Ramyasuda SWAMINATHAN MBBS FRACP · Ramyasuda SWAMINATHAN MBBS FRACP This thesis is presented in...

RENAL AND METABOLIC FUNCTION IN RENAL

TRANSPLANT RECIPIENTS RECEIVING

CALCINEURIN INHIBITORS AND THE EFFECTS OF

CONVERSION TO SIROLIMUS

Ramyasuda SWAMINATHAN MBBS FRACP

This thesis is presented in partial fulfillment of the requirements for the degree of

Master of Clinical Research of the University of Western Australia

School of Medicine and Pharmacology

Faculty of Medicine Dentistry and Health Sciences

The University of Western Australia

February 2012

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Abstract

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Renal transplantation is the best form of renal replacement therapy for patients

with end-stage kidney disease. Refinements in immunosuppressive treatments

and new immunology techniques have reduced early rejection episodes and

improved the short term survival of renal allografts. Patients with successful

renal transplant remain at high risk of long-term cardiovascular complications

which may be mediated, in part, by hyperlipidaemia, hypertension and diabetes.

The rate of late allograft loss due to cumulative immune and non-immune

mediated injury (defined as chronic allograft nephropathy - ‘CAN’) remains

largely unchanged. The immunosuppressive drugs known as the calcineurin

inhibitors (CNI) and the mTOR inhibitors (mammalian Target of Rapamycin

inhibitors “mTOR-I”) may have effects upon the potential non-immune mediators

of CAN (glucose metabolism, lipid profile, proteinuria and blood pressure),

which are also significant cardiovascular risk factors.

This thesis uses retrospective and prospective studies to test the hypothesis

that in renal transplant recipients (RTR) with histological evidence of CAN, the

non-immune mediators of CAN especially proteinuria and/or histological

characteristics of allograft injury determined by BANFF criteria, determine

whether the conversion from a CNI to a mTOR-I is associated with improved

renal function. It also tests whether despite an improvement in renal function

there are any potentially adverse effects upon glucose and lipid metabolism.

Study 1 retrospectively examined the effects of the mTOR-I, Sirolimus (SRL)

upon changes in renal allograft function measured as estimated Glomerular

Filtration Rate (eGFR) and proteinuria and determined the relationship between

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pre conversion renal histology and post conversion eGFR & proteinuria to

identify clinical and histological predictors of successful conversion to SRL from

a CNI. 85 RTRs with biopsy proven CAN, a median of 5 years post

transplantation were studied. 51 were electively converted to SRL (SG) and 34

remained on CNI (CG). This was a clinician initiated non-randomised

conversion. After a median follow-up of 5.3 years the eGFR stabilised in the SG

and continued to decline in the CG. Death censored graft loss was significantly

lower in SG compared with the CG. Baseline proteinuria and histological grades

of tubular atrophy predicted the post conversion eGFR. Sirolimus conversion

was also associated with an increase in proteinuria. Pre-conversion protein:

creatinine ratio of ≥ 50mg/mmol was associated with increase in proteinuria

post-conversion. This study concluded that in RTRs with CAN, conversion to

SRL at a median of 5 years posttransplantation stabilised the eGFR and that

successful conversion was associated with lower histological grades of chronic

tubular atrophy and lower proteinuria at the time of conversion.

Study 2 prospectively studied the effects of SRL upon measures of glucose and

lipid metabolism in stable RTRs without diabetes. 25 RTRs on a CNI based

immunosuppressive regimen (8 Tacrolimus “TAC”, 17 CyclosporineA “CyA”)

with stable renal function were electively converted to SRL. Standard oral

glucose tolerance test (OGTT), fasting lipids, free fatty acids (FFA), apo-

lipoproteins A1 and B, Body Mass Index (BMI) and eGFR were measured

before conversion and at 3 and12 months post conversion to SRL. OGTT was

used to derive i) Insulin sensitivity Index (ISI TX), ii) Homeostasis Model

Assessment score for Insulin Resistance (HOMA- IR), iii) Metabolic Clearance

rate of glucose (MCR). 21/ 25 patients were maintained on statin therapy. The

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mean SRL level was 6.7 +/- 2.2ng/ml and the mean dose was 1.59 +/-0.8

mg/day. After conversion to SRL, there was no change in the BMI, HOMA-IR,

Glycated haemoglobin (HbA1C), ISItx, MCR, high density lipoprotein (HDL), FFA

or Apo A1 at 3 or 12 months post-conversion compared with baseline. However

there was a significant increase in the total cholesterol (TC), low density

lipoprotein (LDL), Triglycerides (TGL), non-HDL cholesterol and Apo B. This

study concluded that in stable RTR with CAN, SRL did not affect the glucose or

insulin homeostasis in this selected patient cohort without diabetes. SRL

induced dyslipidaemia was primarily associated with altered metabolism of Apo

B containing lipids and not with altered glucose or insulin disposition.

Overall this research helps to further clarify the role of mTOR inhibitors in renal

transplant setting, improve the understanding of the factors that contribute to a

successful conversion to mTOR inhibitors in the setting of CAN and understand

the possible mechanisms that effect glucose and lipid metabolism after renal

transplantation, which may have important implications for understanding the

long-term patient and renal allograft survival and assist clinicians in the

appropriate timing and patient selection for the optimal use of the mTOR-I

Sirolimus.

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Table of Contents

Abstract ............................................................................................................. ii

Table of Contents ............................................................................................. vi

List of Tables ................................................................................................... xii

List of Figures ................................................................................................ xiv

Abbreviations ................................................................................................. xvi

Acknowledgements ....................................................................................... xix

Statement of Candidate Contribution: ......................................................... xxi

Introduction ..................................................................................................... 22

Chapter 1 Review of Literature ...................................................................... 26

1.1. End Stage Kidney Disease in Australia .................................................. 27

1.2. Rejection of renal allograft: ..................................................................... 29

1.2.1 Cell Mediated Rejection (CMR): ............................................................. 30

1.2.2 Antibody Mediated Rejection (AMR): ...................................................... 31

1.2.3 Chronic Rejection: .................................................................................. 32

1.3. Mechanism of action of different Classes of Immunosuppressive agents:

............................................................................................................... 33

1.4. Overview of Chronic Allograft Nephropathy ............................................ 37

1.4.1 Definition of CAN: ................................................................................... 37

1.4.2 Nomenclature of CAN – A historical perspective ..................................... 37

1.4.3 Mediators of CAN: .................................................................................. 38

1.4.4 Pathogenesis of CAN ............................................................................. 46

1.4.5 Mechanisms of allograft injury: ............................................................... 48

1.4.6 Banff Histological Classification of CAN .................................................. 50

1.4.7 Role of CNI in CAN ................................................................................. 53

1.4.8 The Natural History of CAN .................................................................... 57

1.5 Role of mTOR inhibitors in CAN: ............................................................. 58

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1.6. Proteinuria post Transplantation: ............................................................ 62

1.6.1 Introduction ............................................................................................. 62

1.6.2 Post Transplant Proteinuria: ................................................................... 63

1.6.3 Sirolimus and Proteinuria: ....................................................................... 63

1.7 Overview of Post Transplant Diabetes Mellitus ....................................... 66

1.7.1 Introduction ............................................................................................. 66

1.7.2 Steroids and PTDM: ............................................................................... 67

1.7.3 CNI and PTDM: ...................................................................................... 67

1.7.4 SRL and PTDM: ..................................................................................... 68

1.8. The mTOR pathway and mTOR inhibitors: ............................................. 69

1.8.1 The upstream components of mTOR ...................................................... 69

1.8.2 The downstream effectors of mTOR pathway ......................................... 71

1.8.3 Positive and Negative Feed-back in mTOR pathway: ............................. 71

1.8.4 Role of mTOR signaling in glucose metabolism: ..................................... 73

1.8.5 Conflicting role of mTOR inhibition on glucose metabolism:.................... 77

1.8.6 Effect of mTOR inhibition on glucose metabolism in RTRs ..................... 77

1.8.7 Limitations of the existing studies ........................................................... 81

1.9 Post Transplant Dyslipidaemia: ............................................................... 82

1.9.1 Overview of the lipid metabolism: ........................................................... 82

1.9.2 Lipid Transport:....................................................................................... 86

1.9.3 Post Transplant Dyslipidaemia: .............................................................. 88

1.10 Summary: .............................................................................................. 91

Chapter 2: Research Methodology ................................................................ 92

2.1 Introduction: ............................................................................................. 93

2.2 Study Hypotheses: .................................................................................. 93

2.3 Aims: ....................................................................................................... 94

2.4 Study Design ........................................................................................... 95

2.4.1 Inclusion Criteria: .................................................................................... 95

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2.4.2 Exclusion Criteria .................................................................................... 95

2.4.3 Study Population .................................................................................... 95

2.5 Study Methods: ....................................................................................... 97

2.5.1 Data collection: ....................................................................................... 98

2.5.2 Prospective Group Study Protocol .......................................................... 99

2.6 Laboratory Methods: ............................................................................. 100

2.7 Study Protocols ..................................................................................... 102

2.7.1 Standard Oral Glucose Tolerance Test: ................................................ 102

2.7.2 Sirolimus conversion Protocol: .............................................................. 102

2.7.3 MPA / AZA dosing ................................................................................ 102

2.7.4 Statin Use in PG ................................................................................... 103

2.8 Follow- up .............................................................................................. 103

2.8.1 Retrospective Study ............................................................................. 103

2.8.2 Prospective Study ................................................................................. 103

2.9 End points: ............................................................................................ 103

2.9.1 Retrospective Study ............................................................................. 103

2.9.2 Prospective Study ................................................................................. 103

2.10 Definitions: ........................................................................................... 104

2.11 Statistical Methods: ............................................................................. 107

2.11.1 Descriptive Statistics:.......................................................................... 107

2.11.2 Additional tests used in Retrospective Study: ..................................... 107

2.11.3 Additional Tests used in the Prospective Study: ................................. 109

2.12 Ethical issues: ..................................................................................... 110

2.13 Results: ............................................................................................... 110

Chapter 3: Evaluation of Renal Outcomes in Renal Transplant Recipients

with Chronic Allograft Dysfunction following conversion from Calcineurin

inhibitors to Sirolimus and the Predictors of Successful Conversion ..... 111

3.1 Hypothesis and Aims ............................................................................. 112

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3.1.1 Hypothesis: ........................................................................................... 112

3.1.2 Aims: .................................................................................................... 112

3.2 Methodology: ......................................................................................... 113

3.2.1 Statistical Methods ............................................................................... 113

3.3 Results .................................................................................................. 114

3.3.1 Baseline Clinical Characteristics: .......................................................... 114

3.3.2 Baseline Histological Characteristics: ................................................... 115

3.3.3 CNI dosing in the CG ............................................................................ 120

3.3.4 SRL dosing in the SG: .......................................................................... 120

3.3.5 eGFR Outcomes: .................................................................................. 121

3.3.6 Proteinuria Outcomes: .......................................................................... 131

3.3.7 Blood Pressure outcomes: .................................................................... 139

3.4 Discussion ............................................................................................. 141

3.4.1 eGFR outcomes: .................................................................................. 141

3.4.2 Proteinuria Outcomes: .......................................................................... 145

3.4.3 Other Outcomes: .................................................................................. 146

3.5 Strengths of the Study: .......................................................................... 147

3.6 Study Limitations ................................................................................... 148

3.6.1 Study Design ........................................................................................ 148

3.6.2 Outcome measures .............................................................................. 148


3.7 Conclusion ............................................................................................. 149

3.8 Validation of Study Hypothesis: ............................................................. 150

3.9 Directions for Future Research .............................................................. 150

Chapter 4: Effect of mTOR INHIBITOR Sirolimus Upon Glucose & Lipid

Metabolism in Stable Renal Transplant Recipients. .................................. 151

4.1 Hypothesis and Aims: ............................................................................ 152

4.1.1 Hypothesis: ........................................................................................... 152

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4.1.2 Aim: ...................................................................................................... 152

4.2 Methods: ................................................................................................ 152

4.2.1 Statistical Methods: .............................................................................. 153

4.3 Results: ................................................................................................. 153

4.3.1 Entry Clinical Characteristics ................................................................ 153

4.3.2 Entry Histological Characteristics: ........................................................ 155

4.3.3 Concomitant use of other immunosuppressants: .................................. 156

4.3.4 Use of Antihypertensive agents: ........................................................... 157

4.3.5 Use of statin: ........................................................................................ 158

4.3.6 Renal Function (eGFR): ........................................................................ 158

4.3.7 Proteinuria ............................................................................................ 158

4.3.8 Effect of SRL conversion upon measures of glucose metabolism: ........ 160

4.4 Discussion: ............................................................................................ 168

4.4.1 eGFR .................................................................................................... 168

4.4.2 Proteinuria vs. albuminuria. .................................................................. 168

4.4.3 Effect of SRL conversion upon Glucose and Insulin metabolism: ......... 170

4.4.4 Effect of SRL conversion upon Lipid Metabolism: ................................. 173

4.4.5 Cardio-vascular risk profile following conversion to SRL ....................... 177

4.5 Strengths of the study............................................................................ 178

4.6 Limitations of this Study:........................................................................ 179

4.6.1 Study Design: ....................................................................................... 179

4.6.2 Outcome measures: ............................................................................. 179


4.7 Conclusion ............................................................................................. 180

4.8 Validation of the study Hypothesis: ....................................................... 181

4.9 Directions for Future Research .............................................................. 182

Bibliography .................................................................................................. 183

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Appendices.................................................................................................... 213

Appendix 1 (Ethics approval)....................................................................... 214

Appendix 2 (Patient Information Sheet) ....................................................... 215

Appendix 3 (Abstracts and Presentations) .................................................. 220

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List of Tables

Table 1.1 Long term renal allograft survival rates ....................................... 36

Table 1.2 Banff 2007 Classification ............................................................... 52

Table 1.3 Summary of renal outcomes and side effect profile following

mTOR-I conversion in transplant recipients................................................. 60

Table 1.4 SRL and PTDM in RTRS- Summary of published studies ........... 79

Table 1.5 Function of Apo-lipoproteins ........................................................ 85

Table 1.6 Studies in RTRs showing SRL induces dyslipidaemia ............... 89

Table 2.1 Data Collected in the Study Population ........................................ 98

Table 2.2 Additional data collected in the Prospective Group .................... 99

Table 2.3 Laboratory Methods ..................................................................... 100

Table 3.1 Baseline Characteristics of RTRs in SG and CG ....................... 114

Table 3.2 Linear mixed modelling of eGFR comparison in the two groups

........................................................................................................................ 122

Table 3.3Comparison of predicted eGFR at specific time-points ............. 123

Table 3.4 Univariate analysis of pre-conversion clinical features that may

predict eGFR response post SRL conversion. ........................................... 124

Table 3.5 Univariate analysis of pre-conversion histological ................... 126

features that may predict eGFR response post SRL conversion. ............ 126

Table 3.6 Model predicting eGFR outcome................................................. 127

Table 3.7 Linear mixed modelling of graft loss censored proteinuria ...... 133

Table 3.8 Baseline PCR correlates with post-conversion PCR ................. 136

Table 4.1 Entry Clinical characteristics of PG ............................................ 154

Table 4.2 Entry Histological Characteristics .............................................. 155

Table 4.3: Concomitant use of other immunosuppressants ..................... 156

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Table 4.4: Use of anti-hypertensive agents and Prednisolone before and

after SRL conversion .................................................................................... 157

Table 4.5 Fasting Glucose, Insulin, C-peptide and Glycated Hb levels post

SRL conversion ............................................................................................. 160

Table 4.6 Changes in Fasting C-peptide levels with time .......................... 161

Table 4.7 Improved Impaired Glucose tolerance and insulin resistance

post-conversion ............................................................................................ 162

Table 4.8 OGTT derived indices post SRL conversion .............................. 164

Table 4.9 Changes in BMI, Hs CRP & FFA post SRL conversion ............. 165

Table 4.10 Changes in Lipids and Lipoproteins post SRL Conversion ... 166

Table 4.11 Significance of the difference among baseline, 3 and 12 month

lipid and lipoprotein values .......................................................................... 167

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List of Figures

Fig 1.1: Age specific mortality rate for Australians on treated with dialysis

or renal transplantation. ................................................................................. 28

Fig 1.2 Mechanism of T-cell mediated rejection ........................................... 30

Fig 1.3 Mechanism of Antibody Mediated Rejection .................................... 31

Fig 1.4 Structure of T-cell and sites of action of immunosuppressants. ... 33

Fig 1.5 Renal allograft survival rates 1965-2008 ........................................... 35

Fig 1.6 Pathogenesis of CAN. ....................................................................... 46

Fig 1.7 Histological changes of CAN ............................................................. 51

Fig 1.8 Mechanism of Chronic CNI toxicity................................................... 54

Fig 1.9 Histological Features of CNI Toxicity ............................................... 56

Fig 1.10 The mTOR pathway .......................................................................... 70

Fig 1.11 Basic Structure of Lipoprotein ....................................................... 83

Fig: 1.12 Endogenous and Exogenous Lipid Transport .............................. 86

Fig 2.1 Study Design ....................................................................................... 96

Fig 3.1 Baseline ‘ci” scores between SG and CG ...................................... 116

Fig 3.2 Baseline ‘ct” scores between SG and CG ...................................... 117

Fig 3.3 Baseline ‘‘cv” scores between SG and CG .................................... 118

Fig 3.4 Baseline ‘ah” scores between SG and CG ..................................... 119

Fig 3.5 Rate of decline in eGFR ................................................................... 121

Fig 3.6 Kaplan-Meier plot of Graft loss ....................................................... 129

Fig 3.7 Changes in PCR CG vs. SG ............................................................. 131

Fig 3.8 Graft loss censored PCR Changes ................................................. 132

Fig 3.9 Comparison of Baseline with post-conversion PCR ..................... 135

Fig 3.10 “ci” Changes at baseline ............................................................... 138

Fig 3.12 “ct” Changes at baseline ............................................................... 138

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Fig 3.11 “cv” Changes at baseline .............................................................. 138

Fig 3.13 “ah” Changes at baseline .............................................................. 138

Fig 3.14 Comparison of Systolic Blood Pressures in both groups .......... 139

Fig 3.15 Comparison of Diastolic Blood pressure in both groups ........... 140

Fig 4.1 Proteinuria Change post SRL conversion ...................................... 159

xvi

Abbreviations

Abbreviation Expansion

4E-BP1 Eukaryotic translation initiation factor – Binding Protein1 ABO Major blood Group Antigen s A,B,O ACE- I Angiotensin Converting Enzyme Inhibitor(s) ACR Albumin : Creatinine Ratio ADA American Diabetes Association AMP Adenosine Mono phosphate AMPK AMP Kinase AMR Antibody Mediated Rejection ANOVA Analysis of Variance ANZDATA Australia and New Zealand Dialysis and Transplant

