cpn thesis 2009 v3 title abstract synopsis table figures i - xxvi v3 201009

The Controversial Role of Cp in Chronic Infection and Vascular Disease.

Thesis Title: The Controversial Role of Chlamydia pneumoniae in Chronic Infection and Vascular Disease Version: 2

Author: Katerina Mitsakos

i

The Controversial Role of Chlamydia pneumoniae in Chronic Infection

and Vascular Disease in Australian Cohorts. Katerina Mitsakos

IOL-207 Infection




ii

THE CONTROVERSIAL ROLE OF CHLAMYDIA PNEUMONIAE

IN CHRONIC INFECTION AND VASCULAR DISEASE IN

AUSTRALIAN COHORTS

\

Katerina Mitsakos

A Thesis submitted for the Degree of Doctor of Philosophy

Faculty of Medicine

The University of Sydney

June 2009

Royal North Shore Hospital (PaLMS) Microbiology & Infectious Disease Department

Northern Clinical School, RNSH

University of Sydney




iii

DECLARATION

I declare that this academic dissertation is all my novel applied narration, except

where duly acknowledged.

Also, please note that the Appendices volume (not submitted) is still available

electronically if required, by request. My email is: [email protected].

I proclaim that no part of this thesis has been submitted for any other degree or

diploma at any other university.

Katerina Mitsakos

June 2009

mailto:[email protected]




iv

ACKNOWLEDGEMENTS

My research was based at Royal North Shore Hospital, PaLMS, Department of Microbiology and

Infectious Diseases. I wish to thank many dear friends and colleagues at RNSH, Microbiology &

Infectious Disease Department. A special deep thanks to a good friend, Chrissie Bell, for her support,

effortless contribution and help throughout my research.

My sincere gratitude reaches out to my two supervisors, Dr Bernard J Hudson and Dr Karl Baumgart

who introduced me to the ”world of research” and for entrusting me with the challenge of this study. I

am beholden to their continuous support, valuable time, and trust as having to juggle full time

employment and self-funding of this project, I would not have made it without their support and

donations.

My highest gratitude goes to Dr Peter Gunn, Head of Molecular Biology Department, Douglass Hanly

Moir (DHM), for introducing me to the molecular world, and offering his valuable expertise and time.

Thank you to Professor Helge Rasmussen, colleagues and staff, from the Department of Cardiology &

Surgery, for their support and for collaborating with providing specimens and data. In particular, a

special gratitude to Dr Cathy Thoo, for her precious collaboration and contribution, and for providing

critical plaque material which without, I would not have completed a crucial part of this study.

Thank you to my postgraduate coordinator Dr Diana Learoyd, Professor Michael Fields and staff at the

Northern Clinical School, Colling Institute, RNSH for their academic supportive encouragement and for

approval of funds toward the final stages of my thesis.

Thank you to Dr Peter Robertson, Prince of Wales Hospital, and staff for their collaboration,

contribution, and support in this study.

Thank you to Dr Karyn Byth-Wilson for their support, expertise, and knowledgeable insights in the

seroepidemiological analytical world of statistics.

A special thanks to Dr G R Rajasekariah, Dr Tony Smithyman and staff from CELLABS, for their warm

hospitality, collaboration, support, generosity, donations, expertise and valuable contribution toward the

study. They always ensured a ready supply of laboratory consumables, reagents and media, thus aiding

in the continuity of this research.

Thank you to the two ethics committees of Sydney Adventist Hospital and The Northern Sydney Area

Health for their valuable support and approval of this current project for the duration of conscription.

Very special thanks goes to Dr Deborah Hutton and staff from the Menzies School of Health Research,

Darwin, for her close interest and support in my work, expertise and alliance in providing me with

precious cell lines and Chlamydial live cultures.

I am indebted to my father for his support, encouragement and badgering to ensure completion and

attendance to my graduation ceremony… when it happens… I am grateful for his support, without him I

would not have been capable to afford this self-funding project. My two sisterly and eternal friends, Tas

and Rebecca, and my brother, Dmitri, who kept me buoyed and amused and made sure I was always

OK. Thanks for putting up with me during my “no social life” work – study period and for just being

there! A special deep thank you to my mother who inspired and spoilt me always with love, and her,

much loved by many, Mediterranean delicacies. My next book will be “Helene’s Scrumptious Cuisine”;

unfortunately she is not with us today... I miss you mum! This is for you, I promised! Last but not least, a sincere thank you to all my reviewers for their contribution, feedback and advice.




v

TABLE OF CONTENTS

page

ABSTRACT ix

SYNOPSIS xi

PRESENTATIONS xiii

LIST OF FIGURES xiv

LIST OF TABLES xvii

ABBREVIATIONS xxii

CHAPTER 1: Literature Review 1

1.1 Literature review 1

1.2 Microbiology 2

1.3 Laboratory Diagnosis of Cp Infection 6

1.4 Seroepidemiological Studies 16

1.5 Immunology: HSP & Infection with Cp 24

1.6 Association In Atherosclerosis 31

1.7 Universal Evidence 54

1.8 Plaque studies 58

1.9 Animal Models 64

1.10 Treatment of Human Infection with Cp 66

1.11 Statins & their antimicrobial effects 74

1.12 Vaccines 75

1.13 Literature Review – Conclusions & Future Directions 76

CHAPTER 2: Methodology 79

Current hypothesis to be investigated in this study 79

Proposed Investigation – Rationale for work to be undertaken 79

Aims of this Study 80

Project Design 81

Materials and Methods 81

Study Population 81

Ethical Proposals 83

CAD (CAD) Population Group 83

Healthy Control Group Population Study 83

Follow-up CAD Group 84

CAD Candidates 84

Risk profiles 85

Control Material and Method Validation 85




vi

Laboratory Methods 85

Clinical Samples 85

Cp Assays 86

Isolation of Cp 87

Proposed Optimal Recovery of Cp from clinical samples in chronic infection sites 92

