cohort of Japanese sIBM patients.
As neither the 8.1AH nor 35.2AH are found in normal
Japanese populations [13], we sought to determine whether
the disease is associated with other specific alleles in
the MHC and whether such alleles are also common to
Caucasian sIBM patients.
4002 3.2 (2) 8.6 (64) 0.223 0.35 (0.08–1.48)4402 3.2 (2) 0.4 (3) 0.050 8.21 (1.35–50.10)
4403 6.5 (4) 8.7 (65) 0.812 0.72 (0.25–2.04)
4601 1.6 (1) 3.6 (27) 0.716 0.43 (0.06–3.25)
4801 1.6 (1) 3 (22) 1 0.54 (0.07–4.05)
5101 8.1 (5) 7.7 (57) 0.807 1.05 (0.41–2.73)
5201 40.3 (25) 10.7 (79) !0.001 5.67 (3.24–9.91)
5401 3.2 (2) 7.7 (57) 0.307 0.40 (0.09–1.68)
5502 1.6 (1) 1.9 (14) 1 0.85 (0.11–6.59)
5601 1.6 (1) 0.5 (4) 0.331 3.02 (0.33–27.48)
5801 1.6 (1) 0.4 (3) 0.275 4.04 (0.41–39.41)
6701 1.6 (1) 1.1 (8) 0.516 1.50 (0.18–12.22)
2711 1.6 (1) 0 (0) 0.077 N/A
a Controls taken from Saito et al. (2000) [13].
Table 2
HLA-DRB1 Allele frequencies for Japanese sIBM patients and a healthy
population
Alleles % Frequency (n) p-value OR (95%CI)
Patients
(2nZ62)
Controlsa
(2nZ742)
0101 8.1 (5) 6.5 (48) 0.593 1.27 (0.49–3.31)
2. Patients and methods
2.1. Patient samples
Thirty one sIBM patients (18 males, 13 females) with
birthplaces across Japan were studied. These patients had
been diagnosed over a period of 7 years at the National
Centre for Neurology and Psychiatry in Tokyo. All patients
were elderly (69.5G6.8 years old) and had typical
pathological findings: rimmed vacuoles and inflammatory
cell infiltration, especially into the endomysium, surround-
ing the myofibres and sometimes into the myofibres.
2.2. HLA typing and statistical analysis
DNA was extracted from muscle biopsies, quantified
using a Nanodrop spectrophotometer (NanoDrop Technol-
ogies, USA) and stored at 4 8C.
High resolution sequence-based HLA-B, HLA-DRB1,
and HLA-DPB1 typing was performed on all samples [14].
The frequencies of these HLA alleles in the patient cohort
were compared with published Japanese population
frequencies. This control population consisted of 371
unrelated, healthy apheresis blood donors from central
Japan [13].
Patient ancestral haplotypes were determined by
comparing possible HLA-B and DRB1 combinations with
the normal population haplotypes for the Japanese [13].
Fisher’s exact test was used to evaluate statistical
significance, with p!0.05 taken as significant.
0405 9.7 (6) 11.5 (85) 0.835 0.828 (0.35–1.98)0410 4.8 (3) 1.8 (13) 0.119 2.851 (0.79–10.29)
0802 8.1 (5) 4 (30) 0.181 2.08 (0.78–5.57)
0803 4.8 (3) 8.1 (60) 0.467 0.58 (0.18–1.90)
1101 1.6 (1) 3.4 (25) 0.714 0.47 (0.06–3.53)
1202 3.2 (2) 1.5 (11) 0.265 2.22 (0.48–10.22)
1301 1.6 (1) 0.7 (5) 0.383 2.42 (0.28–21.01)
1302 9.7 (6) 7.7 (57) 0.620 1.29 (0.53–3.12)
1403 1.6 (1) 1.5 (11) 1 1.09 (0.14–8.58)
1406 1.6 (1) 1.8 (13) 1 0.92 (0.12–7.15)
1501 6.5 (4) 8.5 (63) 0.81 0.74 (0.26–2.11)
1502 37.1 (23) 10 (74) !0.001 5.32 (3.02–9.40)
1602 1.6 (1) 0.9 (7) 0.475 1.72 (0.21–14.22)
a Controls taken from Saito et al. (2000) [13].
3. Results
Our HLA-B and -DRB1 typing of the Japanese sIBM
patients revealed an association with two HLA-B alleles and
one HLA-DR allele. HLA-B*5201 was present in 21 out of
31 patients (68%), with an allele frequency of 40% among
patients (Table 1). This was a statistically significant (p!0.001) increase over the allele frequency of 10.7% for HLA-
B*5201 in the Japanese control population [13]. There was
also a statistically significant increase in patients of the
allele HLA-B*4402 (ORZ8.2, pZ0.05), although the allele
frequency in patients was still very low at 3% (2/62 alleles;
Table 1) and was found in only two of the 31 patients.