Registry AP-1 Activator Protein-1 APC Antigen Presenting Cells Apo A /B/C Apo lipoprotein A/B/C ARB Angiotensin Receptor blocker(s) ATN Acute Tubular Necrosis AZA Azathioprine BD Brain death BMI Body Mass Index CAN Chronic Allograft Nephropathy CCB Calcium Channel Blocker(s) CD 3/4/8 Cluster of Differentiation (3/4/8) CE Cholesterol Ester CG Control Group CM Chylomicron CMR Cell Mediated Rejection CNI Calcineurin Inhibitor(s) CyA CyclosporineA DBD Donation after Brain Death DCD Donation after Cardiac Death DGF Delayed Graft Function DI Disposition Index DNA Deoxy Ribo Nucleic Acid eGFR Estimated Glomerular Filtration Rate EIF4G Eukaryotic translation initiation Factor 4 gamma ESKD End stage Kidney Disease EVR Everolimus FFA Free Fatty Acids FKBP12 FK Binding Protein 12 g Gram(s) GN Glomerulonephritis H and E Haematoxylin and Eosin HbA1C Glycated Haemoglobin HDL High Density Lipoprotein HLA Human Leukocytic antigen HOMA – IR Homeostasis Model Assessment score for Insulin

Resistance HPL Hepatic Lipase HsCRP Highly-Sensitive C-Reactive Protein

xvii

IDL Intermediate Density Lipoprotein IFG Impaired Fasting Glucose IFN Interferon IFTA Interstitial Fibrosis and Tubular atrophy IGT Impaired glucose tolerance IKK Inhibitor of Kappa B Kinase IL-2 Interleukin 2 IQR Inter Quartile Range IR Insulin Resistance IRI Ischaemia Reperfusion injury IRS-1 Insulin Receptor Substrate 1 ISI Tx Insulin Sensitivity Index for Transplantation ITT Intent to Treat kg Kilogram(s) l Litre(s) LCAT Lecithin- Cholesterol Acyl Transferase LDL Low Density Lipoprotein LDLr LDL receptor Lp(a) Lipoprotein(a) LPL Lipoprotein Lipase LRP LDLr related Protein MACE Major Coronary Event MAP Membrane Associated protein MCR Metabolic Clearance Rate of Glucose mg Milligram(s) MHC Major Histo-compatibility Antigen MHC Major Histocompatibility Complex Min minute ml Millilitre(s) MMF Mycophenolate Mofetil mmol Millimol(s) MPA Mycophenolic acid mRNA Messenger Ribonucleic Acid mTOR Mammalian Target of Rapamycin mTOR-I mTOR inhibitor(s) NFAT Nuclear Factor of activated T cell

NFĸB Nuclear Transcription Factor β NK Natural Killer NODAT New Onset Diabetes after Transplantation OGTT Standard Oral Glucose Tolerance Test PAS Periodic acid schiff PCR Protein: Creatinine Ratio PI3K Phosphoinositide-3 Kinase PL Phospholipids PMN Polymorphonuclear neutrophil PPAR- Peroxisome proliferator activated receptor - PRA Panel Reactive Antibodies PTDM Post Transplant Diabetes Mellitus RAAS Renin aldosterone Angiotensin System RPH Royal Perth Hospital RTR Renal Transplant Recipient(s)

xviii

SG Sirolimus Group SRL Sirolimus T- Reg Regulatory T Cell

T2DM Type 2 Diabetes Mellitus TAC Tacrolimus TC Total Cholesterol TCR T Cell receptor TG Transplant Glomerulopathy TGF-β1 Tumour Growth Factor TGL Triglycerides Th (1/2) T Helper subset (1/2) TLR Toll Like Receptors TSC1/2 Tuberous Sclerosis Gene 1/2 VEGF Vascular Endothelial Growth Factor VLDL Very Low Density Lipoproteins. WHO World Health Organisation

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Acknowledgements

I would like to sincerely thank my supervisor Dr. Ashley Irish for his support,

guidance, encouragement and for mentoring me during the past four years. It

has been a great privilege to work with such a highly talented clinician and

researcher, one who has been incredibly tolerant and patient towards my short-

comings and has constantly motivated me to complete this research. His sense

of humour has been a huge encouraging factor.

I thank my co-supervisor Professor Rajalingam Sinnaih, who in spite of his busy

work schedule examined and re-coded all the renal biopsies for the purposes of

this research.

I express my sincere thanks to Ms Sally Burrows, Bio-statistician, University

Department of Medicine, Royal Perth Hospital, for providing statistical support. I

would also like to thank my cousin and bio-statistician Mrs. Sowmya Anand for

helping with statistical analysis.

My special thanks to Mr James Goodchild and Mr Ralph Baker, Department of

Medical Illustration, Royal Perth Hospital for the illustrations published in this

thesis.

I would like to thank the Department of Nephrology and the nephrologists at

Royal Perth Hospital for their support.

Ms Sam Fidler, Senior scientist, Department of Immunology has been of great

help and support with immunological data and I thank her for that.

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I would like to sincerely extend my thanks to Pathwest Laboratories, Royal

Perth hospital and especially to Ms Linda Gregory for the laboratory analysis.

I thank the friendly staff at central specimen collection at Royal Perth Hospital.

Lisa Burnette, my friend and renal research manager has been very supportive.

I thank the renal pharmacists and our library staff for their support.

My sincere thanks, to all the patients, without whose participation, this research

would not have been possible.

This research endeavour would not have been possible without the help,

support, encouragement and motivation of my dear husband, Venkatesan

Narayanaswamy (Venky). Not only did he support me emotionally and shared

the domestic duties during my course-work, he also helped me with the Visio-

drawings published in this thesis. My daughters, Madu and Preetha have been

very patient and have been encouraging me to work at home during the

holidays. I would also like thank my beloved parents Chandra and

Swaminathan, who have dedicated their lives solely for my well-being, have

been of immense support through out my career. They have relieved me of all

my domestic duties during the past few months and this has enabled me to

complete my thesis. To my family, I dedicate this thesis.

Finally I thank all my friends and colleagues whose constant encouragement

has enabled me to complete this work.

xxi

Statement of Candidate Contribution:

I was involved in the concept development and study design for both the studies

in this thesis.

I was responsible for recruiting patients performing clinical examination and

data collection for both the studies in this thesis.

I performed the statistical analyses for the prospective study.

I have presented the results from both studies at national and international

meetings. (Appendix 3).

Dr. Ramyasuda Swaminathan C/Prof. Ashley Irish

Candidate Co-ordinating Supervisor

20 February, 2012

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Introduction

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Kidney transplantation is the best form of renal replacement therapy for those

suffering from end stage kidney disease (ESKD). Recipients of kidney

transplantation have a better quality of life and also extended life expectancy

compared with those who continue on dialysis. The major limitation for

increasing the number of patients who can benefit from kidney transplantation is

the limited availability of donor organs, with the number of people waiting for a

kidney transplant exceeding the organs available for transplantation.

Following renal transplantation kidney function is not indefinite. There is a slow

loss of function over time; with the half life a transplanted kidney reported as

about 12-15 years (defined as the period of time taken for 50% of the

transplanted kidneys to stop functioning). The reason for the chronic attrition of

renal function and eventual return to dialysis or need for further transplantation

is complex and incompletely studied, and has been attributed to several

immunological and non-immunological factors.

A major focus of research in renal transplantation is to examine the patho-

physiology of renal allograft injury and develop ways to improve the longevity of

the renal allograft. With improvements in the immunosuppressive medications

and advances in immunology, there has been an improvement in the

understanding and managing acute rejection. With the introduction calcineurin

inhibitors (CNI) [cyclosporine (CyA) and Tacrolimus (TAC)] as

immunosuppressive agents, acute rejections rates and early (1 & 5 year) graft

survival rates have improved significantly. However, the rates of late graft loss

due to cumulative immune and non-immune mediated injury (chronic allograft

nephropathy- CAN) remains unchanged.

24

Strategies to reduce the incidence of CAN and hence prolong the longevity of

the allograft are therefore the focus of much research. Sirolimus (SRL) is a

relatively new immunosuppressant that has demonstrated promising results in

reducing CAN. This belongs to a class of immunosuppressants called mTOR

inhibitors (mTOR-I). Compared with the CNI such as CyA and TAC, SRL is not

nephrotoxic. Additionally, due to its anti-proliferative properties, SRL has the

advantage of a lower risk of malignancy and was not considered to have an

adverse impact on glucose metabolism in renal transplant recipients (RTR).

Hence SRL was perceived as a major advantage in immunosuppression that

could potentially improve long term renal transplant outcomes. However with

increasing clinical use and longer follow up, some of the side-effects of this drug

such as impaired wound healing, proteinuria, oedema and dyslipidaemia have

become more apparent and limited its use.

In 2006 I commenced clinical research into the effects of SRL upon factors that

may impact long-term patient and kidney survival and identified several areas of

clinical uncertainty:

Which factors predict a favourable response to introduction of SRL with

regard to allograft function?

Does SRL affect glucose metabolism?

What are the characteristic lipid and lipoprotein changes associated with

SRL and what is the aetiology of this dyslipidaemia?

I have addressed and developed these 3 key questions by means of

retrospective and prospective clinical study, the results of which are presented

25

in this thesis entitled “Renal and Metabolic function in Renal Transplant

Recipients receiving Calcineurin Inhibitors and the effects of conversion to

Sirolimus”

This thesis is structured in 4 chapters:

Chapter 1: The literature on renal allograft loss due to CAN is reviewed

focusing on the role of the modifiable non-immunological risk factors of CAN

including post-transplant diabetes, dyslipidaemia, proteinuria and the impact of

various class of immunosuppressants upon these factors, with major focus on

SRL.

Chapter 2: Research methodology

Chapter 3: Results of the retrospective study which compares measures of

renal function in RTRs with CAN who are converted to SRL with those who

continue on a CNI. The clinical and histological factors that may predict these

clinical outcomes following conversion to SRL are described.

Chapter 4: Results of the prospective study, which examines the effects of

conversion from a CNI to SRL upon measures of glucose and lipid metabolism,

are presented.

This research will help to clarify the role of mTOR-I in the renal transplant

setting and improve the understanding of the factors that contribute to

successful conversion to mTOR-I in the setting of CAN and their effect upon

glucose and lipid metabolism. This will assist clinical decision making by

allowing better understanding of the benefits and risks of the use of mTOR-I in

clinical practice.

26

Chapter 1 REVIEW OF LITERATURE

27

1 .1 . End Stage Kidney Disease in Australia

ESKD is a major public health issue with approximately 10% of Australians

having signs of chronic kidney disease. (Chadban, Briganti et al. 2003).

National data presented in the Australia and New Zealand Dialysis and

Transplant (ANZDATA) registry reports indicate that more than 2000

Australians commence on renal replacement therapy every year and this

number has been increasing at a rate significantly higher than the population

growth over the last few decades. Dialysis and renal transplantation are the two

modes of renal replacement therapies available. In 2009, 2337(107 per million)

Australians commenced on renal replacement therapy; 1565 (72/million)

commenced dialysis and 772 (35/million) had renal transplantation. As of

December 2009 18,243(834/million) Australians have ESKD, out of which

10,341(473/million) were maintained on dialysis and 7902 (361/million) had

functioning transplants (ANZDATA 2010).

In Australia, diabetic nephropathy is the leading cause of ESKD accounting for

33% of all those with ESKD, followed by glomerulonephritis (23%) and

hypertension (13%) (ANZDATA 2010).

Renal transplantation is the best form of renal replacement therapy. Compared

with dialysis, transplantation not only improves the quality of life but also the

longevity (Ogutmen, Yildirim et al. 2006). Patient survival rates are better for

those with ESKD who are accepted for transplantation when compared with

28

those who are maintained on dialysis even after adjusting for all degrees of co-

morbidity.(Schnuelle, Lorenz et al. 1998; McDonald and Russ 2002)

In the Australian population, overall mortality rates on dialysis is 15.4/100

patient years compared with 1.23/100 patient years in the transplant population.

(Fig 1.1)

Fig 1.1: Age specific mortality rate for Australians on treated

with dialysis or renal transplantation.

Fig 1.1 depicts the age specific mortality rates for dialysis and transplant population compared with the general Australian population. Mortality rates are highest for the dialysis population. Source (ANZDATA 2010)

The source of a renal allograft can be either a deceased or living (related or

unrelated) donor. In Australia, 60% of the kidney transplants are from

deceased donors and 40% from live donors. (McDonald and Russ 2002)

(ANZDATA 2010). Strategies to improve the longevity of renal allograft function

will help reduce demand by reducing the need for repeat transplantation.

29

1.2. Reject ion of renal a llograft :

Transplantation of a donor kidney into the recipient evokes an immune

response because of the genetic differences between the donor and recipient.

This process is termed “rejection” and can be classified into 2 groups based on

the principle mechanisms of evoking the host immune response.

o T-cell mediated

o Antibody mediated

Renal transplantation requires life-long use of immunosuppressive agents to

suppress innate and acquired mechanisms of immunological graft rejection and

allow the recipient to accommodate the foreign kidney.

30

1.2.1 Cell Mediated Reject ion (CMR):

Cell mediated rejection is the most commonly encountered type of kidney

allograft rejection.

Fig 1.2 Mechanism of T-cell mediated rejection

Fig 1.2 is a simplified depiction of the cellular mechanisms involved in cell mediated rejection. See section 1.2.1 for further explanation. Adapted from (Nankivell and Alexander 2008) Abbreviations: APC- Antigen Presenting Cell; MHL- Major Histocompatibility Ligand; CD – Cluster of

Differentiation; TCR – T Cell Receptor; T reg – Regulator T Cell; IFN- Interferon; TGF β – Transforming Growth Factor β

Donor antigens are presented to the recipient lymphocytes by the antigen

presenting cells (APCs). Dendritic cells and macrophages are the predominant

APCs but B cells, tubular epithelial or endothelial cells can also present

antigens. Antigen presentation activates the naive CD4 T cells and requires a

co-signal which allows the activation of the T lymphocytes which can then

proliferate and enter the interstitial compartment of the allograft and invade the

31

tubular basement membrane (Fig 1.2). Histological hall mark of T-cell mediated

rejection is dense lymphocytic inflammatory infiltrate and mononuclear cells

invading the tubular basement membrane causing tubulitis. In general CMR

responds to glucocorticoids and resolves without any residual damage to the

renal allograft. (Nankivell and Alexander 2008)

1.2.2 Antibody Mediated Reject ion (AMR):

Fig 1.3 Mechanism of Antibody Mediated Rejection

Fig 1.3 is a simplified depiction of the cellular mechanisms involved in antibody mediated rejection. See section 1.2.2 for further explanation. Adapted from (Nankivell and Alexander 2008) Abbreviation: PMN- Polymorphonuclear neutrophil

Preformed or de-novo antibodies can mediate rejection without involving the

APCs. Antibodies that can trigger the immune response in the kidney allograft

include HLA antibodies, anti endothelial cell antibodies and ABO blood group

antibodies.

AMR can either be hyperacute or acute.

Hyperacute rejection: This occurs almost immediately after the graft is

implanted and the vascular clamps are released. This is usually due to

32

prior sensitization and preformed antibodies. Improvements in transplant

immunology cross match techniques and immunosuppressive treatments

have prevented hyper-acute rejection.

Acute AMR: Previous exposure to relevant HLA antigens commonly

causes generation of high titres of complement fixing antibodies which

target the major histocompatibility complex (MHC) antigens displayed by

the donor peri-tubular and glomerular capillary endothelium (Fig 1.3).

(Nankivell and Alexander 2008)

1.2.3 Chronic Reject ion:

Chronic rejection is defined as ongoing immune T and B cell mediated injury to

the allograft usually due to inadequate immunosuppression and /or antibodies

against the allograft. There is a progressive decline in renal function.

Histologically, this is characterized by invasion of renal the parenchyma with T-

cells. In chronic antibody mediated rejection there is an association with donor

specific HLA antibodies or non HLA antibodies and histological features such

as expansion and double- contouring of the glomerular basement membrane

and evidence for complement deposition known as Transplant Glomerulopathy

(TG) (Nankivell and Alexander 2008).

Chronic Rejection is difficult to treat and to date there are no established

therapies. Chronic rejection can lead to chronic allograft nephropathy (CAN)

which is the main focus of this thesis and is discussed in detail in section 1.4

33

1.3. Mechanism of act ion of different Classes of

Immunosuppressive agents:

The drugs used in long term maintenance immunosuppression are steroids,

CNI such as CyA and TAC, mTOR-I such as SRL and Everolimus (EVR), anti-

proliferative agents such as Azathioprine (AZA) and Mycophenolic acid (MPA).

The mechanisms of action of these agents are discussed further and

summarised in Fig 1.4.

Fig 1.4 Structure of T-cell and sites of action of

immunosuppressants.

Fig 1.4 is a simplified depiction of the sites of action of various immunosuppressants. See section 1.3 for further explanation. Source: Adapted from (Halloran 2004); Abbreviations: CD- Cluster of Differentiation; NFAT- Nuclear Factor of activated T cell; IKK – Inhibitor of Kappa B Kinase; MAP – Membrane Associated protein; AP-1- Activator Protein 1; NF –ĸB – Nuclear Factor ĸ B;

34

Glucocorticoids: They bind to the glucocorticoids receptors and

affect DNA transcription factors activator protein 1 (AP1) and nuclear

factor- KB (NF-ĸB).

Calcineurin Inhibitors (CNI): These agents inhibit the calcineurin

receptors which are activated by the antigen presenting cell (APC) via

the TCR/CD3 complex. CyA binds to cyclophilin and TAC to FKBP12

which prevents T cell activation and proliferation.

mTOR Inhibitors (mTOR-I): These act at a different site to the CNI

by inhibiting the Mammalian Target of Rapamycin (mTOR) and thus

arresting the cell cycle at the G1 phase. SRL prevents Inter leukin-2 (IL-

2) dependent T cell proliferation, by arresting the cell cycle at G1 phase.

The mechanism of action of mTOR-I are discussed in detail in

subsequent sections.

Mycophenolic Acid (MPA): MPA is the active form of the pro-

drugs Mycophenolate Mofetil and Mycophenolate Sodium. MPA inhibits

the nucleotide synthesis and prevents proliferation of the T and B cells.

Azathioprine (AZA): Acts by interfering with DNA synthesis and thus

inhibits proliferation of T and B lymphocytes. (Halloran 2004)

Modern immunosuppressive medications have revolutionized transplantation by

significantly improving the 1 year and 5 year graft survival rates because they

reduce early rejection rates to as low as 10% as shown in the SYMPHONY trial

(Ekberg, Tedesco-Silva et al. 2007). Despite impressive reductions in early

rates of allograft rejection, it is notable that long term graft survival has not

changed significantly over the past decades. (Fig 1.5 and Tab 1.1)

35

Fig 1.5 Renal allograft survival rates 1965-2008

Fig 1.5 shows the long term outcomes of the renal allograft survival stratified by era Source:(ANZDATA 2010)

Overall, the annual graft loss after 1 year post transplantation remains constant

with a rate of 3-5%. During the past 3 decades this has not significantly

improved despite the introduction of newer immunosuppressive agents.