PCR sequence analysis 94

Optimisation of PCR specificity 94

Optimisation of PCR sensitivity 95

PCR Assays 95

Methods & Clinical Sample Selection for PBMC and Carotid Plaque Study 101

Statistical Analyses 131

Results 133

Supervision and Support 133

CHAPTER 3: Epidemiology: Seroprevalence of Cp within Australian Population 134

Results 134

Seroepidemiology of 492 Australia Cohorts – Largest Study in Australia 135

Seroepidemiological kinetics of Cp by Age: 1 -90 years (N=492) 135

Seroepidemiological kinetics of Cp by Gender: 1 -90 years (N=492) 136

Seroepidemiological kinetics of the By Status (N=492) Sydney Cohorts 137

Seroepidemiological kinetics of Cp in Healthy Study Cohorts (N=308) 138

Kinetics of Cp seropositivity by Age in Age-Related Sydney Cohorts

(CAD=184; Normal=125; Ages 35 – 95 years; Total Status = 309) 140 Kinetics of Cp seropositivity by Gender in Age-Related Sydney Cohorts

(CAD=184; Normal=125; Ages 35 – 95 years Total Status = 309) 141

Kinetics of Cp seropositivity by Status in Age-Related Sydney Cohorts

(CAD=184; Normal=125; Ages 35 – 95 years Total Status = 309) 142

Methodological Disparity between Methodologies 145

Demonstration of Methodological Variation- Assay choice 148

Evaluation of Risk Profiles in CAD cohorts (N=184) 148

PCR results on PTCA balloon plaque samples 151

Discussion 153

Conclusive Seroepidemiological evidence: Key Points illustrated in this study 177

CHAPTER 4: Predictive value of Cp in cardiovascular disease (N= 160) 233

Results

Serological Status association to symptomatic CAD 234

Seroprevalence amongst Australian cohorts 234

Prediction to any complication or coronary event 234

Analyses of seroprevalence rates and cardiovascular causes; progression to a




vii

number of complications/ coronary events 235

Univariate risk predictors of mortality to CAD 235

Risk prediction of Mortality and future cardiac causes: Complications in pre-existing

CAD and/or acutely diagnosed Australian cohorts 236

Seroprevalence of Cp seromarkers in the Total CAD cohorts in relation to Status:

newly diagnosed and pre-existing CAD with progression to cardiac complications 245

Any prediction with Pre-existing CAD cohorts to disease complications 248

Discussion 253

CHAPTER 5: Cp prediction to a Cardiac Complication after adjustment for other

confounding risk factors (N=160) 259 Result

Antibodies to Cp 259

Circulating immune complexes to Cp 260

Relationship to establish a prediction to subsequent complication from First coronary

Event 260

Cp and seroprevalence to establish coronary risk factors 262

Multivariate Logistic Regression with backward stepwise variable selection for Cp

seropositivity in a treasure hunt to unveil independent influential predictors of cardiac

progression 264

Significance of circulating peripheral leucocytic blood cells in cardiac events 265

Relationship to establish coronary risk factor with pleiotropic effetcs of statins 267

Relationship to establish coronary risk factor with pleiotropic effetcs of alcohol

Consumption 268

Kinetic prediction of circulating Cp IgG and IgA immune complexes to cardiac

Complication within status 269

Discussion 270

Statistical Analyses : Cp seropositivity vs CAD vs Risk profiles vs disease progression 273

CHAPTER 6: Prediction to Cardiovascular Causes, future complications & survival

Rate 300

Results 300

Discussion 301

Statistical Analysis: Survival Analysis (First Fair to First Bad Complication) 303

CHAPTER 7: Existence or Lack of Cp within circulating PBMC 330

Results 330

Patients and specimens (N=17) 333

PCR of clinical specimens 333

Serology of the 17 CAD cohorts 334

Culture of the 17 CAD cohorts 335




viii

Comparison of PCR to culture of the 17 cohorts 335

Direct Detection of Cp in PBMC after Cell Culture 337

Lack of Detection: Reasons why could be endless 337

Discussion 338

Prevalence in other studies 342

Limitations of present study 343

CHAPTER 8: Existence or Lack of Cp within atherosclerotic plaque 351 Results 351

Seroprevalence of Cp in cardiovascular events in the 17 CAD cohorts 351

Profound Risk Profile evaluation of the 17 CAD cohorts 354

Comparison of plaque PCR and serology of the 17 CAD cohorts 354

Comparison of plaque PCR assays (LCx & FAM) performed 355

Comparison of PCR and culture of plaque samples 355

Comparative Univariate risk predictors of mortality from cardiovascular causes 356

Discussion 368

Relationship to risk profile of the 17 cohorts 374

Relationship to age and gender of the 17 cohorts 375

Relationship to smoking of the 17 cohorts 375

Relationship to season of the 17 cohorts 376

Limitations to standardization of laboratory methods 376

Blood sampling, extraction, and PCR targets 377

Study strength and limitations of this small study 380

Direct Detection of Cp in Plaque after Cell Culture 382

Other Studies and Flaws 383

.

CHAPTER 9: Conclusive evidence: Ambiguous Role of Cp in atherosclerosis 395

Reference to worldwide investigations 395

Evidence of circulation of Cp in Australia 411

Lack of Evidence of Detection of Cp 416

Seroepidemiological Evidence of Cp in Atherosclerosis 420

Evidence of C .pneumoniae in Peripheral Blood Mononuclear cells 422

Evidence of Cp in atherosclerotic lesions by culture 424

Evidence of Cp detection in Atherosclerotic lesions by PCR 425

Conclusion Summary 428

REFERENCES 432

APPENDICES – Available electronically if required.




ix

ABSTRACT

In this thesis, I attempt to determine the role of Chlamydia pneumoniae (Cp) in both the

pathogenesis and complications, in Australian cohorts, of Coronary Artery Disease (CAD) by

means of seroepidemiology, molecular technology and cell culture from chronic diseased sites such

as atherosclerotic plaque. Australian studies have thus far been limited. Moreover, in this context,

chlamydial cell culture has never previously been investigated in Australia . Additionally, very

limited attempts have been made worldwide with such culture.