HLA-DRB1*1502 was the only DRB1 allele found to be
more frequent in patients than controls. The allele was
present in 65% (20/31) of patients, with an allelic frequency
of 37%, compared with 10% in controls (ORZ5.3, p!0.001; Table 2). We identified four and three individuals
homozygous for HLA-B*5201 and HLA-DRB1*1502,
Table 3
HLA-B/DRB1 haplotype frequencies for Japanese sIBM patients and a healthy population
Haplotype Patients (2nZ62) Controlsa(2nZ742) p-value OR (95%CI)
% Frequency (n) % Frequency (n)
B*0702, DR*0101 3.2 (2) 4 (30) 1 0.791 (0.18–3.39)
B*1301, DR*1202 1.6 (1) 0.5 (4) 0.331 3.025 (0.33–27.48)
B*1501, DR*1406 1.6 (1) 0.8 (6) 0.431 2.011 (0.24–16.97)
B*1501, DR*1501 1.6 (1) 0.5 (4) 0.331 3.02 (0.33–27.48)
B*3501, DR*0405 3.2 (2) 1 (7) 0.148 3.500 (0.71–17.22)
B*3501, DR*1501 4.8 (3) 0.8 (6) 0.026 6.237 (1.52–25.57)
B*4403, DR*1302 6.5 (4) 4.8 (36) 0.54 1.353 (0.47–3.93)
B*4601, DR*0803 1.6 (1) 0.9 (7) 0.475 1.721 (0.21–14.22)
B*5101, DR*0802 4.8 (3) 0.6 (4) 0.012 9.381 (2.05–42.90)
B*5201, DR*1502 37.1 (23) 8.4 (62) !0.001 6.468 (3.63–11.52)
B*5401, DR*0405 1.6 (1) 3.4 (25) 0.713 0.470 (0.06–3.53)
B*5401, DR*0803 1.6 (1) 0.5 (4) 0.331 3.025 (0.33–27.48)
a Controls taken from Saito et al. (2000) [13].
Table 4
HLA-DPB1 Allele frequencies for Japanese sIBM patients and a healthy
population
Alleles % Frequency (n) p-value OR (95%CI)
Patients
(2nZ60)
Controlsa
(2nZ742)
0201 11.7 (7) 25.2 (187) 0.018 0.392 (0.18–0.88)
A.P. Scott et al. / Neuromuscular Disorders 16 (2006) 311–315 313
respectively. All three individuals homozygous for HLA-
DRB1*1502 were also homozygous for HLA-B*5201.
The alleles HLA-DRB1*1502 and HLA-B*5201 were
found together in 65% (20/31) of the sIBM patients. The
DRB1*1502 allele is only carried as part of a haplotype in
the Japanese population along with HLA-B*5201 [13],
which corresponds to the previously identified 52.1AH [15].
There was a statistically significant increase in the
haplotype frequency of the 52.1AH in patients compared
the Japanese control population (37% vs 8%, ORZ6.5, p!0.001; Table 3). Two other haplotypes, defined by B*3501,
DR*1501 and B*5101, DR*0802 were also found at a
significantly increased frequency in sIBM patients (pZ0.026 and pZ0.012), although in both cases, the haplotype
frequencies were low (4.8%; Table 3).
The 52.1AH in the Japanese can be divided into three
sub-haplotypes defined by the HLA-DPB1 alleles 0201,
0501 and 0901 [13]. All three of these HLA-DP alleles
showed a statistically significant difference between patients
and controls (Table 4). Allele frequencies for HLA-
DPB1*0501 and 0901 were 33.3% and 35% in patients,
respectively, compared to 3.6% and 9.7% in controls.
Conversely, the allele frequency for HLA-DPB1*0201 was
statistically lower than the controls (11.7% vs 25.2%, pZ0.018, ORZ0.4; Table 4).
The frequency of each 52.1 sub-haplotype in patients
could not be determined, as most patients were hetero-
zygous for two of the DPB1 alleles associated with
the HLA-B*5201/DRB1*1502 haplotypes. Of the three
patients homozygous for HLA-B*5201, DR*1502, two
were homozygous for HLA-DP*0901, whilst the last was
heterozygous (HLA-DP*0501/0201).
0202 3.3 (2) 3.4 (25) 1 0.989 (0.23–4.28)0301 5 (3) 4.3 (32) 0.741 1.168 (0.35–3.93)
0401 1.7 (1) 5.8 (43) 0.243 0.276 (0.04–2.04)
0402 8.3 (5) 12.3 (91) 0.533 0.650 (0.25–1.67)
0501 33.3 (20) 3.6 (27) !0.001 13.241 (6.84–25.62)
0901 35 (21) 9.7 (72) !0.001 5.011 (2.80–8.98)
1901 1.7 (1) 0.3 (2) 0.208 6.271 (0.56–70.18)
a Controls taken from Saito et al. (2000) [13].
4. Discussion
This study has demonstrated that sIBM has a previously
unknown genetic association with HLA alleles in Japanese
patients. The associated alleles match those of an ancestral
haplotype found mainly in Asian populations, labelled the
52.1AH and defined by HLA-A*2402, Cw*1202, B*5201,
DRB1*1502, DQA1*0103, DQB1*0601 [15]. The 52.1AH
can be further divided into three sub-haplotypes defined by
their HLA-DPB1 allele-DPB1*0201, 0501, or 0901 [13].