(Pascual, Theruvath et al. 2002)

0.00

0.25

0.50

0.75

1.00

Gra

ft S

urv

iva

l

0 5 10 15 20 25 30 35 40

Years

1965-9 1970-4 1975-9 1980-4 1985-9

1990-4 1995-9 2000-4 2005-8

Primary Deceased Donor Grafts

Graft Survival - Australia and New Zealand

36

Table 1.1 Long term renal allograft survival rates

Survival rates (%) 1year 5 years 10 years 15 years 20 years

1970-1974 58.2 41.9 30.3 22.8 14.6

1975-1979 51.7 36.0 25.6 17.7 12.6

1980-1984 63.6 45.4 32.1 23.0 16.2

1985-1989 80.8 65.8 47.2 32.8 21.3

1990-1994 85.0 70.9 50.7 33.8

1995-1999 88.6 76.2 58.6

2000-2004 91.6 80.8

2005-2009 91.6

Table 1.1 The data in Fig 1.5 in tabulated. Source:(ANZDATA 2010)

In RTR, the main cause of graft loss after 5 years is CAN (44%). Death with a

functioning graft (40% - Patient death due to causes other than renal allograft

failure) is the next major cause of graft loss and malignancy (35%) and cardio-

vascular disease (30%) are major causes of death with functioning graft.

(ANZDATA 2010)

Because, CAN remains the leading cause of graft loss, any strategy to improve

long-term graft survival should include mechanisms to prevent or minimise the

progression of CAN.

37

1.4. Overview of Chronic Allograft Nephropathy

1.4.1 Definit ion of CAN:

Chronic allograft nephropathy is defined as a clinico-pathologic syndrome

consisting of

progressive allograft dysfunction which manifests as rising creatinine

(declining eGFR), proteinuria and hypertension

chronic histological damage defined as the presence of progressive

interstitial fibrosis and tubular atrophy.

The consequences of CAN and their progression eventually lead to graft loss

and the need to return to dialysis or further renal transplantation. (Nankivell and

Chapman 2006)

1.4.2 Nomenclature of CAN – A historical perspect ive

The terminology CAN represented different meanings depending upon the era

of literature reviewed. The distinction between acute allograft rejection (intense

inflammatory response and usually reversible) and chronic rejection (chronic

injury resulting in arterial intimal fibrosis usually due to an allo antibody) was

recognized as early as 1960s and was first described by Hume, Porter,

Jeannette et.al.(Hume, Merrill et al. ; Jeannet, Pinn et al.). This immune

mediated late allograft loss was referred as CAN.(Halloran, Melk et al. 1999)

With improvements in immunosuppressive medications and advances in

transplant immunology it became apparent that the late allograft injury is not

entirely due to immune mediated injury. There was shift in paradigm and the

38

term CAN denoted late allograft loss due to either immune or non-immune

mediated damage. In the early 1990s the nephrotoxicity due to CNI was thought

to be a major non- immune mediator of CAN. The terms CAN and CNI toxicity

were used interchangeably. Now it is being recognized that factors other than

CNI are associated with non-immune mediated late renal allograft injury. (Matas

2011). The change in paradigm is also reflected in the histological classification

of late allograft loss. The Banff 1997 histological classification of CAN does not

distinguish between immune/ non-immune mediated injury. (Racusen, Solez et

al. 1999). It is now recognized late allograft dysfunction is not synonymous

either with chronic rejection or chronic CNI toxicity. But it is represents

irreversible allograft damage which is a cumulative result of several immune

and non-immune mediated factors. The histological findings of interstitial

fibrosis and tubular atrophy are pathognomonic of CAN. As a consequence of

this understanding, Banff 2007 has introduced the terminology IFTA- NOS

(Interstitial Fibrosis/ Tubular Atrophy – Not Otherwise Specified) to denote the

histological damage that cannot be attributed to either immune factors or CNI

toxicity. (Solez, Colvin et al. 2008)

1.4.3 Mediators of CAN:

Because most of the late renal allograft loss has been attributed to CAN, the

risk factors associated with allograft loss are traditionally used as surrogate

determinants of CAN. The immune and non-immune mediated factors that

influence and contribute to the development of CAN can be further divided into

donor or recipient dependant factors (Fig 1.6). In general donor factors

contributing to CAN, are usually non-modifiable unless a recipient has more

than one potential live donor, has the opportunity to chose and hence to some

39

extent able modify some of the donor related risk factors. Similarly some of the

recipient factors such as preexisting diabetes, hypertension and family history

are non-modifiable. In the following sections risk factors of CAN are discussed

as immune and non-immune mediators and further divided into donor or

recipient factors.

1 .4 .3 .1 Immune Mediators of CAN

Donor factors

HLA mismatch and HLA antibodies:

Terasaki and Patel published a land mark paper in 1969 which showed the

presence of preformed cytotoxic antibodies against the donor was associated

with graft loss.(Patel and Terasaki 1969). Over the past few years the

significance of HLA antibodies against both donor specific and non- donor

specific antigens have been studied. Degree of HLA mis-matches between the

donor and recipient and the presence of anti-HLA antibodies are associated

with higher incidences of antibody mediated rejection and CAN. Presence

either de-novo or pre existing of HLA antibodies is associated with a higher

incidence of AMR and also late graft loss. (Mao, Terasaki et al. 2007). The

higher pre-transplant cumulative HLA antibody burden (as measured by Mean

Fluorescence Intensity - MFI) is also associated with greater incidence of late

graft loss. (Lefaucheur, Loupy et al. 2010; Loupy, Hill et al. 2012). Female sex,

multi parity, blood transfusions, higher degree of HLA mis matches and prior

transplantation predispose to the formation of anti HLA antibodies.

40

Role of Non-HLA antibodies:

Antibodies against non-HLA antigens have been identified in renal transplant

recipients and shown to be detrimental to graft function and lead to CAN. Non

HLA antibodies include those against MHC Class 1 chain related gene A

(MICA), Glutathione S-Transferase T, angiotensin II type 1 (AT1R) receptor and

endothelial cell antigens. These antibodies have also been implicated in

progressive graft loss. In addition other factors involved in variation in recipient

immune responses due to polymorphisms in the cytokines IL6, TNF-α,

coagulation factors (prothrombin and Factor V) and the fibrotic growth factor

caveolin contribute to the development of CAN.(Reinsmoen, Lai et al. 2010;

Sigdel, Li et al. 2012). (Dragun 2008; Moore, McKnight et al. 2010)

Recipient Factors

Rejection episodes including Sub-Clinical rejection:

Sub-clinical rejection (SCR) is defined as the presence of histological lesions of

rejection in clinically well functioning grafts i.e. stable creatinine and absent

proteinuria. In a series of protocol biopsies it has been shown that SCR

precedes the development of CAN. (Moreso, Ibernon et al. 2006). The number

of episodes of acute rejection is also associated with poor long term allograft

function (McDonald, Russ et al. 2007). This is thought to be due to the intense

allo-immune response and subsequent inflammatory damage which then

progresses to CAN.

Adequacy of Immune suppression:

Inadequate immunosuppression can lead to development of allo-antibodies.

This can result in an allo immune response which manifests as acute rejection

41

episodes, subclinical rejections or chronic anti body mediated rejection all of

which can lead to CAN. Non- compliance with immunosuppressants is a cause

of inadequate immunosuppression and allograft biopsies show higher degrees

of interstitial fibrosis and tubular atrophy scores in non-compliant RTRs than

those who were compliant with the immunosuppressive medications.(Lerut,

Kuypers et al. 2007)

1.4.3 .2 Non- Immune Mediators of CAN

Donor Factors

Donor Source:

Kidneys from live donors (related or unrelated) survive longer than those from

deceased donors.(Terasaki, Cecka et al. 1995; Fuggle, Allen et al. 2010) . The

allografts from live donors are less prone to peri-transplant injury compared with

the deceased donor allografts. Prolonged cold ischaemic time (time elapsed

between the kidney allograft clamped from the donor to being reperfused by the

recipient, during which time the organ is maintained in cold storage) is a strong

predictor of late allograft loss. Deceased donor allografts have significantly

higher cold ischaemic times(Salahudeen, Haider et al. 2003). Even after

correcting for cold ischaemic times the survival rates for live donor allografts are

superior to the deceased donor allografts.(Roodnat, van Riemsdijk et al. 2003).

Kidney allograft from donors who die of brain damage due to non hypoxic

causes have better survival rates than those who die of hypoxic brain injury.

(Halloran, Melk et al. 1999). Kidney allografts from non heart beating donors

have increased delayed graft function and lower eGFR at 1 and 3 years

compared with allografts from brain dead donors.(Pine, Goldsmith et al. 2010).

42

Cardiovascular instability, use of vasopressins and pro-inflammatory cytokine

release as a consequence of brain death which are different in not only the

setting of deceased vs. live donor, but also depending upon the cause of donor

death (brain vs. cardiac; hypoxic vs. non hypoxic brain injury) all lead to delayed

graft function and be associated with late allograft loss (Pratschke, Weiss et al.

2008). Kidneys from a live donor source have great longevity than from a

deceased donor; non hypoxic brain death in a donor source is associated with

better long term outcomes compared with a kidney allograft received from a

donor secondary to hypoxic brain injury or from a non-heart beating donor.

Donor Age

Increasing donor age is associated with higher risk of late graft loss in both live

and deceased donor kidney allografts.(Chavalitdhamrong, Gill et al. 2008;

Fuggle, Allen et al. 2010). The normal physiological phenomenon of ageing is

associated with glomerulosclerosis, tubular atrophy, interstitial fibrosis and

thickening of vessel wall. These lead to an effective decrease in nephron

number as donor age increases. Implantation biopsies show that the severity of

the histological changes in the donor is associated with reduce renal allograft

survival, in kidneys transplanted from older donors.(Remuzzi, Cravedi et al.

2006).

Donor Sex

The kidney allografts from male donor survive longer than from female donors.

Female kidneys are up to 15% smaller and hence have lower nephron number

and size. This difference in nephron mass contributes to increased

hyperfiltartion injury and subsequent graft loss. (Pratschke, Weiss et al. 2008)

43

Peri-transplant Factors

Delayed Graft Function (DGF)

Delayed graft function (defined as the need for dialysis any time during the

immediate post transplant period) is associated with increased episodes of

acute rejection episodes during the first year post transplantation. (Gentil,

Alcaide et al. 2003) . DGF is also independently associated with lower eGFR

and increased graft loss.(Yarlagadda, Coca et al. 2009). Prolonged cold

ischaemic time and transplantation from a deceased donor (Non-heart beating

donors > Brain Dead Donors) are independent risk factors for DGF and

contribute to the development of CAN.

Ischaemia reperfusion Injury (IRI)

Ischaemia to an allograft occurs during organ retrieval and subsequent

reperfusion by the recipient results in a cascade of inflammatory response. This

phenomenon in the recipient is termed as IRI. IRI leads to the adhesion of the

leukocytes to the vascular endothelium, infiltration of the these leukocytes into

the allograft tissue, increased graft immunogenicity and accelerated host

immune responses which trigger complex injury/repair pathways that promote

graft fibrosis (Timsit, Yuan et al. 2010) (Pratschke, Weiss et al. 2008) and

subsequent development of CAN.

Recipient factors

Hypertension, Post transplant Diabetes Mellitus (PTDM), dyslipidaemia and

proteinuria are not only non-immune mediators of CAN but also significant

cardiovascular risk factors. As in the general population the prevalence of these

risk factors increase with increasing recipient age.

44

Hypertension:

Activation of the Renin Angiotensin – Aldosterone System (RAAS) is associated

with preferential vasoconstriction of the efferent arterioles, sodium retention and

systemic hypertension. It also up regulates Transforming Growth Factor β (TGF

β) and promotes interstitial fibrosis and subsequently leads to IFTA. (Remuzzi,

Perico et al. 2005). Thus hypertension is not only a manifestation of CAN but is

also is an important risk factor for CAN, late renal allograft and patient loss.

(Opelz, Wujciak et al. 1998).

Post Transplant Diabetes Mellitus (PTDM) & Dyslipidaemia;

PTDM adversely affects long term allograft function and patient survival

(Helanterä, Ortiz et al.), (Demirci MS and A 2010) because of an increased

cardio vascular morbidity and mortality post transplantation.(Cosio, Kudva et al.

2005). Dyslipidaemia is a significant cardiovascular risk factor in RTR and

reduction in lipid levels with statins have shown an improvement in

cardiovascular morbidity in RTR (Jardine, Gaston et al. 2011) (Lentine and

Brennan 2004). Though dyslipidaemia has not been shown to impact on the

renal allograft dysfunction directly, it is possible that post transplant diabetes

and dyslipidaemia, by increasing the oxidative stress affect the vascular

endothelium and contribute to late allograft loss.ive stress. PTDM and

dyslipidaemia are discussed in detail in sections 1.7 and 1.9

Viral infections:

Viral infections such as BK virus nephropathy can lead to allograft damage by

activation of fibrotic pathways in the renal allograft. The role of cytomegalovirus

in chronic renal allograft damage is uncertain.(Li and Yang 2009).

45

Proteinuria:

Proteinuria is a manifestation of allograft damage and persistent proteinuria has

also been directly implicated in tubular injury and epithelial mesenchymal

transition leading to fibrosis and progressive allograft damage initiating a

vicious cycle.(Fernandez-Fresnedo, Plaza et al. 2004), (Li and Yang 2009). This

is discussed in detail in section 1.6

There is a complex interplay between various modifiable and non-modifiable

(both immune or-non-immune mediated) factors that can cause allograft

damage. (Fig1.6). Most of the donor and immune mediated factors are not

modifiable. However the use of immunosuppressive medications and host

factors such as diabetes, hypertension and dyslipidaemia are modifiable risk

factors and can significantly influence the renal allograft outcomes. It is these

modifiable metabolic factors that will be addressed in this thesis.

46

Fig 1.6 Pathogenesis of CAN.

Renal Allograft

Tubular DamageChronic Interstitial

Damage

Glomerular

Damage

CAN

(Allograft Dysfunction &

Failure)

Donor Factors

Age

Live vs. deceased

Cold Ischaemia

Co-morbidites

Recipient Factors

Age

HLA mismatch

PRA Level

Co-morbiditesInadequate

Immunosuppression

Inflammation

Sub-Clinical

Rejection

CyA**

&

TAC**

Cytokines and growth factors

Proteinuria Senescence**

Blood Vessels

Hypertension**

Diabetes Mellitus**

Dyslipidaemia**

Other Causes:

Recurrent GN

Transplant Glomerulopathy

Atubular

glomeruli

Cortical

Ischaemia

Ischaemia

DGF/ATN

CNI Toxicity**

Nephron Loss

Disruption of Internal

Architecture

** - Modifibale risk factors of CAN

Fig 1.6 shows the interactions of various immune and non-immune mediators of CAN Adapted from (Nankivell and Chapman 2006) Abbreviations: DGF – Delayed Graft Function; CNI – Calcineurin Inhibitor(s); ATN – Acute Tubular

Necrosis; PRA – Panel Reactive Antibodies; GN – Glomerulonephritis; CAN – Chronic Allograft Nephropathy;

1.4.4 Pathogenesis of CAN

The allograft damage in CAN is usually considered as the end result of

cumulative immune and non-immune mediated insults, which can be host or

donor related. Several models, complementary to each other have been have

been proposed to explain the pathogenesis of CAN.

1.4.4 .1 Chronic Reject ion Model:

This model suggests that chronic immune mediated allograft injury due to

inadequate immunosuppression of host immune responses results in allograft

47

damage. This mechanism was considered a key player in the development of

CAN in the pre CNI era. (Hume, Merrill et al. 1955) (Nankivell and Chapman

2006)

1.4.4 .2 Input-Stress model:

This model takes into account factors influencing the quality of the allograft and

includes donor age, source, cold ischaemic times (input factors) and post

transplant immune and non-immune stressors such as (episodes of rejection,

hypertension, diabetes- mellitus, proteinuria and dyslipidaemia). (Grinyo, Saval

et al.) (Timsit, Yuan et al. 2010).These factors may drive individual nephrons to

senescence and deplete the finite nephron mass leading to CAN. (Halloran,

Melk et al. 1999; Melk 2003; Nankivell and Chapman 2006)

1.4.4 .3 Cumulat ive damage Model:

Several immune and non-immune mediated time-dependent factors lead to

permanent damage of the nephrons Example: repeated episodes of acute

rejection, sub-clinical rejection, hypertension, diabetes etc. The allograft

dysfunction is the result of cumulative catastrophic failure of many individual

nephrons resulting in incremental loss of architectural integrity. (Halloran, Melk

et al. 1999; Melk 2003)

In summary it is important to note that all of these models consider that more

than one factor is responsible for the development of CAN and that it is the

resultant cumulative injury over time which leads to the irreversible damage of

the allograft.

48

1.4.5 Mechanisms of allograft injury:

There are several proposed mechanisms by which injury to specific segments

of the nephron leads to allograft failure.

1.4.5 .1 Internal architectural degradation:

All the mediators of CAN described above can cause damage to specific

segments of the nephron and interstitium.

Individual nephrons may fail due to glomerular, tubular or interstitial damage.

Summated damage of individual nephrons leads to ultimate architectural

degradation and failure of the allograft. (Kriz, Hartmann et al. 2001)

Glomerular damage:

This occurs due to glomerulosclerosis, transplant glomerulopathy or atubular

glomeruli. Atubular glomeruli are formed after irreversible tubular damage

results in disconnection of the glomerulus from the downstream nephron.

(Nankivell 2004) Chronic hypertension, prolonged CNI exposure are some of

the causes of renal allograft glomerulosclerosis, chronic antibody mediated

rejection leads to transplant glomerulopathy.

Tubular damage:

This occurs secondary to localized apoptosis or luminal obstruction by cellular

debris (Nankivell 2004).Tubulitis secondary to cell mediated rejection or

obstruction due to casts such as in oxalate nephropathy may cause of tubular

damage.

49

Interstitial damage:

Adhesions from segmentally injured glomeruli can cause the ultra-filtrate to

escape into the para-glomerular and para-tubular interstitial spaces, trigger

inflammatory process leading to interstitial fibrosis. (Nankivell 2004)

1.4.5 .2 Cort ical Ischaemia:

Tubular cells are metabolically active and hence susceptible to ischaemia of

any cause. Damage to the peri-tubular capillary (PTC) network results in tubulo-

interstitial damage and subsequently allograft dysfunction. (Basile 2004; Yasuo,

Tokihiko et al. 2005). Glomerulosclerosis, arteriolar hyalinosis due to chronic

CNI toxicity, vaso-constriction secondary to acute CNI toxicity, fibro-intimal

hyperplasia due to chronic hypertension and peri-tubular capillaritis in AMR are

some of the examples of the disease processes that lead to cortical ischaemia

and subsequent fibrosis.

1.4.5 .3 Chronic Inflammation:

Acute injury of the renal allograft due to any cause results in inflammation. As a

part of the injury repair pathway, partial or incomplete resolution of inflammation

leads to a vicious cycle of perpetual injury→ inflammation → enhanced allo-

recognition → further injury until allograft eventually fails.(Shishido, Asanuma et

al. 2003; Nankivell 2004)

1.4.5 .4 Epithelia l – Mesenchymal Transit ion (EMT):

Tubular injury resulting in loss of cell adhesion and transformation of tubular

cells to myo-fibroblasts, (under the influence of hypoxia or cytokines like TGF-

50

ß1, interleukin 1) has been proposed as a mechanism of progressive fibrosis

and allograft dysfunction. (Strutz ; Vongwiwatana, Tasanarong et al. 2005)

It is important to note that these proposed mechanisms of injury are not

independent of each other. In RTRs many of these mechanisms contribute to

allograft damage. For example chronic CNI toxicity can cause vasoconstriction

leading to ischaemia, tubular injury and release of cytokines causing EMT,

progressive fibrosis and allograft dysfunction.