Of the total Australian Sydney based population (N=492) studied in this investigation, and in reference

to the international golden standard MIF IgG, the seroprevalence of Cp was 59.6% of the population; the

seroprevalence of IgA was computed 33.5% of the population studied; with higher seroprevalence

among males (40%; N= 492) than in females (19.5%, N= 492). Of the total “healthy” Sydney

population (N=308), ages <5 –95 years, studied, it was illustrated that almost half the population

(MIFIgG: 47.4% of residents; BiocloneIgG 52.3%; MedacIgG: 45.5%) was seropositive to anti-Cp.

Prevalence of IgA species specific antibodies within the same group, measured by the Medac IgA assay

was lower, with 70.1% seronegative and only 29.9% seropositive to anti-Cp IgA.

About 79.9% of persons (N=184) with coronary artery disease (CAD) in Australia, show a seroresponse

to Cp liposaccharide (LPS) epitope with the MIFIgG; 65.8% with the BiocloneIgG; and 49.5% with the

MedacIgG assay. With respect to IgA Cp seropositivity within CAD, our survey demonstrated a total of

73.4% seropositivity with the BiocloneIgA assay and 39.7% seropositivity with the MedacIgA assay.

The “age-related” healthy controls (ages 35 – 95 years) studied (N=125) along with the CAD

population, presented a Cp seroprevalence of 62.4% with the MIFIgG; 61.6% with the BiocloneIgG, and

53.6% with the MedacIgG assay. With respect to IgA Cp seropositivity within the same control group,

our survey presented a lower prevalence for the BiocloneIgA (22.4%) than the MedacIgA (34.4%).

We establish the unreliability of 5 different Cp serological assays. IgG serology is not concordant and

likewise, the inflammatory IgA markers are ambiguous and assay dependent. No reliable associations

were found between circulating IgG and IgA in “age-related” CAD and healthy cohorts, and any

significance was assay dependent: a significant predictive anti-Cp IgG seropositivity value to CAD was




x

computed with the IgGMIF (P= 0.001); with respect to the IgGBioclone and the IgGMedac a

nonsignificant prediction was calculated with P values of 0.454, and P= 0.475, respectively. Likewise,

the anti-Cp IgA seropositivity value to CAD prediction was computed to be non-significant with the

MedacIgA assay (P= 0. 347) and of significant value with the Bioclone IgA assay (P=<0.001).

An attempt to provide a link by proving presence of the organism in re-stenosis CAD patients post

stenting, via culture, antigen and DNA detection was unsuccessful; An attempt to provide a correlation

of the organism with long term coronary events over a follow up period of 5 years lacked a significant

association; Our attempt to demonstrate a correlation with recognized ‘risk factors’ and cardiac end

points in association with Cp seropositivity between pre-existing CAD and newly diagnosed CAD

cohorts, was not very promising. Elevated triglycerides, hypertension and cholesterolaemia were the

closest risk predictors to cardiovascular events; Some risk predictions to CAD, in relation to Cp

seropositivity, were yet again assay dependent: elevated triglycerides presented a significant correlation

with the MedacIgG (P= 0.049) and the BiocloneIgG (P= 0.041) assays only; and elevated

cholesterolaemia with the MedacIgA assay ( P= 0.029).

Our attempt to provide evidence of existence of the organism in plaque tissue and respective peripheral

blood mononuclear cells (PBMC), in high risk CAD small group of participants, with DNA,

antigenaemia and isolation, was unsuccessful. Although a very small study, findings should be

considered, as they do add to universal archives. Moreover, of the 17 culture-negative and/or PCR-

negative individuals in this study, none satisfied serologic criteria for acute “active” infection.

Our findings, in agreement with many other reviews, support our hypothesis that Cp is not a predictive

cofactor to CAD and, in addition, have proven that inconsistencies and flaws do exist in interpretation

of data. Often, serologic markers to Cp infection are seen in association with uncomplicated

atherosclerosis and other chronic conditions, yet their predictive value for cardiovascular events is not

significant. Cp prevalence is recognized to be high world wide, however high seroprevalence and even

antigen detection do not prove causality in chronicity. We have illustrated that the seroepidemiology

data which triggered renewed interest in Cp as a significant agent in the aetiology and pathogenesis of

CAD, lacks strength. This may be due to confounding factors (e.g., socioeconomic status) and

publication bias towards positive findings. Indeed, more rigorously controlled observational and




xi

prospective studies as discussed in this thesis, appear to weaken the seroepidemiologic links between

chlamydial infection and atherosclerosis.

SYNOPSIS

Chlamydiae are a unique group of obligate intracellular microorganisms comprising important

pathogens of vertebrates as well as symbionts of free-living amoebae that are common inhabitants of the

aquatic environment. Amoebae may act as reservoirs for these organisms, implying that Chlamydia-like

organism have potential for widespread dissemination. In this context it is crucial to recognize that new

environmental Chlamydiae species are increasingly described (162, 318, 319, 610, 724, 1051).

Chlamydia pneumoniae (Cp) is a well documented, but widespread, respiratory tract pathogen and

frequently affiliated to community-acquired pneumonia. Chlamydia pneumoniae is a pathogen that has

been hypothesised to be associated with well over 30 diverse chronic diseases of markedly different

pathologies and pathogenic mechanisms.(543, 717) including lung cancer (570) and age-related macular

degeneration (AMD) (817, 818).