The increased frequency of HLA-DPB1*0501 and 0901
in patients compared to controls reinforces the conclusion
that the 52.1AH is associated with sIBM. The decreased
frequency of HLA-DPB1*0201 does not exclude the
possibility that the equivalent 52.1 sub-haplotype is
increased, since the decrease in DPB1*0201 may be due
to the absence of other AHs carrying DPB1*0201 in the
patient group. HLA-DPB1*0201 is the most common HLA-
DPB1 allele amongst the normal Japanese population (allele
frequencyZ25.2%) and is found in many Japanese
haplotypes in addition to 52.1AH [13].
Tateyama (2003) [12] speculated in his case study of two
sisters that sIBM may have a genetic origin in the Japanese
and that HLA-analysis of a larger cohort of Japanese sIBM
patients was needed. Our results support the existence of a
genetic association factor for sIBM in Japanese patients.
Whilst this is the first time the 52.1AH has been associated
with sIBM in any population, the haplotype and its alleles
have also been associated with other diseases in Japanese
A.P. Scott et al. / Neuromuscular Disorders 16 (2006) 311–315314
populations. In the Japanese, the 52.1AH is associated with
susceptibility to Takayasu arteritis [16–18], ulcerative
colitis [19], abdominal aortic aneurysm with simultaneous
aorto-iliac occlusive disease [20], juvenile dermatomyositis
[21] and resistance to type 1 diabetes mellitus [22].
Similarly, the 8.1AH (HLA-B8, DR3), which is
associated with sIBM in the Caucasian population, is also
associated with multiple other diseases in Caucasians [23].
This includes two diseases associated with the 52.1AH in
the Japanese population; type 1 diabetes mellitus [24] and
juvenile dermatomyositis [25,26]. However, in the case of
type 1 diabetes mellitus, the 8.1AH and 52.1AHs have
opposite effects, despite their similar influence on sIBM
susceptibility. Specifically, 52.1AH has a protective effect
against type 1 diabetes mellitus in the Japanese [22],
whereas the 8.1AH has a predisposing effect in Caucasians
[24]. When the 8.1 and 52.1AHs are associated with similar
diseases in different ethnic groups, this implies a possible
common mechanism of disease aetiology.
All of the diseases associated with the 52.1AH differ
greatly in their pathology and clinical features. The two
most similar diseases are sIBM and juvenile dermato-
myositis, both of which are inflammatory myopathies.
Even so, there are clear differences between the diseases.
Clinically, juvenile dermatomyositis occurs within the first
two decades of life and is characterised by a skin rash
with the predominant lymphocytes comprising B cells and
CD4C T cells [27]. Conversely, sIBM patients generally
have an age of onset over 50 years, exhibit no skin rash
and CD8C T cells and macrophages are the predominant
lymphocytes in affected muscles [28]. Regardless of these
disparities, the common haplotypic association between
the two diseases suggests that there may be a shared
susceptibility allele within the MHC which, depending on
other genetic or environmental factors, may trigger either
sIBM or juvenile dermatomyositis through separate
effector mechanisms.
Three separate HLA haplotypes have now been shown to
be associated with sIBM in different ethnic groups—the
8.1AH and 35.2AH in Caucasians and now the 52.1AH in
Japanese. This finding represents a major step towards
isolating a possible universal susceptibility factor for
predisposition to sIBM. The linkage disequilibrium pre-
vailing in the MHC region has consistently hampered efforts
to study MHC-related diseases. With three currently known
haplotypes from two different ethnic groups, it may now be
possible to explore the genetic factors influencing sIBM in a
level of detail that was not previously feasible.
It has been proposed that the inflammatory component
of sIBM may be secondary to the accumulation of
abnormal, ‘foreignized’ proteins in sIBM muscle fibres
[29]. Our data and that of others on HLA associations [7]
in sIBM neither supports nor refutes such a hypothesis.
The fact that 8.1, 35.2 and 52.1AHs do not share any
common HLA alleles suggests that the genes responsible
for disease aetiology are not HLA genes and reside
elsewhere in the MHC. It is possible that the disease-
causing gene may not be involved in antigen presentation.
Previous research by Price et al. isolated sIBM suscep-
tibility in the Caucasian population to a region between
HOX12 and HLA-DRB1 [7]. The location of any sIBM
susceptibility allele in the Japanese 52.1AH cannot be
directly inferred from the results of this study, except to
say that it is in linkage disequilibrium with HLA-B*5201,
DRB1*1502, and DPB1*0501 and/or DPB1*0901.
Acknowledgements
We would like to acknowledge the clinicians across
Japan who collected the patient samples for this study. In
addition, we would also like to acknowledge Patricia Price
for helpful discussions during this study. This study was
supported by Australian National Health and Medical
Research Council (NH&MRC) Fellowship Grant 139170.
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