1.4.6 Banff Histologica l Classificat ion of CAN

The histological features of CAN have been described by a consensus of

pathologists, nephrologists and immunologists further determined the criteria

denoted as the Banff ‘97 classification. This was later revised in 2007, called

Banff 2007. (Table 1.2)

The predominant histopathological changes of CAN are non-specific interstitial

fibrosis (ci), and tubular atrophy (ct), where the pre-fix ‘c’ denotes the chronicity

of the lesions. Additional features of CAN include glomerulopathy (cg),

expansion of mesangial matrix (mm) and vascular fibrous intimal thickening

(cv). The latter 3 attributes are considered to represent immune mediated

damage of the allograft. (Fig 1.7)

51

Fig 1.7 Histological changes of CAN

1.7a CAN. There is interstitial fibrosis, tubular atrophy and glomerulosclerosis in a patchy pattern. Infiltrates of small lymphocytes are present in the fibrotic interstitium and not in the non atrophic tubules. (PAS –Silver Stain x5)

1.7b Transplant obliterative arteriopathy with thickened intima infiltrated with inflammatory cells and thickened muscle walls. (PAS x5)

52

Table 1.2 Banff 2007 Classification

Table 1.2 explains the salient features of the BANFF 2007 histological classification.

Grade 0 Grade I

(Mild)

Grade II

(Moderate)

Grade III

(Severe)

Interstitial fibrosis(ci):

cortical area affected

ci0: ≤ 5% ci1: 6-25% ci2: 26-50% ci3: >50%

Tubular Atrophy (ct): area of cortical

tubules are atrophied

ct0: No tubular atrophy

ct1: up to 25%

ct2: 25-50%

ct3: >50%

Glomerulopathy(cg): Capillary loops

with double contours

cg0: <10%

cg1: 11- 25%

cg2: 26-50%

cg3: >50%

Vascular fibrous intimal thickening(cv):

Mesangial Matrix thickening (mm)

cv0: No change

mm0: No increase

cv1: up to 25%

mm1: up to 25%

cv2: 26-50%

mm2: 26-505

cv3: > 50%

mm3: >50%

53

1.4.6 .1 Banff 2007 updates

The Banff working group reviewed its classification of CAN in 2007 and the term

chronic allograft nephropathy was replaced with interstitial fibrosis and tubular

atrophy (IFTA) but the existing histological scoring categories remain

unchanged (Solez, Colvin et al. 2008). The main reason for this change in

nomenclature was to differentiate CAN from chronic cellular or antibody

mediated rejection and calcineurin inhibitor toxicity. In this thesis the term CAN

will be used and not IFTA.

1.4.7 Role of CNI in CAN

The CNI have significant effects upon renal micro-vascular function. In animals

and humans they cause renal afferent arteriolar vasoconstriction, reduced renal

blood flow and this leads acutely to reduced renal function. Acute CNI toxicity is

characterized by smooth muscle necrosis and early hyalinosis in afferent

arterioles and/or isometric vacoulation of proximal tubules. These early changes

are reversible (Liptak and Ivanyi 2006). However, the chronic damage due to

prolonged CNI exposure may play a role in progressive renal allograft damage

by immunological or non-immunological pathways. CNI induced

vasoconstriction leads to hypoxia and release of pro-inflammatory and pro-

fibrotic factors such as angiotensin 2, transforming Growth Factor – TGF β1.

CNI can also cause up-regulation of Toll like receptors (TLR) leading to

activation of Nuclear Transcription factor NFĸB and AP1 which activates

dendritic cells and T lymphocytes and eventually lead to chronic allograft

damage.(Li and Yang 2009). The patho-physiology of CNI nephrotoxicity is

depicted below. (Fig 1.8).

54

Fig 1.8 Mechanism of Chronic CNI toxicity

Calcineurin Inhibitors

(CyA & TAC)

Vasoconstriction

Ischaemia

Release of Angiotensin

II & TGF – β1

Inflammation and

Fibrosis

CAN

Activation of NFkβ and

AP1

Up regulation of TLR2 &

TLR4 and their Ligands

Fig 1.8 depicts the immune (right) and vascular mechanisms (left) through which chronic CNI exposure leads to allograft injury. Adapted from (Li and Yang 2009); Abbreviations: TLR- Toll Like Receptors; NFĸβ - Nuclear Transcription factor ĸB;

AP1- Activator Protein 1; TGF – β1 – Transforming Growth Factor β1

55

1.4.7 .1 Histological Changes of CNI Nephrotoxicity:

The histological changes of chronic CNI toxicity include arteriolar hyalinosis,

striped interstitial fibrosis and tubular atrophy (Fig 1.9). The glomeruli exhibit

non-specific changes such as glomerular hypertrophy, expansion of mesangial

matrix, focal or global sclerosis. (Liptak and Ivanyi 2006; Shimizu, Ishida et al.

2008). Acute CNI nephrotoxicity seems to correlate well with the serum drug

levels and responds to dose reduction, but the chronic histological changes do

not regress after CNI withdrawal.(Servais, Toupance et al. 2009)

Banff Classification of CNI Toxicity:

The Banff’97 classification has described the following quantitative criteria for

arteriolar hyaline thickening (ah)

Ah0: No PAS positive hyaline thickening

Ah1: Mild to moderate PAS positive hyaline thickening in at least one arteriole

Ah2: Moderate to severe PAS positive hyaline thickening in more than one

arteriole

Ah3: Severe PAS positive hyaline thickening in many arterioles

Banff 2007 has recommended alternate scoring for arteriolar hyalinosis as

described below.

Banff 2007 modification of ‘ah’

Aah0: No typical lesions of CNI arteriolopathy

Aah1: Replacement of degenerated smooth muscle cells by hyaline deposits

present in only one arteriole, no circumferential involvement.


present in more than one arteriole, no circumferential involvement.

56


with circumferential involvement irrespective of the number of arterioles.

Fig 1.9 Histological Features of CNI Toxicity

1.9a: CNI Toxicity. The arterioles show hyaline deposits (H&E x20)

1.9 b CNI Toxicity: The nodular hyaline deposits are seen in the afferent and efferent arterioles. There is glomerular mesangial expansion. (PAS x20)

57

1.4.8 The Natural History of CAN

The histological changes of CAN can be detected as early as 3 months post

transplantation and usually pre dates clinical evidence of allograft dysfunction

and frequently progressive and ultimately lead to allograft failure. (Li and Yang

2009). At one year post transplantation approximately 95% of renal allografts

show evidence of at least Banff grade I CAN and 75% show evidence of CNI

nephrotoxicity. By 5 years post transplantation these figures increase to 100%

and 93% respectively. (Nankivell 2003). These studies were based on earlier

use of CNI with higher doses. More recently the use of CNI minimization

protocols has been shown to improve graft function in the early transplant

period (Ekberg, Tedesco-Silva et al. 2007). Because chronic CNI nephrotoxicity

is not directly related to the serum levels of the drug, the long-term effects of

CNI minimisation upon CAN remain to be elucidated.

In addition to the direct nephrotoxicity and contribution to the development of

the histological features of CAN, CNI have additional deleterious effects upon

lipids, blood pressure and glucose metabolism which are independent risk

factors for the development of CAN and adversely affect allograft and patient

outcomes. CyA and TAC have different effects on glucose and lipid metabolism.

TAC is associated with a higher rates of PTDM, due to its effects upon the

pancreatic beta cells and insulin deficiency but has less effect on LDL-

cholesterol levels and blood pressure(Dmitrewski 2001). CyA has higher rates

of hypertension and increased LDL-cholesterol levels but a lower rate of post-

transplant diabetes. Diabetes and dyslipidaemia are risk factors for CAN and

have significant impact on long-term graft and patient survival. Therefore

measures to minimize these effects by the use of alternative

58

immunosuppressive strategies such as mTOR inhibition, or CNI minimization /

avoidance have been developed (Haller and Oberbauer 2009; Oberbauer and

Haller 2009). In addition, the early detection and intervention upon modifiable

risk factors such as diabetes, hypertension and dyslipidaemia may prevent or

slow the progression of CAN.(Sharif, Shabir et al. 2011) (Campistol 2009)

1.5 Role of mTOR inhibitors in CAN:

mTOR-I are a relatively new class of immunosuppressive agents that bind with

the specific cytosolic protein FKBP-12. The FKBP-12-sirolimus complex inhibits

the activation of the mammalian target of rapamycin (mTOR), a critical kinase

for cell cycle progression. The inhibition of mTOR results in blockage of several

specific signal transduction pathways. The net result is the inhibition of

lymphocyte activation, which results in immunosuppression (Fig 1.4).

mTOR-I are not nephrotoxic because they do not influence renal blood flow or

micro-vascular function. SRL has been shown to reduce inflammation and

improve endothelial dysfunction (Maamoun, Esmail et al. 2011) compared with

CNI, (Sancho, Pastor et al. 2010) For these reasons mTOR-I were considered

as an alternative immunosuppressive to prevent or reduce CAN or to replace

CNI therapy in those patients with established CAN. In addition to their

immunosuppressive properties SRL also has anti-proliferative properties and

has been shown to decrease the incidence of malignancy, especially non-

melanoma skin cancers. Hence in the last few years there is an increasing trend

to convert RTRs to mTOR-I with the aim to preserve allograft function and

prevent malignancies (Schena and Pascoe 2009). There are several studies

59

that have demonstrated that conversion from CNI based immunosuppression to

mTOR-I improve renal function. Oberbauer et.al for the Rapamune

Maintenance Regimen (RMR) Study (Oberbauer, Segoloni et al. 2005), Kreis

et.al for the Sirolimus European renal Transplant Study (Kreis, Cisterne et al.)

and Flechner et.al (Flechner, Goldfarb et al. 2002) published some of the early

randomized control trials which showed that mTOR-I based

immunosuppression improved eGFR in RTR compared with maintenance on a

CNI. Some of the more recent studies that have evaluated the renal function

and adverse effects of mTOR-I are summarised in Table.1.3.

60

Table 1.3 Summary of renal outcomes and side effect profile following mTOR-I conversion in transplant

recipients

1. (Uslu, Töz et al. 2009) 2. (Lebranchu 2009) 3. (Schena and Pascoe 2009) 4. (Teperman 2009) 5. (Egbuna 2009)

Table 1.3 summarises some of the most recent studies. The renal outcomes and side-effect profile following conversion to mTOR-I in transplant recipients are reported.

Publication

Year

Study design Improvement

in eGFR

Proteinuria Other side effects Comments

Uslu1

2009 Retrospective Yes Yes Dyslipidaemia Had baseline and 12 months post

conversion histology follow-up.

CONCEPT2

2009 Randomised Control

Trial; Conversion to

SRL at 12 weeks post

transplantation

Yes No Aphthous Ulcers, Diarrhoea oedema Included low immunological risk

patients. Excluded patients with

Creatinine clearance of less 40ml/min

and Proteinuria>1g/day

CONVERT3


Trial

Yes Yes Aphthous ulcers, Dyslipidaemia ,

infections

Showed benefit in RTR with a baseline

GFR of>40ml/min.

Lower incidence of malignancy

STN4


trial

Yes Not mentioned Dyslipidaemia Renal function in liver Transplant

recipients; 12 month follow-up

Egbuna5

2009 Retrospective Yes Yes Mucosal and skin lesions;

Dyslipidaemia

Compared SRL conversion steroid

withdrawal or steroid continuation.

Follow-up was 12 months

61

The relevant studies are discussed in detail in Chapter 3, section 3.4.

Though there is significant improvement in eGFR following conversion to SRL,

these studies also demonstrate that SRL has several side effects that have the

potential to limit their widespread use or replace entirely CNI based treatments.

The two major side effects of SRL, proteinuria and dyslipidaemia can be

detrimental to both graft function and patient morbidity. Additional and common

side effects including skin rash, GI symptoms, lymphoedema, interstitial

pneumonitis, impaired wound healing and reduced male fertility, have also

limited the wider use of mTOR-I (Remuzzi, Ruggenenti et al. 2009) (Cravedi,

Ruggenenti et al. 2010). mTOR-I with or without CNI are not optimal when used

as first-line immunosuppression because of an increase risk of rejection in the

early transplantation period with or without a CNI. (Flechner 2008; Budde,

Becker et al. 2011). The discussion about the suitability of mTOR-I as primary

immunosuppression is beyond the scope of this review. However the use of

CNI in the early transplant period and later conversion to mTOR-I before

permanent allograft injury occurs is an accepted paradigm.(Sharif, Shabir et al.

2011) (Flechner, Kobashigawa et al. 2008)

The effect of SRL on glucose metabolism in RTR however is uncertain

(discussed in section 1.7) and this thesis will study the effect of SRL upon

proteinuria, glucose and lipid metabolism, because of their significant risk to

patient and allograft health, and also because they have the potential for

modification by therapeutic interventions.

62

1.6. Prote inuria post Transplantat ion:

1.6.1 Introduct ion

Proteinuria refers to the detection of increased of protein levels in the urine.

Proteinuria can be quantified by 24 hour collections or random sampling

corrected for urine flow by the ratio of protein: creatinine. Up to 150mg of

protein/day is considered normal. Proteinuria of more than 150mg/day (Protein:

Creatinine ratio >21 mg/mmol) is considered pathological and is a result of one

or more of the following mechanisms (Cameron JS, 1998).

o increase glomerular permeability (glomerular proteinuria)

o tubulo-interstitial disease (tubular proteinuria)

o Increase filtration through normal glomeruli (overflow proteinuria)

1.6.1 .1 Glomerular Proteinuria:

Glomerular Proteinuria is caused by the loss of glomerular charge barrier or

glomerular size barrier or a combination of both. The extent of proteinuria can

range from as little as 150 mg/ day to >50g /day or more in extreme cases.

Protein excretion greater than 3.0g/ day (PCR >360mg/mmol) is described as

nephrotic range proteinuria. Glomerular proteinuria is non-selective and albumin

is the predominant protein.

1.6.1 .2 Tubular Proteinuria:

Tubular proteinuria occurs when the primary site of injury is tubulo-interstitium

and failure of the tubules to reabsorb the filtered proteins. Proteinuria in these

63

conditions is usually low-grade i.e. < 2g/day (~PCR 200mg/mmol). In addition to

tubular proteins such as the microglobulin, and other low molecular weight

proteins, only low levels of albuminuria will be present due to impairment in the

tubular re-absorption.

1.6.1 .3 Overflow Proteinuria:

This is due to excess amounts of an abnormal protein filtered through normal

glomeruli e.g. light chains in multiple myeloma.

1.6.2 Post Transplant Proteinuria:

Proteinuria is one of the clinical features of CAN. The major cause of proteinuria

post transplantation is glomerular proteinuria (Chung, Kil Park et al. 2000). In

RTR proteinuria is a predictor of graft loss and cardiovascular mortality

(Fernandez-Fresnedo, Plaza et al. 2004). Immunosuppressants themselves can

directly influence the extent of proteinuria in RTRs CNIs can reduce proteinuria

whilst mTOR-I increase proteinuria. (Barama 2008).

1.6.3 Sirolimus and Proteinuria:

One of the major physiological effects of SRL in RTRs is the development of

significant proteinuria, which may require cessation of therapy (Dervaux,

Caillard et al. 2005; Moore, Light et al. 2007) (Sahin, Sahin et al. 2006). The

exact mechanism by which SRL causes proteinuria is not clear. Most studies

have demonstrated proteinuria in the setting of CNI withdrawal and CAN

(Letavernier, Pe'raldi et al. 2005; ska, Banasik et al. 2006) (Ruiz, Diekmann et

64

al. 2005; Boratynska 2006). Under these circumstances, whether SRL causes

proteinuria by direct nephrotoxic effects, or whether the proteinuria is due to the

effects of CNI withdrawal, or both mechanisms is difficult to determine. There

have been reports of new onset proteinuria including nephrotic range

proteinuria and rarely, de-novo glomerulonephritis (Dittrich, Schmaldienst et al.

2004) following conversion from CNI to SRL, consistent with a direct

nephrotoxic effect. SRL may cause proteinuria by glomerular injury including

direct damage to podocytes (Torras, Herrero-Fresneda et al. 2009), down

regulation of Vascular Endothelial Growth Factor - VEGF receptors (Izzedine,

Brocheriou et al. 2005) or loss of nephrin expression in the glomeruli (Biancone,

Bussolati et al. 2010). In animal models, SRL causes worsening of the

glomerular proteinuria due to podocyte injury but its anti-proliferative effects

may reduce tubulo-interstitial proteinuria by reducing the tubulo-interstitial

fibrosis (Torras, Herrero-Fresneda et al. 2009). However, there is conflicting

evidence about the effects of SRL on the tubular interstitium, with some studies

showing that SRL causes tubulo interstitial damage, preventing protein re-

absorption and leading to tubular proteinuria. (Straathof-Galema 2006).

The mechanism(s) by which SRL causes proteinuria in-vivo still remain to be

fully elucidated. It is notable that in some studies, a pre-conversion proteinuria

more than 800mg/day has been shown to predict the development of significant

proteinuria post conversion suggesting that pre-existing injury may predispose

to this complication (Diekmann, Budde et al. 2004; Diekmann 2008). However,

there are no studies in RTR, which have identified whether the proteinuria

secondary to SRL is glomerular, tubular or a combination of both. There are no

studies that have specifically examined the histological features or the dominant

65

damage to specific histological compartment that predict post conversion

proteinuria in RTRs. This research has studied pre conversion clinical and

histological factors that can predict proteinuria post conversion to SRL. The

results are reported in Chapter 3

66

1.7 Overview of Post Transplant Diabetes

Mellitus

1.7.1 Introduct ion

Post transplant diabetes mellitus (PTDM - the total of prevalent and incident

diabetes) is a frequent cause of complications after kidney transplantation and

has been associated with both poor graft outcomes and an increase in patient

cardiovascular morbidity and mortality (Crutchlow and Bloom 2007; Balla 2009).

Death with a functioning graft due to cardiovascular causes is a major cause of

graft loss. New onset diabetes after transplant (NODAT) is the term used to

identify incident diabetes occurring after renal transplantation in distinction to

those where diabetes predates the transplant. The incidence rates of NODAT in

RTRs are in the order of 10 to 40 %.(Balla 2009). The non modifiable risk

factors for NODAT include age, genetic background, family history of diabetes

and pre transplant impaired glucose tolerance. Modifiable risk factors include

obesity, viral infections and immunosuppressants (Shah, Kasravi et al. 2006;

Balla 2009) (Hur, Kim et al. 2007; Roland 2008; Sharif and Baboolal 2010).

NODAT, similar to Type 2 Diabetes Mellitus (T2DM) is characterized by chronic

hyperglycaemia, insulin resistance and relative insulin deficiency. Some

immunosuppressants commonly used after kidney transplantation such as

glucocorticoids, CNI and possibly mTOR-I have significant impact on glucose

metabolism, whilst others such as Azathioprine and Mycophenolic acid are

neutral. (Chow and Li 2008).