The controversial role of Chlamydia pneumoniae (Cp) causing human chronic infection and vascular

disease generated much interest so we commenced an investigation here in Australia, seeking for

evidence to help support an hypothesis that this respiratory pathogen, Cp, is strongly connected with

chronic vascular disease, whilst framing our hypothesis on lack of evidence for its role as reported

extensively in international published data. On review of previous reported studies, the majority have

supported the role of Cp in atherosclerosis, either seroepidemiologically (447, 783, 1044) or through

evidence of Cp in atherosclerotic lesions (114), by immunohistochemistry (130, 310, 419, 514, 521, 522,

677, 786, 868) or electron microscopy (142, 514, 522, 868) or PCR (130, 142, 240, 310, 419, 511, 513,

514, 521, 522, 676, 677, 689, 786, 787, 866) but very few have based it on cultivation of Cp from

atherosclerotic plaque (155, 418, 786).

Surveys performed on CAD patients alone (without normal controls) reported IgG seroprevalences of

40-84% (873) comparable with our survey that estimated 79.9% (N=184) seropositivity within CAD

population.




xii

Many reviews report major inter- and intralaboratory inconsistencies in detection rates of Cp in vascular

specimens. More and more investigations question positive findings and report discordant results

between clinical samples and methodologies applied, and inconsequential associations are evident. The

present investigation provides further evidence supporting the conclusion that Cp is not an important

cofactor in CAD and is not associated to cardiovascular progression.

There are a few Australian studies that have investigated the possible link between atherosclerosis with

this common respiratory pathogen. Most have failed to detect Cp in atherosclerotic plaque except for

one recent Australian study (155). Flaws in laboratory methods do exist and confirmatory culture is

often not performed to exclude confounding factors like false positive results., often due to cross-

reactivity. In another Australian study (758), no association of Cp was evident in any of the samples

tested in agreement with our findings.

Much of the evidence reported of the alleged role of Cp in CAD, is based upon serological studies and

findings are very controversial. Likewise, in this survey, we endeavoured to portray the unreliability of

serological Cp assays: a seroepidemiological survey of 308 Sydney based healthy residents and 184

CAD Sydney Candidates, undergoing coronary percutaneous translucent coronary angioplasty (PTCA) ,

were evaluated using 5 different methodologies: three for IgG determination and two IgA determination

immunoassays. Inconsistent sensitivities between all immunoassays were evident. Serological screening

for the seroprevalence of Chlamydia IgG antibodies and the inflammatory predictor of Chlamydia IgA

antibodies in 409 cohorts, was demonstrated to be an unreliable tool.

We investigated the presence of Cp DNA in 184 PTCA balloon plaque debris post restenosis and, in 17

individuals undergoing elective PTCA surgery, both PBMCs and vascular tissue specimens, using three

PCR assays: a nested touchdown ompA gene PCR as described by Tong and Sillis, a Real-Time VD4

restriction site of the ompA genome, specific to Cp, as described by Campbell et al and modified by us;

and thirdly another Real-Time Lc-PCR targeting the VD4 ompA of Cp genome, as described by

Tondella et al and modified by us for the Roche LightCycler. None of the three PCR assays used detect

Cp DNA in any vascular sample; similar negative findings have been recently reported by many other

investigators (610, 611). An anologous study has reported the first detection of Cp on angioplasty

balloons after coronary angiography (1015), however the same investigators reported cross-




xiii

contamination flaws and inconsistencies of positive findings. Although all our CAD cohorts had high

seroprevalence of Cp antibody, none were consistent with acute infection. None had plaque and/or

PBMC positive antigen for Cp by either PCR or cell culture immediately post collection.

Culture was the ultimate confirmatory tool used in this investigation. It is important to note that although

this study sample population is small and the findings did not demonstrate Cp antigenaemia, the use of

cell culture makes this study meticulously unique and should be reported, as there are not many

investigations that have used this approach as proof of Cp presence. Overall, these results do not provide

strong support for the hypothesis that Cp infection is a risk factor for clinical CAD. Cp seroprevalence

was not a predictive cofactor to cardiovascular causes and eventful cardiac complications. Infectious

agents may play an important role in atherogenesis as hypothesized, but we conclude, based on our

findings and those previously published, that the jury’s verdict is not with Cp.

PRESENTATIONS

1. Katerina Mitsakos, Karl Baumgart, Bernard Hudson, Helge Rasmussen, and Anthony Smithyman.

Five Year Follow-up of Sydney patients undergoing coronary angioplasty and stenting examined for

serologic markers of Cp, In Proceedings of the ASID 2003.

2. Karl Baumgart, Katerina Mitsakos, Bernard Hudson, Kate Levy, Archie Darbar, Helge Rasmussen,

Ian Chambers, Anthony Smithyman and Sharon Chen: Serologic markers of Cp infection in patients

living in Sydney undergoing coronary angioplasty and stenting, In Proceedings of the Australasian

Chlamydiae Consortium, 1999.

3. Hudson BJ, Hofmeyr A, Williams E, Mitsakos K, Fisher N, Lennox V, McDougall G, Tick Borne

Diseases Research Unit (TDRU), Department of Microbiology & Infectious Diseases RNSH; Australia

2005: Prospective Study of Australian Spotted Fever - Clinical & Epidemiological Features; In

Proceedings of the International Rickettsial Conference, Spain.




xiv

LIST OF FIGURES

Figure 1.0 Outcome of host-microbe interaction in infection (adapted: Casadevall & Pirofski, 2000)

Figure 1.1 Unique cycle of genus Chlamydiae

Figure 1.2 Postulated mechanisms: The link Infections and Vascular Disease

Figure 1.3 Activation mechanism of the Pathogenesis in Respiratory Infections

Figure 1.4 Pathogenesis of Chlamydiael Disease and progression to Atherosclerosis

Figure 1.5 Potential mechanisms of infectious agents in Atherosclerosis

Figure 1.6 Pathogenic mechanism which Cp could affect the development of Atherosclerosis

Figure 1.7 Monocyte-endothelial cell interaction

Figure 1.8 Development of atheromatous plaques

Figure 1.9 Endothelial Dysfunction in Atherosclerosis

Figure 1.10 Unstable Fibrous Plaques in Atherosclerosis

Figure 1.11 Possible mechanisms for the involvement of Cp in Atherosclerosis

Figure 2.1 Management of clinical: Biopsies, Tissues, Bronchial Lavage, NPA

Figure 2.2 Management of clinical samples: whole blood, EDTA, Buffy Coat

Figure 2.3 An optimized cell culture protocol for isolation and identification of Cp

Figure 2.4 Illustration of a serial dilution performed:optimization of the LC-PCR

Figure 2.5 Illustration of a serial dilution performed: sensitivity of the LC-PCR

Figure 2.6 Illustration of a serial dilution performed: optimization of the FAM-PCR

Figure 3.1 Histogram- Distribution of Age for the IgG MIF assay

Figure 3.2 Histogram- Distribution of Age for the IgG Bioclone assay

Figure 3.3 Histogram- Distribution of Age for the IgG Medac assay

Figure 3.4 Histogram- Distribution of Age for the IgA Medac assay

Figure 3.5 Histogram- Age with Gender in Healthy Population (N=308)

Figure 3.6 Histogram- Kinetic Percentage distribution of anti-CP IgG (all three assays) with Age (N=308)

Figure 3.7 Histogram- Percentage distribution of anti-C p IgA (Medac) with Age (N=308)

Figure 3.8 Histogram - Percentage distribution of anti-Cp IgG in Healthy females vs. Age per decade (N=154)

Figure 3.9 Histogram - Percentage distribution of anti-Cp IgG in Healthy males vs. Age per decade (N=154)

Figure 3.10 IgG assays vs. seroprevalence vs. Healthy 308 Cohorts




xv

Figure 3.11 Schematic trend distribution of IgG seroprevalence in Healthy Sydney residents (N=308)

Figure 3.12 Histogram - Trend of of anti-C.p IgG within the paediatric Acquired community vs. Our study

Figure 3.13 Histogram - Percentage distribution of anti-Cp IgG in Healthy males vs. Age per decade (N=154)

Figure 3.14 Histogram: Age per Decade for Males vs. anti- Cp IgG (all assays)

Figure 3.15 Histogram: Distribution of anti- Cp IgG STATUS vs. Gender in 309 Cohorts

Figure 3.16 Bar Illustration of Status vs. Age per Decade vs. Number of seropositive assays

Figure 3.17 Histogram: Cp Seroprevalence by Age within STATUS = Normal (N=125)

Figure 3.18 Histogram: Cp Seroprevalence by Age within STATUS = CAD (N=185)

Figure 3.19 Bar chart: STATUS with Age (N=309)

Figure 3.20 Bar chart: Age vs. STATUS vs. Number of assays applied (N=309)

Figure 3.21 Schematic illustration of Cp seropositivity within CAD vs. Age

Figure 3.22 Descriptive line Trend of anti-Cp IgG & IgA within the CAD cohorts

Figure 3.23 Histogram : trend of of anti-Cp IgG & IgA within the CAD cohorts

Figure 3.24 Histogram – Status vs. IgA Medac seroprevalence

Figure 3.25 Histogram – Status vs. IgA Bioclone seroprevalence

Figure 3.26 Histogram – Status vs. Number out of five Seropositivity

Figure 3.27 Line Distribution og IgG within Gender against Stented CAD and Normal subjects

Figure 3.28 Histogram of IgG assay seroprevalence against Stented Female Subjects per age group

Figure 3.29 Histogram of IgG assay seroprevalence against Healthy Female Subjects per age group

Figure 3.30 Histogram of IgG assay seroprevalence against Stented Male Subjects per age group

Figure 3.31 Histogram of IgG assay seroprevalence against Healthy Male Subjects per age group

Figure 3.32 Histogram of IgG assay seroprevalence against Stented and Healthy Females age per decade

Figure 3.33 Histogram of IgG assay seroprevalence against Stented and Healthy Males age per decade

Figure 3.34 Histogram of IgGMIF Distribution in Stented vs. Healthy subjects per age group

Figure 3.35 Distribution of serum OD concentrations for both anti-Cp IgG and IgA Medac assay

Figure 3.36 Distribution of serum OD concentrations for anti-Cp IgG and IgA Bioclone assay

Figure 3.37 Distribution of serum OD concentrations for both anti-Cp IgG and IgA Bioclone vs.

Medac assay (CAD vs.Normal; N=309)

Figure 3.38 Pie chart – Percentage distribution of cardiovascular factors in 184 CAD cohorts

Figure 3.39 Line trend - Percentage cardiovascular profiles against seroprevalent markers IgG and IgA

Figure 3.40 Pie Chart - Percentage distribution of cardiovascular risk profiles in CAD (N=184).




xvi

Figure 5.1 Line trend :Seroprevalence of Cp IgGMIF within CAD status with relative Risk profiles.

Figure 5.2 Line trend :Seroprevalence of Cp IgABIOCLONE within CAD status & Relative Risk profiles.