67

1.7.2 Steroids and PTDM:

Steroid treatment has been shown to be a determinant of insulin resistance post

transplantation. Glucocorticoids increase hepatic glucose production, decrease

peripheral insulin sensitivity, increase weight and increase insulin resistance

and increase the risk of NODAT. Dose reduction of steroids has been shown to

improve insulin resistance (Crutchlow and Bloom 2007) (Oterdoom, de Vries et

al. 2007; Roland 2008). However complete steroid withdrawal has not shown to

reduce the risk of NODAT compared with low dose prednisolone (Midtvedt,

Hjelmesaeth et al. 2004).

1.7.3 CNI and PTDM:

CyA and TAC impair insulin secretion and predispose to NODAT. Animal and

human studies have shown that CNI, especially TAC is directly toxic to the

pancreatic islet cells. In transplant recipients with hyperglycaemia, biopsy of the

pancreas has demonstrated that CNI exposure is associated with cytoplasmic

swelling and vacuolisation, implying toxicity to pancreatic β cells. This effect

was more pronounced in those patients receiving TAC compared with CyA.

TAC is more diabetogenic than CyA.(Drachenberg 1999). The hyperglycaemia

associated with TAC is also dose-dependent with higher doses causing more

pancreatic islet cell damage and the effect of CNI is independent and additive to

the effects of steroids causing PTDM. (Marchetti p 2000; Larsen 2006) (Heisel,

Heisel et al. 2004; Webster A 2005; Shah, Kasravi et al. 2006; Chadban 2008;

Roland 2008; Lee 2010; Morales 2010).

68

1.7.4 SRL and PTDM:

The role of SRL on glucose metabolism is uncertain. mTOR inhibition has been

reported to have variable effects on varied effect on glucose metabolism. To

understand how mTOR-I may impact upon glucose metabolism, it is essential to

review the mTOR pathway The mTOR pathway and the impact of mTOR

inhibition on glucose metabolism are described in detail in section 1.8

69

1.8. The mTOR pathw ay and mTOR inhibitors:

The mTOR protein is a serine-threonine kinase that is a part of a complex

intracellular signaling pathway which modulates cell growth and proliferation by

regulating protein synthesis. The upstream components of the signaling

pathway(s) activate the mTOR and the downstream components are effector

pathways of protein synthesis.(Hay and Sonenberg 2004; Hartford and Ratain

2007; Vodenik, Rovira et al. 2009) (Wullschleger, Loewith et al. 2006) (Fig 1.10)

1.8.1 The upstream components of mTOR

The upstream activators of the mTOR pathway include:

1. Insulin via the insulin receptor substrate -1 (IRS-1)

2. Amino acids via Phosphoinonositide-3 kinase (PI3K ) pathway

3. Other growth factors via the phospoinositide-3 kinase (PI3K) / Akt

pathway

4. Energy status of the cell via LKB1 and AMP- activated kinase (AMPK)

The upstream inhibitors of the mTOR

1. Stress signals such as DNA damage and hypoxia act via the TSC

pathway to cause inhibition of mTOR pathway

70

Fig 1.10 The mTOR pathway

IR

Insulin

IRS - 1

Class 1

PI 3K

Protein Kinase B

Akt

TSC 1 & 2

Rheb

mTOR/Raptor

Complex

S 6K4E – BPs 1

eIF 4E eIF 4B S6 e EF 2K

Protein Translation

Glucose

Energy Status

AMPK

Stress

(DNA damage

Hypoxia)

Growth Factors

& Harmones

mTOR/Rictor

Complex

GTP

Class 3

PI 3K

Amino Acids

Siro

limu

s &

Oth

er

mT

OR

In

hib

ito

rs

1

2

1

3

4

5

Positive Feedback

Inhibitory Feedback

Adapted from (Hartford and Ratain 2007), (Wullschleger, Loewith et al. 2006);

Fig 1.10 depicts the simplified version of the mTOR pathway. Pathways 1, 2, 3, 4 & 5 are the upstream regulators of the mTOR complex. Abbreviations: IR – Insulin receptor; IRS – Insulin receptor substrate; PI3K – Phosphoinositide – 3

Kinase; AMPK- adenosine Mono-phosphate Kinase; TSC – Tuberous Sclerosis gene; 4E-BP- Eukaryotic translation initiation factor – Binding protein; eIF-4E - Eukaryotic translation initiation factor; S6 k- S6 Kinase.

71

1.8.2 The dow nstream effectors of mTOR pathw ay

These pathways control the translation of specific mRNAs and protein

synthesis.

1. Phosphorylation of eukaryotic translation initiation factor – Binding

Protein1 (4E-BP1), which in turn inhibits the eIF-4E (Eukaryotic

translation initiation factor) – Binding Protein1, resulting in protein

synthesis

2. Phosphorylation and activation of S6 Kinase 1 (S6K1). This also has an

inhibitory feed back by inhibiting IRS-1

3. Activation of eukaryotic translation initiation factor 4 gamma (e-IF4G)

1 .8 .3 Posit ive and Negat ive Feed-back in mTOR

pathw ay:

mTOR signaling is also controlled by several negative and positive feed-back

loops. In the cell the mTOR forms a complex to either GBL protein (raptor

proteins-mTOR1) or the rictor proteins (mTOR2) (Hay and Sonenberg 2004;

Hartford and Ratain 2007; Varma 2008; Vodenik, Rovira et al. 2009). (Fig1.11)

The rictor complex is not inhibited by the mTOR-I and hence will not be

discussed further. The mTOR GBL / raptor complex receives input from the

upstream pathways like PI3K/Akt, TSC1/TSC2 and AMPK and acts through

downstream effectors S6 kinase (S6K, and translation factor inhibitor E4BP1).

This pathway is critical for cell growth, cell cycle progression and regulation of

organ size. (Hay and Sonenberg 2004) (Wullschleger, Loewith et al. 2006). SRL

72

and other mTOR-I bind to the FK506 intracellular binding protein (FKBP12). The

rapamycin – FKBP12 complex that is formed inhibits the mTOR by

destabilization of mTOR/raptor complex thereby interfering with the ability of the

mTOR / raptor complex to signal the downstream effectors. (Di Paolo,

Teutonico et al. 2006)

73

1.8.4 Role of mTOR signaling in glucose metabolism:

1.8.4 .1 Mechanisms by w hich mTOR activat ion may cause

glucose intolerance and insulin resistance:

Reduced function of Insulin Receptor (IR) and IR substrate (IRS)- 1contributes

to NIDDM in humans (White 1998). Nutritional excess, chronic hyperglycaemia

and/or obesity which are predisposing factors for the development of insulin

resistance and non-insulin-dependent diabetes mellitus (NIDDM) are also

potent activators of mTOR (pathways 2 & 4, Fig 1.10).

Over activation of mTOR pathways even in physiologic conditions involving

excess nutrient supply or hyper-insulinaemia promote phosphorylation of IRS-1

and IRS-2 that inhibit their function, promote degradation and possibly inhibit

protein translation. Hyperstimulation of downstream S6K pathway can stimulate

the inhibitory phosphorylation of IRS-1 (i.e. negative feedback) resulting in

insulin resistance.

The mTOR/GBL/raptor complex can be activated by insulin (via the insulin

receptor substrate IRS 1) or other growth factors via the PI3K/Akt complex

(Hartford and Ratain 2007). IRS 2 expression results in β-cell growth,

proliferation and survival, whereas reduction of IRS-2 causes beta cell

apoptosis. mTOR activation by hyperglycaemia results in the inhibition of IRS-2

and hence beta cell apoptosis. IRS-1 and PI3K play an important role insulin

regulated metabolic process and reduced function of insulin receptor and IRS-1

can contribute to non- insulin dependent diabetes mellitus in humans (White

1998)

74

Activation of mTOR complex by amino-acids and hyperglycaemia have all

shown to increase insulin resistance through PI3K /S6K pathway and

suppression of IRS-1-dependent PI3-kinase/Akt signaling. (Tremblay and

Marette 2001) (Tzatsos and Kandror 2006).

Chronic activation of mTOR by glucose (and/or IGF-1) in β-cells can lead to

increased Ser/Thr phosphorylation of IRS-2 that targets it for proteosomal

degradation, resulting in decreased IRS-2 expression and increased β-cell

apoptosis and lead to decrease β-cell mass and hence predispose to diabetes.

(Briaud, Dickson et al. 2005)

These studies demonstrate that mTOR activation results in altered signaling

that would promote or increase insulin resistance suggesting that mTOR

inhibition (by SRL) should improve insulin resistance. The complex pathways of

mTOR activation also has other feed-back mechanisms that modify these

effects and these changes may mean that mTOR inhibition have the capacity to

increase or reduce insulin resistance as discussed in the following sections.

75

1.8.4 .2 Mechanisms by w hich mTOR inhibit ion may cause

glucose intolerance and insulin resistance:

If mTOR stimulation increases insulin resistance then blocking the mTOR

complex with SRL should decrease insulin resistance. However, there are

mechanisms by which mTOR inhibition can cause insulin resistance. SRL can

worsen insulin resistance and cause diabetes by direct toxic effects pancreatic

islet cells, by inhibiting the growth cycle. (Bell 2003). Animal studies show,

mTOR / S6K pathway which is critical for beta cell adaptation to hyperglycaemia

when chronically inhibited by mTOR-I augment insulin resistance, beta cell

dysfunction and death. (Fraenkel 2008). Long term administration of SRL is

associated with hyper-insulinaemia and worsening glucose tolerance in the

mouse model of nutrition dependent T2DM. Decrease in insulin stimulated Akt

Phosphorylation and glucose transporter protein synthesis by chronic mTOR

inhibition has been suggested as one possible mechanism. (Chang 2009)

Studies in humans have also demonstrated that mTOR inhibition promotes

insulin resistance. Studies in RTR show that when challenged in vivo with

insulin, chronic inhibition of the mTOR/S6K pathway by SRL is associated with

an impaired activation of IRS-1, IRS-2 and AKT pathways causing insulin

resistance. (Di Paolo, Teutonico et al. 2006).

76

1.8.4 .3 Mechanisms by w hich mTOR Inhibit ion may improve

insulin resistance:

There is also evidence that mTOR inhibition can reduce insulin resistance.

Animal studies have shown that SRL prevents the onset of Type 1 diabetes

(Baeder, Sredy et al. 1992).

mTOR inhibition in humans by SRL promotes insulin mediated glucose uptake

by skeletal muscles in the setting of amino-acid excess. (Tremblay and Marette

2001). mTOR-I stimulate insulin mediated glucose uptake in humans in the

setting of hyper-insulinaemia and nutrient abundance, conditions which are

known to activate the mTOR /S6K pathway. (Krebs 2007). SRL can prevent

insulin resistance caused by chronic insulin treatment by preventing

i) reduction of IRS-1 protein levels

ii) down regulation of acute insulin-induced Protein Kinase B (PKB)

phosphorylation and

iii) down regulation of insulin stimulated glucose transport. (Berg

2002)

The pro inflammatory cytokine interleukin 6 (IL6) levels correlate with obesity,

insulin resistance and predict the development of T2DM. In vitro, mTOR

inhibition is shown to ameliorate IL-6 induced insulin resistance in liver cells

through a pathway independent of S6K1 protein (Kim 2008)

77

1.8.5 Conflict ing role of mTOR inhibit ion on glucose

metabolism:

Mechanisms described in sections 1.8.4.1 – 1.8.4.3 are mostly derived from in-

vitro studies, animal models or in vivo studies conducted under strict

experimental conditions using healthy volunteers. It is not clear whether same

mechanisms function in the setting of chronic mTOR inhibition in the post renal

transplantation setting, where multiple other factors affecting glucose and

insulin regulation are involved.

Chronic and long-term hyperglycaemia causes pancreatic beta cell apoptosis,

whereas in the short term hyperglycaemia promotes beta cell stimulation.

mTOR signaling has varied effects on glucose metabolism depending upon the

nutritional status, insulin and glycaemic status weight and adiposity and whether

the duration of mTOR inhibition is acute or chronic. Hence mTOR inhibition can

either alleviate or aggravate insulin resistance depending upon the baseline

conditions.

1.8.6 Effect of mTOR inhibit ion on glucose metabolism

in RTRs

The use of mTOR-I, especially in the setting of CNI withdrawal is anticipated to

have a significant impact upon glucose metabolism. Whether mTOR-I will

ameliorate or accentuate insulin resistance and its effect upon the cause or cure

NODAT, may depend upon the baseline characteristics of RTRs and additional

risk factors for NODAT and the duration and intensity of mTOR inhibition. Table

78

1.4 summarises the some of the available and most relevant studies and the

clinical implications of MTOR inhibitors on glucose metabolism in renal

transplant recipients and highlights the variability in the outcome measures

reported and conclusions obtained.

79

Table 1.4 SRL and PTDM in RTRS- Summary of published studies

Continued…

Study Study design Comparator NODAT as

primary

end point

Follow-up

(months)

SRL associated

with

PTDM/NODAT

Comments

Kahan1 Randomised Control

Trial;

CyA with SRL 2 or

5mg

No 12 NO NODAT not defined

Kasiske2 Retrospective

USRDS data

CyA, TAC& SRL No No Based on anti-diabetic

prescriptions

Teutonico3 Prospective CyA, TAC& SRL Yes 6 Yes

Araki4 Retrospective CyA, TAC& SRL Yes 39 No Used ADA guidelines

Arellano5 Retrospective None No 35 No NODAT not defined

80

1. (Kahan 2000) 2. (Kasiske, Snyder et al. 2003) 3. (Teutonico, Schena et al. 2005) 4. (Araki, Flechner et al. 2006) 5. (Arellano, Campistol et al. 2007) 6. (Veroux, Corona et al. 2008) 7. (Johnston, Rose et al. 2008) 8. (Laecke 2009)

Table 1.4 summarises studies which have evaluated post transplant diabetes in the setting of mTOR-I. Abbreviations: USRDS – United States Renal Data System; CyA- Cyclosporine A; TAC – Tacrolimus; SRL – Sirolimus; NODAT – New onset Diabetes after transplantation.

Study Study design Comparator NODAT as

primary end

point

Follow-up

(months)

SRL associated

with NODAT

Comments

Veroux6 Retrospective CyA, TAC& SRL Yes 21 No New onset fasting

hyperglycaemia was

defined as NODAT

Johnston7 Retrospective

USRDS

CyA, TAC& SRL Yes Yes Based on anti-diabetic

prescriptions

Van Laecke8 Retrospective CyA, TAC& SRL No 3 Yes Compared RTRs with

or without NODAT and

analysed risk factors

81

1.8.7 Limitat ions of the exist ing studies

These studies have several major limitations. Most are retrospective and the

criteria for diagnosing NODAT are not standardised. Use of other

immunosuppressive agents, steroids BMI and age (which are significant risk

factors for development of diabetes & insulin resistance) and target were SRL

levels not reported in many of the studies. (Pavlakis and Goldfarb-Rumyantzev

2008)

Therefore interpretation of these conflicting studies is difficult and the

conclusions drawn are open to criticism and require additional study. The

variability in analysis and reporting of these trials has influenced the design and

reporting of the prospective study of SRL conversion from a CNI upon

measures of glucose and insulin metabolism in RTRs described in Chapter 4 of

this thesis.

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1.9 Post Transplant Dyslipidaemia:

1.9.1 Overview of the lipid metabolism:

The major lipids in human plasma are free fatty acids (FFA), Cholesterol (CHL),

Cholesterol-Esters (CE), triglycerides (TGL) and phospholipids (PL).

1.9.1 .1 Lipids:

All lipids except FFA are transported in the form of lipoproteins (LP) in plasma.

LP are spherical particles which are made of lipid and protein molecules. TGL

and CE (hydrophobic) which are non-polar lipids constitute the core of the

lipoproteins. PL and CHL (which are amphipathic) cover the surface of the

lipoprotein. Apolipoproteins are present on the surface of the lipoproteins.

Figure 1.11 shows the basic structure of a lipoprotein.

83

Fig 1.11 Basic Structure of Lipoprotein

Fig 1.11 depicts the simplified version of the structure of a lipoprotein. Phospholipids, cholesterol and Apo lipoproteins are present on the surface the lipo protein.;

1.9.1 .2 Lipoproteins:

Lipoproteins are classified into five major classes based on their densities:

Chylomicrons (CM) transport dietary cholesterol and triglycerides

from intestine to adipose tissue, muscles and liver. The major lipid is

TGL

Very Low Density Lipoprotein (VLDL) is synthesized in the liver from

endogenous lipids.

Intermediate Density Lipoprotein (IDL) is formed during lipolysis of

VLDL to LDL and contains relatively less triglyceride and more

cholesterol.

84

Low Density Lipoprotein (LDL) is synthesized in the liver and is the

major carrier of plasma cholesterol and has very low TGL content

High Density Lipoprotein (HDL) is synthesized in the liver and

intestine and plays a major role in mobilizing the cholesterol from the

peripheral tissues.(Rader D.J. 2012)

1.9.1 .3 Apolipoproteins:

Apolipoproteins are a class of proteins that are present on the surface of the

lipoproteins, provide stability to the lipoproteins and play a major role in their

metabolism.

Apolipoprotein A (Apo-A):

Apo A is found predominantly in HDL. Isoform includes AI, AII and AIV.

Apolipoproteins B (Apo-B):

Apo-B comprises of two isoforms, Apo B 100 rich in VLDL particles, VLDL

remnant particles and LDL particles and Apo B48 rich in Chylomicron and

Chylomicron- remnants. Because of the longer half life of LDL particle (3-4days)

compared with VLDL particles, LDL particles account for 90% of apo B in the

plasma. Apo B is synthesized by the liver and has the region that binds to the

LDL receptor (LDLr) (Sniderman, Couture et al. 2010) .

Apo C Lipoprotein (Apo- C):

Apo-C Synthesized by the liver and is present in all the lipoproteins except LDL.

85

Table 1.5 Function of Apo-lipoproteins

Apolipoprotein Lipoprotein Function

AI,II and IV HDL,CM AI is Structural component of

HDL; LCAT activator; Role of AII

and IV unknown

B48

B100

CM

VLDL, IDL, LDL

B48 is structural component of

CM;

B100 is the structural

component of VLDL,IDL,LDL;

Ligand for LDL receptor

CI,CII,CIII All lipoproteins

except LDL

C1 inhibits uptake of CM and

VLDL remnants by the liver;

C2: activator of LPL;

CIII Inhibitor of LPL

Apo E All lipoproteins

except LDL

Binds lipoproteins to the LDLr,

LRP and ApoE receptor

Table 1.5 explains the function of the different classes of apo lipoproteins; Adapted from (Rader D.J. 2012) Abbreviations: Apo – Apolipoproteins; LDL – Low density lipoprotein; VLDL – Very Low density lipoprotein; HDL – High density Lipoprotein; LDLr- LL receptor; LRP – LDLr relate protein

Apolipoprotein E (Apo-E):

Apo-E is synthesized by the liver and mediates the uptake of chylomicron, IDL,

VLDL and LDL by the liver by LDLr and LDLr related protein. It exists in 3 major

isoforms E2, E3 and E4. Absence of Apo E causes increase in plasma levels of

chylomicron and VLDL remnants and cause premature atherosclerosis. (Rader

D.J. 2012).