Figure 5.3 Histogram – Percentage Cp seroprevalence per assay within Healthy vs. CAD Status

Figure 5.4 Line Trend - Percentage Cp seroprevalence per assay within Healthy vs. CAD Status

Figure 5.5 Line trend – Assay comparison (ELISA vs. MIF) vs. Cp Seroprevalence in CAD Status

Figure 5.6 Prospective studies of Cp IgG titres with OR within CAD cohorts vs. Our Study

Figure 6.1 Kaplan-Meir Curve First Fair Complication with Pre-existing CAD Status

Figure 6.2 Kaplan-Meir Curve First Fair Complication with Gender

Figure 6.3 Kaplan-Meir Curve First Fair Complication with IgGMIF

Figure 6.4 Kaplan-Meir Curve First Fair Complication with IgGBioclone

Figure 6.5 Kaplan-Meir Curve First Fair Complication with IgABioclone

Figure 6.6 Kaplan-Meir Curve First Fair Complication with IgGMedac

Figure 6.7 Kaplan-Meir Curve First Fair Complication with IgAMedac

Figure 6.8 Kaplan-Meir Curve First Fair Complication with Any Aspirin

Figure 6.9 Kaplan-Meir Curve First Fair Complication with Any Stati

Figure 6.10 Kaplan-Meir Curve First Fair Complication with Elevated n Glucose >6.0mmol/L

Figure 6.11 Kaplan-Meir Curve First Fair Complication with Family History of CAD

Figure 6.12 Kaplan-Meir Curve First Fair Complication with Obesity

Figure 6.13 Kaplan-Meir Curve First Fair Complication with Elevated Cholesterol

Figure 6.14 Kaplan-Meir Curve First Fair Complication with Elevated Triglycerides

Figure 6.15 Kaplan-Meir Curve First Fair Complication with Diabetes

Figure 6.16 Kaplan-Meir Curve First Fair Complication with Hypertension

Figure 6.17 Kaplan-Meir Curve First Fair Complication with Smoking History

Figure 6.18 Kaplan-Meir Curve First Fair Complication with Previous Underlying Disease (PUD)

Figure 6.19 Kaplan-Meir Curve First Fair Complication with Previous Vascular Disease (PVD)

Figure 6.20 Kaplan-Meir Curve First Fair Complication with Positibe to All 3 IgG Assays

Figure 6.21 Kaplan-Meir Curve First Fair Complication with Positive to Both IgA assays

Figure 6.22 Kaplan-Meir Curve First Fair Complication with Positive to All Five Assays

Figure 6.23 Kaplan-Meir Curve First Serious Complication with Pre-existing CAD Status

Figure 8.1 Histogram – Risk Variables vs. Univariate predictors to mortality (N=17)

Figure 8.2 Photo 5: Taken from a positive atheroscleotic plaque after tissue culture.




xvii

Figure 8.3 Photo 6: Taken from a positive atherosclerotic plaque after tissue culture.

Figure 8.4 Photo 7: Taken from a positive atherosclerotic plaque: Chalmydial mimicry?

Figure 8.5 Photo 8: Positive control slide IOL-207 after tissue culture.

Figure 9.1 Illustration of autofluorescent reactivity compounds in atheorsclerotic tissue.

Figure 9.2 Photo 7: Demonstration of Non-specific staing: Antigen ?Chalmydial mimicry?

LIST OF TABLES

Table 1.1 Epidemiology of Chalamydia pneumoniae (Cp)

Table 1.2 Diagnostic criteria of Cp infection in prospective seroepidemiological studies

Table 1.3 Specific Factors that may link Cp infection in Coronary Artery Disease

Table 1.4 External factors triggering HSP production

Table 1.5 Koch’s postulates for Infectious Diseases

Table 1.6 Human Disease and their contributory role for infection

Table 1.7 Former Publications that have demonstrated the ability of Cp to multiply in cells of arterial walls

Table 1.8 Detection role of Cp by PCR and/or ICC in tissues obtained in 38-autopsy case

Table 1.9 Demonstration of Cp by IFT (genus-specific)

Table 1.10 Efficacy of antibiotics against Cp

Table 2.1 PCR Assays for Cp detection of the ompA gene– Tong & Sillis

Table 2.2 Cp isolates by PCR based fluorescence assays designed to detect regions of the ompA gene

Table 2.3 Criteria for serologic diagnsosis of Cp in chronicity

Table 2.4 Cp infectivity grading criteria for cell culture

Table 2.5 Cp PCR detection assay used for vascular aortic plaque & PBMC

Table 2.6 Molecular cloning of separate VDs of the Cp MOMP gene

Table 2.7 QC strains fro sensitivity and specificity for LC-PCR assays

Table 2.8 Quantification anlyses for the PCR detection assays

Table 2.9 Bacterial load Optimization: Examples of Serial Dilution: known EB/μL.

Table 2.10 Optimization: Determining Sensitivity Performance for PCR Assays.

Table 2.11 Method 1: LC-PCR Bacterial load sensitivity

Table 2.12 Method 2: FAM-PCR Bacterial load sensitivity




xviii

Table 3.1 Independent sample test – Per age group in 492 Sydney residents

Table 3.2 Paired Sample statistics for Age in 492 Sydney residents

Table 3.3 Independent Test for Gender in 492 Sydney residents

Table 3.4 Summary:Cp seropositivity (all ages) with Age & Gender Variables vs. Cp assay (N=492)

Table 3.5 Summary Table: Cp seropositivity general STATUS vs. Serological Methodologies (N=492)

Table 3.6 T test Correlations for paired Variables of Cp seropositivity (N=492)

Table 3.7 Paired sample test correlations in 492 Sydney Residents

Table 3.8 Case Summary Comparable analyses of C p seropositivity (all ages) with Age and Gender

vs. serological methodologies (492)

Table 3.9 Percentage Cp seroprevalence per control age group; (ages <1 years to 90 years).

Table 3.10 Comparable serological analysis of Cp seropositivity in healthy females (N= 154).

Table 3.11 Comparable serological analysis of Cp seropositivity in healthy males (N= 154).

Table 3.12 Summary: Gender Variable Correlation with OR, 95% CI, P values in Healthy cohorts (N=308).

Table 3.13 Summary table: Gender Variable per age group vs. Status (N=309)

Table 3.14 Summary table: Age and Gender Variable within Status (N=309) : t test

Table 3.15 Age per decade vs.number of seropositive assays out of five (t test)

Table 3.16 Age per decade with anti-IgG MIF/ anti-IgG Bioclone/ anti-IgA Bioclone/ anti-IgG

Medac anti-IgA Medac / as variable in logistic regression analysis.