86

1.9.2 Lipid Transport:

Fig: 1.12 Endogenous and Exogenous Lipid Transport

Fig 1.12 shows the endogenous and exogenous pathways of the Lipid Cycle Adapted from: (Vaziri 2003); Abbreviations :C- cholesterol; CE- Cholesterol ester; TG- triglyceride; HDL- High density Lipoprotein; IDL

- Intermediate density Lipoprotein; VLDL- Very low density Lipoprotein; LDL- Low Density lipoprotein.

87

1.9.2 .1 Exogenous Pathw ay:

This is used to distribute dietary lipids to various parts of the body. (Fig 1.12)

Dietary triglyceride and cholesterol are incorporated into the chylomicrons and

are delivered to the adipose tissue and skeletal muscles in the form of FFA.

This is mediated by Apo C proteins. Lipoprotein lipase is the enzyme that splits

the TGL into glycerol and FFA. A deficiency in this enzyme causes

hypertriglyceridaemia, which is one of the mechanisms proposed for the

hypertriglyceridaemia associated with ESKD. (Vaziri 2003)

1.9.2 .2 Endogenous pathw ay:

The source of the lipids (TGL, CE &PL) is the liver rather than the intestine. (Fig

1.14) Liver incorporates these lipids to form VLDL incorporating Apo-B. The

hepatic lipoprotein lipase is the enzyme that splits the VLDL to release TGL to

the tissues. Deficiency of hepatic LPL causes a delay in the breakdown of VLDL

and can contribute to hypertriglyceridaemia.(Rader D.J. 2012)

88

1.9.3 Post Transplant Dyslipidaemia :

Dyslipidaemia is a major risk factor for cardio vascular events post renal

transplantation (Jardine, Fellstram et al. 2005). Immunosuppressants play a

major role in post transplant dyslipidaemia.(Kanbay, Yildirir et al. 2006). Steroid

induced dyslipidaemia is a consequence of weight gain, peripheral insulin

resistance and increased hepatic synthesis of VLDL. CyA causes

hypercholesterolaemia by reducing the activity of 7 alpha hydroxylase in the

liver which is the rate limiting step for cholesterol catabolism. CYA increases

LDL and TC levels by increasing hepatic lipase activity and decreased

lipoprotein lipase activity which results in the impaired clearance on LDL and

VLDL. (Vaziri, Liang et al. 2000). Tacrolimus does not significantly alter the lipid

or lipoprotein profile of renal transplant recipients. (Deleuze, Garrigue et al.

2006).

1.9.3 .1 Effect of MTOR inhibit ion on lipid metabolism in RTRs:

Several studies in RTRs have consistently shown that SRL induces mixed

hyper-cholesterolaemia and hypertriglyceridaemia. Dyslipidaemia is one of the

major side-effects that limits the use of mTOR-I in RTRs. Mixed dyslipidaemia is

also seen in heart and liver transplant recipients receiving mTOR-I.(Tenderich

2007; Watson, Gimson et al. 2007). The dyslipidaemia associated with mTOR-I

is neither dependant on the age, sex, pre-existing lipid profile of RTR nor the

dose of SRL. Some of the older and recent studies in RTRs demonstrating the

effect of SRL on lipid metabolism are presented in Table 1.6. It is worth noting

that the earlier studies used higher target levels of SRL compared with more

recent studies, but in both instances SRL was associated mixed dyslipidaemia.

89

Table 1.6 Studies in RTRs showing SRL induces dyslipidaemia

1. (Groth 1999) 2. (Kahan 2000).. 3. (Morrisett, Abdel-Fattah et al. 2002) 4. (Wlodarczyk, Vitko et al. 2005) 5. (Kasiske 2008)

Table 1.6 summarises some of the relevant studies in RTRs showing SL induced dyslipidaemias. Abbreviations; N/A – Information not available/ provided; TC – Total Cholesterol; TGL - Triglyceride

Study SRL level

ng/ml)

Increase TC Increase TGL Comments Statin Use

Groth-19991 15-30 Yes Yes RCT 40%

Kahan -20002 15-30 Yes Yes RCT 60%

Morisset-20023 N/A Yes Yes Prospective

SRL 10mg/day

N/A

Wlodarczyk-20054 N/A

Yes Yes Prospective

SRL+TAC(2doses 0.5

or 2mg/day)

N/A

Kasiske-20085 N/A Yes Yes Systematic Review Variable

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1.9.3 .2 Limitat ions of exist ing studies describing the e ffect of

mTOR–I on lipid metabolism in RTRs:

Dyslipidaemia was not primary end-point in many of the trials and the majority

did not measure a more comprehensive analysis of lipid classes, sub fractions

or lipoproteins levels. Hence the mechanism of lipid abnormalities caused by

SRL has not been comprehensively studied.

Animal studies have shown mTOR stimulation promotes fat storage by

suppressing lipolysis and stimulation of de-novo lipogenesis and mTOR

inhibition stimulates lipolysis with elevated FFA levels (Chakrabarti, English et

al.). In vitro studies have demonstrated that mTOR inhibition causes reduced

lipid uptake and reduce fat cell number there by impairing the capacity of

adipose tissue for plasma clearance and reduction in Peroxisome proliferator –

activated receptor (PPAR- ) expression contributing to hypertriglyceridaemia.

(Houde, Brule et al. 2010). However studies exploring the mechanism of SRL

induced dyslipidaemia in RTR are very limited. The relevant studies are

discussed in detail in Chapter 4, section 4.4. Understanding how SRL affects

lipid metabolism in RTR will help us understand and manage this common and

important cardiovascular risk factor. The effect of SRL on cardiac risk factors in

RTRs and the effect of SRL conversion upon lipids and lipoproteins in routine

clinical (non-experimental) settings and their relationship with possible

mechanisms of SRL induced dyslipidaemias form part of the prospective study

and reported in Chapter 4.

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1.10 Summary:

mTOR-I improve renal allograft function (GFR) and because of their anti-

proliferative properties have been effective in reducing malignancies post

transplantation. However some of their side-effects preclude their wide-spread

clinical use in RTR. Proteinuria and dyslipidaemia are two major side-effects of

mTOR-I. These are also important cardio-vascular risk factors. The effect of

mTOR-I upon PTDM, which is another significant cardiovascular risk factor, is

uncertain. Over recent years, much research has focused on the improvement

in the renal allograft function and the side-effects of mTOR-I in RTR. However

work in RTR, focusing on the predictors of improved renal allograft function, the

mechanisms of mTOR-I induced proteinuria, dyslipidaemia and glucose

intolerance, in the clinical setting are limited and should be the focus of future

studies.

92

Chapter 2 RESEARCH METHODOLOGY

93

2.1 Introduct ion:

In 2002, the renal unit at Royal Perth Hospital (RPH) commenced the use of the

mTOR-I SRL as a component of therapeutic agents for maintenance

immunosuppression. It is the policy of our centre to use SRL after an initial

period of CNI use and to biopsy the renal allograft prior to mTOR-I conversion in

order to determine that conversion is clinically appropriate and that when

relevant, the cause of allograft dysfunction is known to be potentially responsive

to elimination of CNI and introduction of an mTOR-I. RTRs with biopsy proven

CAN or normal renal histology were eligible for conversion, while patients with

active glomerular disease or rejection were excluded.

2.2 Study Hypotheses:

In RTR with biopsy confirmed CAN who are converted to SRL from a CNI

1. Baseline proteinuria independently determines the degree of change in renal

function (eGFR).

2. Evidence of allograft injury scored by renal histology will independently

predict the post-conversion change in eGFR and occurrence of proteinuria.

3. SRL has independent and potentially adverse effects upon glucose and lipid

metabolism.

94

2.3 Aims:

In a cohort of RTRs with CAN

1) To retrospectively

compare the graft function (eGFR) and proteinuria between

those converted to SRL and those maintained on a CNI.

determine the relationship between pre conversion renal

histology (as defined by BANFF criteria) and post conversion

eGFR and proteinuria

identify clinical and histological predictors of successful

conversion to SRL from a CNI.

2) To prospectively determine the effect of SRL upon glucose and lipid

metabolism at 3 and 12 months following conversion from a CNI

based immunosuppressive regimen.

95

2.4 Study Design

This study comprises a retrospective and a prospective component.

2.4.1 Inclusion Criteria:

Adult RTR with

Exposure to CNI (CyA or TAC) for at least 6 months post

transplantation.

Biopsy proven and/ or clinical CAN.

2 .4 .2 Exclusion Criteria

RTR who were converted to SRL due to indications other than CAN

BK virus nephropathy.

Non-skin malignancies

Salvage therapy for recurrent rejections

2 .4 .3 Study Populat ion

The biopsy database maintained at RPH renal unit was interrogated and RTRs

who underwent renal biopsy and had a diagnosis of CAN were identified.

Between January 2002 and December 2009, 97 RTRs had biopsy proven CAN

and satisfied the inclusion and exclusion criteria. From the pharmacy database

an additional 13 RTRS who were maintained on SRL and either had declined

biopsy or had a medical contra-indication but had a clinical scenario consistent

96

with the diagnosis of CAN and satisfied other inclusion criteria were also

identified. These 110 RTRs comprised the study population. The study

population was divided into a retrospective and a prospective group. (Fig 2.1)

Fig 2.1 Study Design

Fig: 2.1 Shows patient screening, allocation and study design Abbreviations: EVR – Everolimus: RTR – Renal Transplant Recipient: SG – Sirolimus Group: CG-

Control Group; CAN- Chronic allograft nephropathy

97

2.4.3 .1 Retrospective Study Group

85 RTRs satisfied the entry criteria and entered the retrospective study group.

51/ 85 were converted from a CNI based regimen to SRL (defined as Sirolimus

Group =SG) and the remaining 34 RTRs continued on CNI (defined as the

control group =CG). Conversion to SRL or continuing on a CNI was based on a

clinical decision by the treating nephrologist.

2 .4 .3 .2 Prospective Study Group:

Between June 2006 and December 2009 25 /110 RTRS, who were electively

converted to SRL and satisfied the selection criteria, entered the prospective

study (the prospective group = PG). Patients entering this study had to fulfill the

following additional inclusion criteria:

Not diabetic at the time of conversion.

Signed Informed consent to participate in the study (Appendix 2- PIS)

2.5 Study Methods:

Patients’ medical records were reviewed and the data shown in Table 2.1 were

collected for all 110 patients.

98

2.5.1 Data collect ion:

The following data were collected retrospectively by reviewing the patient

records.

Table 2.1 Data Collected in the Study Population

Data Characteristic Specific Data Collected

General Baseline demographics ( age , sex, date of

transplant)

Primary Renal Disease

Duration of dialysis

Immune mediators of

graft function

Number of previous transplants

HLA mis-matches

Maintenance Immunosuppression

Duration of CNI exposure

Non-immune mediators

of graft function

Donor source (cadaveric vs. live),

Donor age

Diabetic Status

Histology* Based on BANFF 2007 criteria

Clinical Parameters* Serial Blood pressure readings

Laboratory Parameters* Serum Creatinine

Urine protein: Creatinine Ratio

Table 2.1 shows the list of all the clinical, laboratory and histological data that was collected from the study population (retrospective and prospective studies) * Data not specifically measured for the purposes of this study, but collected from patient records

99

2.5.2 Prospect ive Group Study Protocol

Table 2.2 Additional data collected in the Prospective Group

Data

Characteristic

Additional Data Collected

Laboratory

parameters*

OGTT (glucose and insulin), FFA, HbA1c

Lipids: Total Cholesterol, HDL, LDL, Apo-

lipoprotein A& B,

Trough SRL levels

Hs CRP

Urinary Spot PCR/ ACR (Albumin: Creatinine

ratio

Clinical

Parameters*

Blood pressure, height and weight

Table 2.2 shows the list of all additional clinical and laboratory data that was collected only in the prospective group. *Collected for the purposes of this study at the time of conversion and at 3 and 12 months post conversion to SRL

Blood Pressure: Blood Pressure was measured with wall mounted aneroid

sphygmomanometer, in the clinic setting with patient sitting after 5 min of rest.

Cuff size adjusted to patient arm circumference.

Lipids: Samples were obtained after 12 hours fasting.

Spot PCR/ ACR: Random sample was collected.

100

2.6 Laboratory Methods:

All biochemical tests used were performed as routine clinical care using

standard methods at Path-west Laboratories. (Table 2.3)

Table 2.3 Laboratory Methods

Test

Methodology

Apo lipoprotein A1 The assay is done by BNII, an immunochemical reaction

using Siemens reagent (Siemens Healthcare Diagnostics

Inc. Newark, DE 19714 USA

Apo-lipoprotein B The assay is done by BNII, an immunochemical reaction

using Siemens reagent (Siemens Healthcare Diagnostics

Inc. Newark, DE 19714 USA

Total Cholesterol HITACHI 917 using cholesterol esterase (Roche

Diagnostics, Indianapolis, IN USA)

C-Peptide Immulite 2000 C-Peptide is a solid phase, two site

chemiluminescent immunometric assay

Creatinine By Creatinine Reagent (Abbott Diagnostics, Abbott

Laboratories, Abbott Park, IL 60064, USA)

FFA Cobas Mira Analyser (Roche Diagnostics, Basel,

Switzerland)

Glucose by HITACHI 917 using Hexokinase in Roche reagent

(Roche Diagnostics, Indianapolis, IN USA)

Hb A1C The HbA1c assay method is the Biorad Variant II

101

Test

Methodology

Haemoglobin A1c program. This is a HPLC method, using

a cation exchange cartridge. HbA1c is identified on the

basis of it's elution time, and labile A1c and carbamylated

haemoglobin elute earlier and do not interfere.

HDL/LDL by HITACHI 917 using PEG-modified enzymes and

dextran sulphate in Roche reagent (Roche Diagnostics,

Indianapolis, IN USA)

Insulin Immulite 2000 Insulin (Siemens Medical Solutions

Diagnostic, 5210 Pacific Concourse Drive, Los Angeles,

CA 90045-6900-USA)

SRL Micro particle enzyme immunoassay (MEIA) using the

Abbott Imx analyser (Abbott Diagnostics, NSW Australia)

Triglycerides by HITACHI 917 using lipoprotein lipase in Roche reagent

(Roche Diagnostics, Indianapolis, IN USA)

Urea by HITACHI 917 using urease in Roche reagent (Roche

Diagnostics, Indianapolis, IN USA)

Urine Albumin by HITACHI 917 using bromocresol green in Roche

reagent (Roche Diagnostics, Indianapolis, IN USA)

Urine protein by HITACHI 917 using Benzethonium chloride in Roche

reagent, turbidimetric method (Roche Diagnostics,

Indianapolis, IN USA)

Table 2.3 explains the laboratory methods and the reagents used for the tests used in this research. .All tests n the retrospective study are routine clinical care. Blood samples for the additional tests in the prospective study, were frozen stored under standard conditions at Royal Perth Hospital Biochemistry department and analyzed in batches.

102

2.7 Study Protocols

2.7.1 Standard Oral Glucose Tolerance Test:

This was performed according to WHO standards. Glucose and insulin levels

were measured after 8 hours of fasting, 60 and 120 min post intake of 75g of

glucose.(American Diabetes Association). Fasting C-peptide was also

measured.

2.7.2 Sirolimus conversion Protocol:

The CNI was stopped abruptly and replaced with SRL – there was no

overlapping period. Some patients were given 5 mg of SRL (loading dose) on

day 1 and subsequently 2mg per day. SRL levels were measured day 5 of

conversion aiming to achieve a trough level of 5-10 ng/ml. The dose of anti-

proliferative agents (Mycophenolic Acid “MPA” or Azathioprine “AZA”) and

steroids were maintained or altered according to the clinicians’ discretion.

2.7.3 MPA / AZA dosing

The RTRs were maintained on one of the two types of Mycophenolate

preparations commercially available [Mycophenolate Mofetil (MMF) - Cellcept®

Roche Pharma, Italy and Mycophenolate Sodium- Myfortic® Novartis]

depending upon the clinician preference. For the purposes of this study the

Myfortic doses were converted to equivalent MMF doses (dose equivalence

was calculated on the basis that 1000mg MMF = 720mg Myfortic) and reported

as the dose of MPA.

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2.7.4 Stat in Use in PG

The RTRs who were maintained on a statin were not required to stop the statin

for the purposes of entering the prospective study. Though this is a limitation of

the research methodology, it was felt that in this high cardio-vascular risk

population, cessation of statin therapy for the purposes of clinical research was

inappropriate.

2.8 Follow - up

2 .8 .1 Retrospect ive Study

Patients were followed up until June 2011.

2.8.2 Prospect ive Study

12 months from time of entry.

2.9 End points:

2 .9 .1 Retrospect ive Study

eGFR and Proteinuria at census

Graft Failure

Conversion Failure

2.9.2 Prospect ive Study

The PG was followed up for 12 months post conversion and measures of

glucose and lipid metabolism were collected as detailed in table 2.2

104

2.10 Definit ions:

Time “0”:

Date of biopsy or date of conversion to SRL (if biopsy was not done).

eGFR:

The eGFR is calculated using the abbreviated MDRD Formula:

eGFR (ml/min/1.73m2) = 186 x (S Cr/88.4-1.154 x (Age)-0.203 x (0.742 if female)

We have chosen abbreviated MDRD to calculate the eGFR as this it is the most

validated equation of the commonly used equations which is routinely used by

our laboratories to report eGFR using serum creatinine.(Mariat 2005; The

Australasian Creatinine Consensus Working Group 2005; Jong 2006)

Proteinuria and albuminuria:

Measured as spot PCR and ACR mg/mmol.

Significant Proteinuria:

PCR >100mg/mmol. An arbitrary cut-off of 100 was chosen because this

approximates to 1g of proteinuria/ day, which most clinicians would consider

significant.

Nephrotic range Proteinuria:

PCR >300mg/mmol

Graft Failure:

Progressive deterioration in renal allograft function resulting in initiation of renal

replacement therapy.

105

Conversion Failure:

RTRs in SG who discontinued SRL due to adverse outcome or side-effects of

SRL therapy.

Diabetes:

Defined as a American Diabetic Association 2010 guidelines (American

Diabetes Association 2010)

Fasting blood glucose of ≥ 7 mmol/l or 2 hour plasma glucose of > 11.1 mmol.

Measures of Insulin resistance and Insulin Sensitivity:

The gold standard for determining the insulin sensitivity is the euglycaemic

hyperinsulinaemic glucose clamp technique, which was described by De Fronzo

et.al in 1979. This technique is cumbersome and expensive and cannot be used

in larger studies or in day-to- day clinical practice. Several surrogate estimates

of insulin sensitivity and insulin resistance based on the insulin and glucose

values obtained during standard oral glucose tolerance tests have been shown

to correlate well with the gold standard glucose clamp technique. OGTT derived

measures of Insulin sensitivity and Resistance, which include HOMA- IR score

HOMA-IR), Insulin Sensitivity Index (ISItx), Disposition Index (DI) and Metabolic

Clearance rate of Glucose have all been validated in renal transplant

population(Stumvoll, Mitrakou et al. 2000; Hjelmesæth 2001). These measures

have been used in this study to assess the changes in the glucose metabolism.

Insulin resistance was calculated using the Homeostasis Model

Assessment Score (HOMA-IR) = Ins0 (μmol x Glu0 (mmol/l) / 22.5);

106

HOMA –IR has been validated to mirror the glucose clamp technique in

the assessment of insulin resistance (Bonora, Targher et al. 2000).

A Value of >2.5 is defined as IR. Increasing values of the HOMA-IR score

indicate increasing insulin resistance.

OGTT derived Insulin sensitivity indices for transplantation (ISItx): is

calculated using the formula [0.028 - 0 0.0032 x BMI (kg/m2) –

0.0000645 X Ins 120 (pmol/l) – 0.00375 x Glu 120 (mmol/l)]. Decreasing

values means increasing insulin resistance.(Hjelmesæth 2001;

Teutonico, Schena et al. 2005) . Ins120 and Glu120 represent Insulin &

Glucose values measured at 2 hours during the standard OGTT.

Disposition index (DI) is as a measure for the ability of the pancreatic

beta cell to compensate for various degrees of insulin resistance and has

been studied in RTRs. (Teutonico, Schena et al. 2005) In

normoglycaemic individuals DI is a constant whereas it declines with the

development of glucose intolerance

DI = ISItx x Secr*1phaseInsulin release and ß – cell function is estimated using

BMI and insulin & glucose values at 0 and 60 min from OGTT

*Secr1phase = 728 +3.537 x Ins0 -120.3x Glu60 + 1.341 x Ins 60 + 21.27 x

BMI

Metabolic Clearance rate of Glucose (MCR) = 19.24 – (0.281x BMI) –

0.00498x Ins120) – (0.333xGlu120). The MCR values decline with

increasing insulin resistance.

The values ISItx, DI, MCR are generated for specific populations and do not

have a “normal reference range”. Comparisons of the values within the

population and interpretation based on the pre-post values are recommended.

107

2.11 Stat ist ical Methods:

2.11.1 Descript ive Stat ist ics:

All continuous variables were examined for normality of distribution using

histograms and box plots. Normally distributed data were reported as mean +/-

standard deviation for descriptive purposes and mean +/- standard error of the

mean for comparative purposes. Data that were not normally distributed were

logarithmically transformed and re-examined for normality of distribution. If

logarithmic transformation normalized the data distribution they were presented

as geometric mean (95% Confidence Intervals-CI). Non normalised data were

summarised using proportions, medians, and inter-quartile range (IQR) as

appropriate. Differences between baseline characteristics of the two groups

were investigated using T-Test for normally distributed data, Wilcoxon rank sum

tests for continuous variable for skewed distributions and chi square tests for

categorical variables. Fisher's exact test was performed when the number

(25% or more) of expected values in the table was small (<5).

Software used: SPSS v. 19 (Statistical Package for Social Sciences, Chicago,

IL, USA).

Additional statistical methods used to analyze the results in the retrospective

and prospective studies are described in subsequent sections.

2.11.2 Addit ional tests used in Retrospective Study:

Scatter plots for each outcome over time, overlaid with the Locally Weighted

Scatter plot Smoothing (LOWESS) fit were examined to determine if non linear

terms were required to model the data. The fit was assessed to be

108

predominantly linear. Longitudinal outcomes were assessed using Linear

Mixed Modeling with patient and time specified as random effects, generating

models with not only random intercepts but also random slopes. Interaction

terms between time and group were tested to investigate differences in

outcomes over time between CG and SG.

The relationships between baseline histological features and eGFR over time

were investigated using a manual backward step-wise linear mixed model

regression. Each variable was added to a “base” model that incorporated time,

group and their interaction, to determine if a main effects association was

present. Three way interactions between time group and the histological

variable and their lower order terms were then included to identify if the effects

varied over time between groups. Only significant interaction terms are

reported. All factors and their interaction terms with p values <0.1 were added

to the base model and a backward stepwise process was applied to determine

the final model. Variables that were not significant at 0.05 were removed one at

a time and the resulting model investigated for evidence of confounding. This

process continued until all variables in the model were either significant or

important in the model.

Subgroup analyses of outcomes at conversion or at census and their

association with baseline histological features were performed using Fisher’s

exact test due to the small samples involved. Fisher’s exact test was used to

determine the association between baseline histological features, proteinuria,

eGFR and post conversion eGFR and proteinuria measures.

109

Software used: StataCorp2011. Stata Statistical Software Release 12. College

station, TX : Stata Group LP

2.11.3 Addit ional Tests used in the Prospective Study:

The measures of glucose metabolism and lipid fractions were examined in the

same group on more than two separate occasions. Hence, within subjects

ANOVA (repeated measures of ANOVA) was used to compare the differences

among the means.

The Mauchly’s test of sphericity (testing homogeneity of covariance) was used

prior to conducting a within subjects ANOVA to lower the risk of Type 1 error

associated with multiple comparisons. If the data failed the sphericity test (P-

value <0.05), SPSS modified the ANOVA F test to make it more conservative

and less likely to reject the null hypothesis by reducing the degrees of freedom

around the numerator and the denominator of the F ratio. If the r- ANOVA was

significant, paired t-tests were performed with Bonferroni adjustment for 3-way

comparison and P-value of <0.02 was considered significant in the 3 way T-

tests.

Software used: SPSS v. 19 (Statistical Package for Social Sciences, Chicago,

IL, USA).

110

2.12 Ethica l issues:

This study has been approved by the Ethics committee of RPH. (Appendix 1)

2.13 Results:

The results of the retrospective study are presented in Chapter 3 and those of

the prospective study in chapter 4

111

Chapter 3 EVALUATION OF RENAL OUTCOMES IN

RENAL TRANSPLANT RECIPIENTS WITH

CHRONIC ALLOGRAFT DYSFUNCTION

FOLLOWING CONVERSION FROM

CALCINEURIN INHIBITORS TO

SIROLIMUS AND THE PREDICTORS OF

SUCCESSFUL CONVERSION

112

3.1 Hypothesis and Aims

3.1.1 Hypothesis:

In RTRs with biopsy confirmed CAN who are converted to SRL from CNI

Baseline proteinuria will independently determine the degree of change

in renal function (eGFR).

Evidence of allograft injury scored by renal histology will independently

predict the post-conversion change in eGFR and occurrence of

proteinuria.

3.1.2 Aims:

In a cohort of RTRs with CAN, to retrospectively

i. Examine the effects of SRL upon changes in graft function

(eGFR) and proteinuria and compare with those maintained

on a CNI.

ii. Study the relationship between pre conversion renal

histology (as defined by BANFF criteria) and post

conversion eGFR and proteinuria

iii. Identify clinical and histological predictors of successful

conversion to SRL from a CNI.

113

3.2 Methodology:

This has been described in detail in Chapter 2.

85 RTRS with clinical and/or biopsy proven CAN who satisfied the inclusion and

exclusion criteria were followed for a median 64 months (IQR 12-92). 51/85

were converted to SRL (defined as SG) and 34/85 continued on the CNI

(defined as CG). The decision to convert or maintain CNI use was based on a

clinical decision by the treating nephrologist.

3.2.1 Stat ist ical Methods

As explained in Chapter 2, data were summarised using proportions, medians

and IQR. Longitudinal outcomes were analysed using Linear Mixed Modeling.

The relationship between baseline histological features and eGFR over time

was investigated using a manual backward step-wise linear mixed model

regression. Sub-group analysis of PCR outcomes was done using Fisher’s

exact test due to the small samples involved.

114

3.3 Results

3.3.1 Baseline Clinical Characterist ics:

Table 3.1 Baseline Characteristics of RTRs in SG and CG

Characteristics SG CG P- value

Number of RTR@ 51 34 -

Male: Female (%)@ 63 : 37 58: 42 NS

Age at Tx (years)* 41.8+/- 12.6 42.7 +/- 11.5 0.6

Years on CNI ** 4.5 (1.4,9.1) 4.8 (3.1,11.4) 0.2

Pre-Transplant DM@ 9.8 % 8.8% 1.0

DM @ conversion** 22 % (11/51) 38 %(13/34) 0.14

eGFR ml/min** 48.3 (20,55) 40.8( 20,54) 0.06

Urinary PCR(mg/mmol) ** 14.5 .(9,26) 21.5 (6.5,57) 0.42

Use of Steroids (%)@ 70 71 1.0

Total HLA –Mismatch ** 3 (2,4) 3 (2,5) 0.7

*Values expressed as mean +/- Standard Deviation; **Values expressed as median (with 95% Confidence Intervals); @ Values expressed represent actual numbers P ≤ 0.05 is significant. Table 3.1 shows the differences in the baseline characteristics between the two groups. Abbreviations: SG – Sirolimus Group; CG – Control Group; RTR- Renal Transplant recipients; Tx –

Transplantation; CNI - Calcineurin Inhibitors; DM - Diabetes Mellitus; eGFR- estimated Glomerular Filtration Rate; PCR- Protein : Creatinine ratio

115

At baseline the two groups were similar for age, sex distribution, donor age,

HLA mismatches, duration of CNI exposure, prevalence of PTDM and steroid

use. Although not quite attaining statistical significance, the eGFR was lower in

the CG compared with the SG (41 vs. 48 ml/min P=0.06). Both groups had low

levels of proteinuria at baseline [14 (SG) vs. 21 (CG) mg/mmol]. Because of the

retrospective nature of the study ACR measurements were not routinely done

and hence not reported here. This has been addressed in the prospective study

presented in Chapter 4.

3.3.2 Baseline Histological Characterist ics:

41 / 51 of the SG and all 34 CG patients had undergone a renal biopsy prior to

conversion. These biopsies were coded based on the Banff 2007 criteria by a

single histo-pathologist, blinded to the clinical outcomes, for the purposes of this

research. Figures 3.1 to 3.4 depict the frequency distribution of the baseline

histological scores.

116

3.3.2 .1 Tubulo-interst it ia l injury: “ci” and “ct” scores

Fig 3.1 Baseline ‘ci” scores between SG and CG

Fig 3.1 shows the distribution of the severity of Chronic interstitial fibrosis- “ci “ scores as defined by BANFF 2007 between the Sirolimus Group –SG (blue) and Control Group- CG (red)

There was no difference in the chronic interstitial fibrosis – “ci” scores at

baseline between the groups. (Fig 3.1)

SG

CG

0

50

ci'0' ci'1'

ci'2' ci'3'

19

44

32

5

6

47

32

15

%

Chronic interstitial Fibrosis

Baseline 'ci' scores

117

Fig 3.2 Baseline ‘ct” scores between SG and CG

Fig 3.2 shows the distribution of the severity of Chronic tubular atrophy - “ct” scores as defined by BANFF 2007 between the Sirolimus Group –SG (blue) and Control Group - CG (red)

At baseline, the chronic tubular atrophy scores “ct” were different between the

groups with CG having more “ct3” than the SG. (Fig 3.2)

SG

CG

0

50

100

ct'0' ct'1'

ct'2' ct'3'

12

49

39

0

3

50

32

14

%

Chronic Tubular Atrophy

Baseline 'ct' scores

118

3.3.2.2 Vascular intimal injury: “cv” scores

The “cv” scores which indicate vascular damage due to immune mediated

mechanisms were not different between the groups at baseline. (Fig 3.3)

Fig 3.3 Baseline ‘‘cv” scores between SG and CG

Fig 3.3 shows the distribution of the severity of chronic vascular intimal thickening score- “cv” scores as defined by BANFF 2007 between the Sirolimus Group –SG (blue) and Control Group- CG (red)

SG

CG

0

20

40

60

0 1

2 3

32 51

15

2

24 46

21

9

%

Vascular intimal thickening

Baseline "cv' scores

119

3.3.2 .3 Tissue injury due to chronic CNI exposure: “ah” scores

Fig 3.4 Baseline ‘ah” scores between SG and CG

Fig 3.4 shows the distribution of the severity of arteriolar hyalinosis - “ah” scores as defined by BANFF 2007 between the Sirolimus Group –SG (blue) and Control Group- CG (red)

There was no difference in the “ah” scores, which denotes chronic vascular

injury secondary to CNI exposure (Fig 3.4) nor in the glomerulosclerosis score

which denotes overall damage to the glomerular capillaries.(data not shown)

In summary, the CG group had higher proportion grade 3 scores compared with

the SG. But except for the ‘ct’ findings, the ‘ci’, ‘cg’ and ‘ah’ scores did not reach

statistical significance.

SG

CG

0

50

ah'0' ah'1'

ah'2' ah'3'

41

27

17

15

32

24 35

9

%

Arteriolar Hyalinosis

Baseline 'ah' scores

120

3.3.3 CNI dosing in the CG

In response to the biopsy finings, in the CG 50 % (17/34) of the RTRS had the

dose of CNI reduced and in 1 patient the CNI was withdrawn. The mean dose

reduction was 28 % (Range 14-50%). 3 RTRs were switched to a different CNI

(CyA ↔ TAC). In the remaining 13 patients (34%), there was no change in the

CNI use.

3.3.4 SRL dosing in the SG:

In the SG the mean SRL level was 7.2 +/- 1.9ng/ml. The mean SRL dose was

1.54 +/-0.6 mg/day.

121

3.3.5 eGFR Outcomes:

Fig 3.5 Rate of decline in eGFR

Fig 3.5 shows the change in eGFR over time between the two groups; Sirolimus Group –SG (blue) and Control Group- CG (red); X axis: Time in Years Y axis: eGFR expressed in ml/min/1.73 m

2

In the SG the eGFR remained almost stable during the duration of follow-up at

47.8 ml/min compared with 48.3 ml/min at baseline. In the CG there was a

significant decline in the eGFR from a baseline value of 40.8 ml/min to 30.1

ml/min. (Fig 3.5)

The rate of decline of eGFR was significantly higher in the CG. The eGFR

declines at a rate of 0.0402 ml/week (2.1ml/year) in the CG compared with the

0.002ml/week (0.1 ml/year) in the SG. (P=0.02)

10

20

30

40

50

60

Pre

dic

ted e

GR

F (

fixe

d)

Conversion 1 2 3 4 5 6 7Years

SRL 95%CI Control 95%CI

Fitted SRL Fitted Control

122

3.3.5 .1 Linear Mixed- Modeling for Slope of eGFR

Using linear mixed modeling, rates of decline of eGFR were compared in both

the groups. The results are presented in Table 3.2

Table 3.2 Linear mixed modelling of eGFR comparison in the two

groups

eGFR Co-ef Std.Err P>IzI 95%Confidence

Interval

1.CG -7.5 4.0 0.061 -15.4 0.3

time -0.002* 0.01 0.84 -0.02 0.02

CG# c. time 1 -0.04* 0.017 0.02* -0.07 -0.01

Constant 48.31 2.5 0.000 45.93 54.15

*Indicates Slopes in both groups ** P value for difference in slopes P≤ 0.05 is significant Table 3.2 shows the results of linear mixed modeling comparing the two groups; Abbreviations: eGFR – estimated Glomerular Filtration Rate; Co-ef – Coefficient; Std.Err – Standard

Error; Sirolimus Group –SG and Control Group- CG . See section 3.4.1.1 for explanation.

Explanation for Table 3.2

The 1st row (1.CG) indicates that at time ‘0’ (baseline) there is on average a

difference between the CG and SG of 7.5 ml/min. The negative sign indicates

that the GFR in CG is less than the SG.

The 2nd row (time) indicates that when Control=0 (SG) the rate of change of

GFR over time is 0.002ml/min/week. The negative sign indicates that the GFR

declines with time and P value of 0.84 indicates that in the SG the value is not

significantly different from the baseline.

123

The 3rd row is the interaction term and represents the difference between the

slopes between the 2 groups. This term indicates that in the CG the GFR

declines by an additional 0.04 ml/min/week compared with the SG.

3.3.5 .2 Predicted eGFR at specific Time points:

The predicted eGFR values at specific time points and percentage of decline

from baseline in the two groups is shown in Table 3.3

Table 3.3Comparison of predicted eGFR at specific time-points

SG*

ml/min/1.73m2

CG*

ml/min/1.73m2

% decline from Baseline

SG CG

Baseline 48.30 40.79 - -

1 year 48.20 38.66 0.2 5.1

2 years 48.09 36.49 0.43 10.5

3 years 47.98 34.36 0.66 15.7

4 years 47.88 32.23 0.87 21.1

5 years 47.77 30.10 1.1 26.2

*Values expressed as Mean Table 3.3 shows the predicted values of eGFR at specific time points and the percentage of decline from the baseline value between the SG and CG Abbreviations: eGFR – estimated Glomerular Filtration Rate; Sirolimus Group –SG and Control Group-

CG

124

3.3.5 .3 Predictors of improvement in eGFR post conversion:

The significant difference in the slope of the eGFR over time indicates that the

SG has higher eGFR compared with CG over time. In order to evaluate the

factors that may predict the eGFR response to conversion, baseline histological

scores and clinical features that may predict post-conversion eGFR were then

analysed in a 3 –way interaction model, similar to the model explained in Table

3.2

The results of the univariate analysis for clinical factors that may predict

response are shown in Table 3.4 The interaction terms are not shown.

Table 3.4 Univariate analysis of pre-conversion clinical features

that may predict eGFR response post SRL conversion.

eGFR** Co-ef Std. Err P>IzI 95% Confidence

Interval

Duration on CNI 0.12 0.33 0.7 -0.53 0.76

Donor age -0.2 0.12 0.09 -0.43 0.04

PCR @Conversion -.0.04 0.017 0.02* -0.08 -0.008

P≤ 0.05 is significant. *Significant Predictor in univariate analysis ** Interaction terms not shown Table 3.4 shows the results of univariate analysis of the pre-conversion clinical features that may predict post SRL conversion eGFR response Abbreviations: eGFR – estimated Glomerular Filtration Rate; Co-ef – Coefficient; Std.Err – Standard

Error; Sirolimus Group –SG and Control Group- CG

The other factors that were examined in the model and were found to be not

significant included donor sex, age at transplant and degree of HLA mis-

matches (data not shown).

125

In univariate analysis examining the role of parameters of histological injury,

only the histological ‘ct 1-3’ scores, ‘cv 2-3’ scores and cg3 scores predicted the

post conversion eGFR. ‘ah3’ scores almost reached significance

(p=0.06).Baseline ‘ci1-2’, ‘ah1-2’ or ‘gl’ scores did were not predictive of the post

conversion outcomes. (Table 3.5)

126

Table 3.5 Univariate analysis of pre-conversion histological

Features that may predict eGFR response post SRL conversion.