Table 3.16 Independent sample t test with OR & 95% CI and significance at 2-tailed with

Number of seropositive assays out of five.

Table 3.17 Crosstabulations within Status: CAD vs. Healthy (N=309) vs. Number of seropostive

assays out of five.

Table 3.18 Comparison of anti-Cp assays: ELISAs vs. EIA vs. MIF within Status (N=309).

Table 3.19 Descriptive serology of anti-Cp IgG and IgA in CAD population (ELISA vs. EIA vs. MIF).

Table 3.20 Descriptive serology of anti-Cp IgG and IgA in Healthy population (ELISA vs. EIA vs. MIF).

Table 3.21 Summary table – Categorical serological analysis of all anti-Cp IgG/IgA assays and seropositivity

within Status (CAD vs. Normal) – OR plus 95% CI and P values of significance with k value

of agreement

Table 3.22 Comparative analysis of anti-C .pneumoniae using the Medac IgA assay in Status (N= 309).

Table 3.23 Comparative analysis of anti-C .pneumoniae using the Bioclone IgA assay in Status (N= 309).

Table 3.24 Comparative analysis of the two anti-C .pneumoniae IgA assays: Bioclone assay vs.Medac in




xix

Status (N= 309); OR ,95%CI plus McNemar test plus k degree of agreement

Table 3.25 Categorical variable analysis of anti-Cp IGA assay seropositivity in Status (N=309)

Table 3.26 CaseProcesing summary; Chi square, Symmetric measures, in Status vs. Number of seropostive

assays (0 to five) (N=309)

Table 3.27 Conflicting Agreement of Serologic Assays – McNemar & Kappa normal scale Variables

Table 3.28 Stented female Population vs. healthy female population- Age comparative analysis

Table 3.29 Stented male Population vs. healthy male population- Age comparative analysis

Table 3.30 Percentage cardiovascular risk factors in N=184 CAD Sydney cohorts

Table 3.31 Percentage cardiovascular risk profiles with Cp markers (N=184)

Table 3.32 Percentage Number distribution of risk profiles in N=184 Sydney cohorts

Table 3.33 Comparative studies on the seroprevalence of Cp that used EIA and MIF in the latest 2000s

Table 3.34 Global seroprevalence of C .pneumoniae IgG using the MIF test in any healthy population

Table 3.35 Seroprevalence of Cp IgG & IgA in CAD: Comparison with other investigations (1988 – 2008).

Table 3.36 Diagnosis of Cp infection criteria by different methodologies and Interpretation bias

Table 4.1 Summary table: Statistical Seroprevalence of IgG & IgA prediction to a coronary event (N=160)

Table 4.2 Statistical Seroprevalence of IgG and IgA prediction to a coronary event in Pre-existing CAD

Table 4.3 Statistical analysis: Prediction of risk profile to progression to any cardiac event

Table 4.4 CAD status * Number of Complications * All positive assays (five of five assays)

Table 4.5 CAD status * Any Complication * IgG

Table 5.1 Unadjusted predictive OR for seropositive IgGMIF with risk factors to a complication

Table 5.2 Unadjusted predictive OR for seropositive IgGBIOCLONE with risk factors to a complication

Table 5.3 Unadjusted predictive OR for seropositive IgABIOCLONE with risk factors to a complication

Table 5.4 Unadjusted predictive OR for seropositive IgGMEDAC with risk factors to a complication

Table 5.5 Unadjusted predictive OR for seropositive IgAMEDAC with risk factors to a complication

Table 5.6 Summary table: Cp IgGMIF prediction for CAD with risk profiles with predictive O/R and P values.

Table 5.7 Summary table: Cp IgABIOCLONE prediction for CAD with risk profiles

Table 5.8 Seroprevalence of Cp IgGMIF to the prediction of the Pre-existing (OLD) CAD with risk profiles

Table 5.9 Seroprevalence of Cp IgGMIF to the prediction of the (NEW) CAD with risk profiles

Table 5.10 Seroprevalence of Cp IgABIOCLONE to the prediction of the OLD CAD with risk profiles

Table 5.11 Seroprevalence of Cp IgABIOCLONE to the prediction of the NEW CAD status with risk profiles

Table 5.12 Seropositivity of Cp in coronary atheroscleroris within the NEW CAD cohorts




xx

Table 5.13 Seropositivity of Cp in coronary atheroscleroris within the (OLD) CAD cohorts

Table 5.14 Seropositivity of Cp in coronary atheroscleroris within the Total Status (OLD vs. NEW)

Table 5.15 NEW CAD cohorts: Cp seroprevalence and impact on future of cardiovascular events: progression

to a number of cardiac complications (N=114 of 160)

Table 5.16 OLD CAD cohorts: Cp seroprevalence and impact on future of cardiovascular event: progression

to a number of cardiac complications (N=46 of 160)

Table 5.17 Total CAD Status cohorts: Cp seroprevalence and impact on future of cardiovascular

events:progression to a number of cardiac complications (N= 160)

Tbale 5.18 Comparison: Cp * Medac Assay * IgGMIF * Bioclone

Table 5.19 Descriptive Analysis: Impact of Independent Risk Variable Prediction on CAD (OLD vs. NEW)

Table 5.20 Descriptive Analysis: Impact of Independent Risk Variable Prediction on any Cardiac Complication

within CAD Status (Pre-existing vs. NEW)

Table 5.21 Descriptive Analysis: Independent Risk Variable Prediction on more than one progressive Cardiac

Complications within CAD Status (Pre-existing vs. NEW)

Table 6.1 Survival analyses Summary Table to First Fair Complication (UAP or Hospitalization or

Vascularization and/or AMI) with OR, 95% CI, P values

Table 6.2 Summary Table:Odds Ratio(O/R) prediction to First Fair Complication

Table 6.3 Survival Analyses Summary Table to First Serious Complication (AMI or CABG or Death)

Table 6.4 Summary Table: Cox Regression Odds Ratio(O/R) prediction to First Serious Complication

Table 6.5 Risk Variables in order of their predictive lower rosk elimination O/R after CAD diagnosis

with ot without pre-existing CAD and/or with or without any complcation.

Table 7.1 Interpretation of seropositive diagnosis of C. penumoniae in 15 CAD atherosclerotic patients.

Table 7.2 Association between circulating PBMC C.pneumoniae DNA (PCRpositive), IgG antibodies to

Cp (MIF positive) and culture positive in this present survey.

Table 7.3 Presence of circulating C .pneumoniae in PBMC

Table 7.4 Studies describing prevalence of Cp DNA detection in PBMC with respect to PCR targets.

Table 7.5 Studies with controls describing relationship between Cp DNA detection in PBMCs

Table 7.6 Studies of PBMC detection in various case groups, CAD,blood donors

Table 8.1 Comparison of real-time FAM- PCR and LC-PCR assay with cell culture for detection of Cp

Table 8.2 Compliment Fixation (CF) results – Elimination of cross-reactivity and non-specificity.

Table 8.3 Seroprevalence of IgG/IgA markers in chronic CAD cohorts and diagnosis




xxi

Table 8.4 CAD patient caharacteristics by univariate risk predictors of mortality and Cp seropositivity

Table 8.5 Chronic infection of a Control subject with relative risk profiles.

Table 8.6 Stattistical analysis: Univariate Prediction of Cardiac Morbidity in 17 atheroscleroric subjects.

Table 8.7 Summary of diverse blood sampling, DNA extraction and respective PCR targets employed

by various investigators worldwide.

Table 8.8 Detection of C .pneumoniae in atherosclerotic plaque in 17 CAD cohorts.

Table 8.9 Results of published C .pneumoniae detection in atherosclerotic lesions in CAD patients.

Table 8.10 Results of published studies of C .pneumoniae detection in Normal tissue with and without

CAD.

Table 8.11 Results of published studies of C .pneumoniae culture and PCR detection in Atherosclerotic

tissue in cohorts with and without CAD.

Table 9.1 Seropositivity to multiple infectious agents: % risk to progression of cardiovascular events.

Table 9.2 Seroprevalence of C .pneumoniae in the Sydney cohortsurvey (1998-2000).




xxii

ABBREVIATIONS

AAA - Abdominal Aortic Aneurysm

AMI - Acute Myocardial Infarction

ARI - Acute Respiratory Infection

ATP - adenosine triphosphate

CAD - CAD

CFT/CF - complement fixation

CHD - Coronary Heart Disease

CMV - Cytomegalovirus

COPD - Chronic Obstructive Pulmonary Disease

C/O - Cut-off

Cpn/Cp - Chlamydia pneumoniae

CRP - C-reactive protein

CVD - Cardiovascular Disease

DFA - direct fluorescence antibody assay

DNA - deoxyribonucleic acid

EB - elementary body (s)

EBV - Epstein-Barr virus

EIA - enzyme immunoassay

EIU - enzyme immunoassay unit

ELISA - enzyme-linked immunosorbent assay

FA - fluorescent antibody

FITC - fluorescein isothiocyanate

GTP - guonosine triphosphate

h - hour

HBV - Hepatitis B virus

HCV - Hepatitis C virus

HIV - Human Immunodeficiency Virus

Hsp/HSP - heat shock protein (s)

HSV - Herpes Simplex Virus

IB - intermediate body

IC - Immune Complex

IF - immunofluorescence

IFA - immunofluorescence assay

IDFA - indirect immunofluorescence antibody assay

IHA - indirect haemoglutination assay

IHD - Ischaemic Heart Disease

IgG - immunoglobulin G fraction

IgM - immunoglobulin M fraction

IOL-207 - Chlamydia pneumoniae isolate

ISR - Immune Status Ratio




xxiii

KDa - kilo Dalton

Kdo - 3-deoxy-manno-octylosonate

LPS - lipopolysaccharide

LVG - lymphogranuloma venereum

Mab(s) - monoclonal antibody (s)

MI - Myocardial Infarction

MIC - minimum inhibitory concentration (s)

MIF - microimmunofluorescence test

min - minute (s)

MOMP - major outer membrane protein

NAAT - nucleic acid amplification test

NEW - Non Pre-Existing CAD within Status(Acutely diagnosed with AMI)

OLD - Pre-Existing CAD within Status (Known Pre-Existing AMI)

OMC - outer membrane complex

Omp2 - outer membrane protein 2

OmpA - outer membrane protein A

OR - odds ratio

ORF - open reading frame

PAb - polyclonal antibody (s)

PCR - polymerase chain reaction

PLT - psittachosis-lymphogranuloma venereum-trachoma

PID - pelvic inflammatory disease;

PMN - polymorphonuclear

Pmps - polymorphic membrane proteins

PVD - Peripheral Vascular Disease

RB (s) - reticulate body (s)

rELISA - recombinant enzyme-linked immunosorbant assay

RNA - ribonucleic acid

rRNA - ribosomal RNA

RCT - Randomised Controlled Trials

RTI - respiratory tract infection

Status - subjects within population (Normal vs. CAD; NEW vs. OLD)

STD - sexually transmitted disease

SPG - sucrose-phosphate-glutamate (Chlamydia transportation medium)

TFI - tubal factor infertility

TRIA - time-resolved fluoroscopic immunoassay

TRIC - trachoma inclusion conjunctivitis agent

TWAR - synonym for Cp

TW-183 - Chlamydia pneumoniae isolate

URTI - Upper Respiratory Tract Infection

VD - variable domain

WIF - whole-inclusion fluorescence

cpn thesis 2009 v3 title abstract synopsis table figures i - xxvi v3 201009

Documents

chronic infection

vascular disease version

controversial role of

thesis title

katerina mitsakos iol

department of microbiology

special gratitude

valuable time