Table 3.5 shows the results of univariate analysis of the pre-conversion histological features that may predict post SRL conversion eGFR response *Interaction terms not shown **Denotes significant P values. P≤ 0.05 is significant Abbreviations: eGFR – estimated Glomerular Filtration Rate; Co-ef – Coefficient; Std.Err – Standard

Error; Sirolimus Group –SG and Control Group- CG ; ct- Chronic tubular atrophy; cv- chronic vascular intimal thickening; cg-chronic glomerulopathy; ah- arteriolar hyalinosis; gl- glomerulosclerosis

eGFR*

Co-ef Std. Err P>IzI 95%Confidence

Interval

ct 1 -15.2 7.1 0.03** -29.1 -1.4

ct2 -31.1 7.2 <0.001** -45.4 -17.0

ct3 -36.3 10.1 <0.01** -56.2 -16.4

cv1 -6.1 4.8 0.2 -15.4 3.3

cv2 -15.7 6.1 0.01** -27.7 -3.4

cv3 -29 9.5 0.002** -47.7 -10.2

ci1 3.3 11.7 0.8 -19.6 26.3

ci2 -10.1 15.7 0.5 -40.9 20.9

ci3 -12.9 21.1 0.5 -54.3 28.4

cg1 0.1 5.8 0.9 -11.4 11.6

cg2 -10.5 7.4 0.15 -25.0 3.9

cg3 -21.7 9.4 0.02** -40.2 -3.2

ah1 -1.0 5.5 0.8 -11.8 9.7

ah2 -1.7 5.7 0.8 -12.6 9.2

ah3 -13.1 7.0 0.06 -26.9 0.8

gl <25% 8.3 9.8 0.4 -10.9 27.6

gl 26-50% 5.9 10.2 0.6 -14.0 25.8

gl >50% -11.6 11.6 0.3 -34.3 11.0

127

3.3.5 .4 Final mult ivariate model predict ing Post -conversion

eGFR:

Multi-variate analysis was performed in a stepwise backward elimination

(manual) as described in Chapter 2. The final model that best predicts eGFR is

shown in Table 3.6.

Table 3.6 Model predicting eGFR outcome

eGFR Co-ef P>IzI 95%Confidence

Interval

1 1.CG -7.5 0.1 -16.9 1.9

2 time 0.02 0.08 -0.003 0.05

3 CG#c.time1 -0.05 0.012* -0.87 0.01

4 PCR@conv -0.072 0.396 -0.24 0.09

5 CG#c.PCR@conv1 0.06 0.516 -0.11 0.22

6 c.time# c.PCR@conv1 -0.001 0.002* -0.002 .0005

7 CGl#c.time# .PCR@conv1 0.001 0.014* 0.0002 0.0002

8 Ct1 -13.4 0.05* -26.9 0.2

9 Ct2 -29.1 <0.001* -42.9 -15.8

0 Ct3 -25.7 0.016* -46.7 -4.7

11 cons 70.7 0.000* 57.9 83.6

P≤ 0.05 is significant *Denotes significant P values. Table 3.6 shows the results of the final multi-variate analysis of the pre-conversion clinical and histological features that may predict post SRL conversion eGFR response using step-wise backwards elimination analysis Abbreviations: eGFR – estimated Glomerular Filtration Rate; Co-ef – Coefficient; Std.Err – Standard

Error; Control Group- CG ; ct- Chronic tubular atrophy; cv- chronic vascular intimal thickening; cg-chronic glomerulopathy; ah- arteriolar hyalinosis; gl- glomerulosclerosis; PCR – Protein : Creatinine ratio; cons – constant; conv- conversion

128

Table 3.6 shows a three way interaction term between, groups, time and PCR.

The higher baseline PCR values are associated with greater decline in eGFR

over time in both groups. (Row 7: 3-way interaction between group, time and

PCR at conversion; Table 3.6). Rows 8-10 show that increasing severity of

tubular damage is associated with increasing decline of eGFR.

3.3.5 .5 Different re lat ionship betw een baseline PCR and eGFR in

both groups:

The 2-way interaction term (row 6) also indicates that the relationship between

baseline PCR and decline in eGFR is different in the SG compared with the CG

(P=0.002).

For a unit increment in PCR the eGFR declines at the rate of 0.07ml/min in the

SG compared with 0.002ml/min in the CG (P=0.02) (Data not shown). This

demonstrates that baseline proteinuria has differing effects upon the eGFR

outcome in both groups and that higher baseline proteinuria is associated with

greater decline in eGFR post conversion to SRL.

129

3.3.5 .6 Graft Loss:

In the SG the actual graft loss was 6% (3/51) compared with 24% (8/34) in CG.

P= 0.02. There were no deaths in either group during the follow-up.

The median time to graft loss in the SG was 3.1 +/- 2.1 years compared with 2.4

+/- 1.5 years in the CG. (P=0.01) (Fig 3.6)

Fig 3.6 Kaplan-Meier plot of Graft loss

Fig 3.6 shows the Kaplan Meier Plot of graft loss between the two groups. SG- Green; CG- blue Abbreviations: SG- Sirolimus Group; CG- Control Group

SG

P=0.01

CG

130

3.3.5 .7 Conversion Failure:

11 out of 54 (20%) ceased SRL due to a complication. The median time to

stopping therapy was 12 months (IQR 5-38). The majority stopped therapy

because of the development of nephrotic range proteinuria.

6 /11 (55%) ceased therapy due to nephrotic range proteinuria.

2/11 due to infection

1/11 due to edema without nephrotic range proteinuria

1/11 due to Transplant Glomerulopathy (DSA)

1/11 due to sexual dysfunction

All conversion failures were assumed to have reached the end point and Intent

to Treat (ITT) analysis was not used to analyze the graft loss.

The lower rates of graft loss in the SG should be interpreted in the context of

high rates of conversion failure.

131

3.3.6 Proteinuria Outcomes:

At baseline, the median proteinuria was similar between the SG and CG (14.5

vs. 21mg/mmol). After a median follow – up of 64 months, the increase in

proteinuria was similar in both groups. (Fig 3.7)

Fig 3.7 Changes in PCR CG vs. SG

Fig 3.7 shows the change in Proteinuria over time between the two groups; Sirolimus Group –SG (red) and Control Group- CG (blue) X axis: Time in years; Y axis: Proteinuria expressed as PCR mg/mmol

0

200

400

600

Pre

dic

ted P

CR

(fixe

d)


Control 95%CI SRL 95%CI

Fitted Control Fitted SRL

132

3.3.6 .1 Graft loss censored Proteinuria

Proteinuria is a marker of allograft dysfunction and allograft injury, irrespective

of the aetiology of graft injury. In order to exclude this confounder that

heterogeneity of advanced allograft injury may mask more subtle changes of

proteinuria in those with less advanced injury, the proteinuria changes were

analysed after excluding those with graft loss in both the groups. (Fig 3.8)

Fig 3.8 Graft loss censored PCR Changes

Fig 3.8 shows the change in Proteinuria over time between the two groups after censoring for graft loss; Sirolimus Group –SG (red) and Control Group- CG (blue) X axis: Time in Years; Y axis: Proteinuria expressed as PCR mg/mmol

-500

0

500

100

0

Pre

dic

ted P

CR

(fixe

d)




P=0.003

133

Table 3.7 Linear mixed modelling of graft loss censored

proteinuria

PCR Co-ef Std.Err P>IzI 95%Confidence

Interval

1.CG 11.6 19.1 0.5 -25.9 49.1

time 1.2 0.39 0.003* 0.39 1.94

CG# c. time 1 -1.1 0.65 0.083 -2.4 0.15

Constant 36.7 11.2 0.001 14.83 58.66

* P value for difference in proteinuria measured as PCR mg/mmol between the two groups P≤ 0.05 is significant Table 3.7 shows the results of linear mixed modeling of change in proteinuria between the groups after censoring for graft loss Abbreviations: PCR – Protein: Creatinine ratio; Co-ef – Coefficient; Std.Err – Standard Error; Sirolimus

Group –SG and Control Group- CG

Table 3.7 shows that the PCR values change with time and in the SG the PCR

increases by 1.2 mg/mmol/ week (P=0.003), compared with 0.1mg/mmol/week

in the CG. (The linear mixed modeling Table 3.7 is interpreted in the same way

as Table 3.2)

134

3.3.6 .2 Proteinuria in SG

Not only there was a significant increase in proteinuria following conversion to

SRL, 11% (6/54) developed nephrotic range proteinuria leading to cessation of

SRL therapy. Patients in the SG were further analysed to find out whether a

specific level of proteinuria at the time of conversion predicted the development

of significant proteinuria (defined as a PCR of>100mg/mmol) after conversion to

SRL. The numbers were too small to generate a ROC analysis, hence requiring

a different statistical approach. A PCR of 50mg/mmol which corresponds to

approximately to 0.5 g of proteinuria/day, was defined as a clinically acceptable

or safe level of proteinuria and used to divide the SG into two groups, based on

the proteinuria at the time of conversion. (Fig 3.9).

o Those with normal PCR at conversion(PCR<50mg/mmol)

o Those with elevated PCR at conversion (PCR>50mg/mmol)

135

Fig 3.9 Comparison of Baseline with post-conversion PCR

Fig 3.9 shows the change in Proteinuria over time between the two SG; Blue: PCR> 50mg/mmol at the time of conversion Green: PCR ≤ 50mg/mmol at the time of conversion X axis: Time in years; Y axis: Proteinuria expressed as PCR mg/mmol; Abbreviations: PCR – Protein: Creatinine ratio

RTRs with the higher baseline PCR (>50mg/mmol creatinine) had a statistically

significant increase in proteinuria compared with those RTRs who had

proteinuria (<50mg/mmol) at baseline (17 vs. 71 % P<0.0001; Fig. 3.10). The

odds of having a PCR greater than100mg/mmol post SRL conversion are 11.5

times (OR) higher than if the PCR at baseline is ≥50mg/mmol (P=0.015).

3.3.6 .3 Predictors of Post Conversion PCR:

The changes in PCR from baseline to the end of follow-up did not differ

between the two groups (Fig 3.7). Hence the linear mixed modeling that was

0

200

400

600

Pre

dic

ted S

RL

PC

R(f

ixe

d)


PCR>50 95%CI PCR<=50 95%CI

Fitted PCR>50 Fitted PCR<=50

P<0.0001

136

used to predict eGFR changes could not be used to predict the PCR changes

post conversion. However, sub –group analysis was performed in the SG to

analyse the baseline histological and clinical features of those who developed

significant proteinuria post conversion, compared with those who did not. The

results are summarised in Table 3.8

3.3.6 .4 Baseline proteinuria predicts post conversion Proteinuria

Table 3.8 Baseline PCR correlates with post-conversion PCR

PCR at end-of follow-up (mg/mmol)

PCR

at

Conversion

(mg/mmol)

<50 51-100 >100

<50 66 17 17

51-100 40 0 60

>100 0 0 100

Table 3.8 shows the correlation between proteinuria at the time of conversion and post conversion proteinuria. Values are expressed as percentages of RTRs who had a PCR <50, 51-100, >100 at the time of conversion and post-conversion to SRL

Table 3.8 shows 17% of those with a PCR of <50mg/mmol, 60% of those with

50-100mg/mmol and 100% of those with a baseline PCR of 100mg/mmol

developed significant proteinuria after conversion to SRL.(P=0.03). Therefore

increasing levels of baseline proteinuria correlates with increased risk of post-

conversion proteinuria. A cut-off of 50mg/mmol appears to be a clinically useful

measure to guide an acceptable clinical decision point for conversion.

137

3.3.6 .5 Durat ion on CNI and post conversion proteinuria

The median time to conversion to SRL was 6.8 years (IQR 4.5 - 7.1) in those

who developed significant proteinuria post conversion compared with 2.6 years

(IQR 1.3- 8.7) in those who did not. Although this did not reach statistical

significance and could be due to the small sample size it suggests that later

conversions with an increased risk of chronic tubular injury due to CNI exposure

may be relevant and requires further exploration.

3.3.6 .6 Histological Injury Scores and post conversion

Proteinuria

Figures 3.11 to 3.14 show the baseline histological changes in those who

developed significant proteinuria and those who did not develop significant

proteinuria post SRL conversion. There is no difference in the histological

changes between the groups.

138

Fig 3.10 “ci” Changes at baseline

Fig 3.12 “ct” Changes at baseline

▀ Group 1: Significant Proteinuria post conversion

▀ Group2: Proteinuria <100mg/mmol post-conversion

Fig 3.10 -3.13 show the comparison of the histological changes between the groups who developed proteinuria after conversion with those who did not.

Fig 3.11 “cv” Changes at baseline

Fig 3.13 “ah” Changes at baseline

0

20

40

60

ci0 ci1 ci2

ci3

11

56

33

0

24 36 36

4

chronic interstitial fibrosis

Baseline "ci" scores : Gp 1 Vs.Gp 2

0

50

ct0 ct1 ct2

ct3

12 44 44

0

16

44 40

4

Axi

s Ti

tle

Baseline "ct" scores: Gp 1 vs.Gp 2

0

100

cv0 cv1 cv2 cv3

22 67

11 0

40 40 16 4 A

xis

Titl

e

Chronic Vascular Intimal Changes

Baseline "cv" scores : Gp 1 Vs.Gp 2

0

50

ah0 ah1 ah2 ah3

27 27 19 27

38 38 14 10

Axi

s Ti

tle

Arteriolar Hyalinosis

Baseline 'ah" scores: Gp 1 vs. Gp 2

P=0.1

139

3.3.7 Blood Pressure outcomes:

Systolic and diastolic blood pressure was similar in both groups and did not vary

during the follow-up. (Fig 3.14)

Fig 3.14 Comparison of Systolic Blood Pressures in both groups

Fig 3.14 shows the change in systolic blood pressure over time between the two groups; Sirolimus Group –SG (red) and Control Group- CG (blue) X axis: Time in years; Y axis: Diastolic BP expressed in mm of Mercury;

The mean systolic BP was 129 +/- 16 mmHg in the SG compared with 129 +/-

18 in the CG.

140

Fig 3.15 Comparison of Diastolic Blood pressure in both groups

Fig 3.15 shows the change in diastolic blood pressure over time between the two groups; Sirolimus Group –SG (red) and Control Group- CG (blue) X axis: Time in years; Y axis: Diastolic BP expressed in mm of Mercury;

The mean diastolic BP was 75 +/- 8 mmHg in the SG compared with 77 +/- 10

in the CG. (Fig 3.15)

3.3.7 .1 Use of anti-hypertensive agents:

In the SG the number of anti-hypertensive medications before conversion was

2.4 +/-1.4 compared with 2.3 +/- 1.5 in the CG. Post conversion these values

were 2.3 +/- 1.3 and 2.6 +/- 1.7; i.e. no change within or in between groups.

70

75

80

85

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iasto

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141

3.4 Discussion

3.4.1 eGFR outcomes:

This study demonstrates that in RTRs with CAN, conversion to SRL from a CNI

is associated with a significantly lower rate of decline in eGFR, in fact the eGFR

after a median of 5 years follow up was nearly identical to the baseline.

However in the group who did not receive SRL but continued or reduced the

CNI there was a continued loss of eGFR such that at the end of follow up, they

had lost an eGFR of 10ml/min. which equates to a 26% loss of eGFR from

baseline. (41 ml/min at the time of biopsy to 30ml/min).The absolute graft loss

was also statistically higher in the CG than the SG.

This difference in rate of decline in eGFR between the groups could be

attributed either to the beneficial effects of SRL upon the allograft or due to the

effects of CNI withdrawal or a combination of both. Pontrelli et al examined the

histological changes in renal allograft biopsies before and after SRL conversion

and reported that conversion to SRL decreases the progression of interstitial

fibrosis compared with continuation on a CNI (Pontrelli, Rossini et al. 2008).

The anti-proliferative properties of SRL could be a possible mechanism for

regression in the fibrosis scores. It is possible that reduction in fibrosis similar to

that in Pontrelli, occurred in the SG and /or fibrosis progressed in the CG, which

resulted in improved eGFR in the SG compared with the CG. Follow-up

examination of renal histology may have been informative but was not available

in the two groups studied here. Ruiz et.al compared implantation biopsies and

protocol biopsies at 1 year and showed that RTRs on SRL had less ‘ci’ and ‘ct’

scores than those maintained on a CNI. (Ruiz, Campistol et al. 2002). However

142

Servais et.al demonstrated that SRL conversion, though associated with

improvement in eGFR is not associated with regression of interstitial fibrosis.

(Servais, Toupance et al. 2009). Flechner et.al have shown that continuing CNI

either in the same of reduced dose is associated with persistent histological

damage compared with CNI withdrawal.(Flechner, Kobashigawa et al. 2008).

From the available literature it is unclear if the difference in the chronic

histological damage scores is due to the adverse effects of CNI continuation or

if SRL causes improvement in the histology scores. The current study does not

answer this question, but the multivariate model suggests that being on SRL is

a strong and independent predictor of lower rate of decline of eGFR. This could

be explored in further studies.

The other strong predictor of the difference in eGFR outcomes between the

groups was the degree of ‘ct’ changes and the multivariate model predicted

that increasing severity of histological scores of ‘ct’ directly and independently

correlated with rate of loss of eGFR declined. The histological scores at

baseline were not significantly different in both groups, except for the chronic

tubular atrophy changes. The CG had higher proportion of ct3 compared to the

SG. (Fig 3.2) One might argue that the decline in eGFR in the CG was because

of the higher proportion of ct3 at baseline, although the distribution of grade 1

and grade 2 changes at conversion were similar in both groups. (50 vs. 49%

and 32 vs.39%. Figure3.2) The multivariate modeling takes in to account for this

variation and suggests that in addition to the ‘ct’ changes, SRL and baseline

proteinuria independently predicted the difference in outcome between the

groups.

The Banff Classification scores of ‘gl’ and ‘ah’ describe the non immune

mediated injury to the vasculature with ‘ah’ denoting exposure to CNI. These

143

scores were not different between the groups at baseline. Though changes of

arteriolar hyalinosis are associated with chronic CNI exposure, these changes

are not exclusive to CNI exposure. Strain upon the vascular endothelium due to

age related factors and hypertension could also produce similar histological

changes. In addition to arteriolar hyalinosis, CNI exposure can lead to chronic

tubular atrophy (Liptak and Ivanyi 2006). In the current study, the duration of

CNI exposure did not predict improvement in the eGFR either in uni or multi

variate analysis suggesting that neither the duration of CNI exposure nor the

histological changes of CNI toxicity, predict the eGFR outcomes post

conversion to SRL. Irrespective of the aetiology of the inciting insult chronic

tubulo-interstitial damage is associated with decline in GFR in kidney disease

in most states (Liu 2011). A similar mechanism could explain why chronic

tubular injury rather than glomerulosclerosis or arteriolar hyalinosis predicts

eGFR outcomes in the current study. This finding should also be interpreted

along with the outcomes of blood pressure, which remained stable during the

period of follow-up in both groups. ‘cg’ and ‘cv’ changes denote allograft injury

due to immune mediated processes. [In the current study both groups (CG and

SG) had similar immunological risk (degree of HLA mismatches) and the

baseline biopsy did not show any difference in these scores]. It is not surprising

that these scores did not predict the eGFR outcome.

Clinically, a lower baseline proteinuria was associated with a decreased rate of

decline in eGFR post conversion to SRL, as shown in the multi variate analysis.

It was also noted that the effect of proteinuria was different in the SG compared

with the CG. Higher baseline proteinuria was associated with decline in eGFR in

both groups. However, for a similar degree of baseline proteinuria the rate of

144

decline in eGFR was significantly higher in the SG. This association in addition

to the histological predictors suggests that conversion to an mTOR-I before

advanced tissue injury occurs may be beneficial.

Several studies have demonstrated improvement in eGFR after conversion to

SRL in renal and other solid organ transplantation (Table 1.3). The CONVERT

trial is one of the largest studies that examined 830 RTRs prospectively after

conversion to SRL from a CNI based regimen. They reported that an

eGFR>40ml/min at the time of conversion was associated with both better graft

and patient survival. The mean time to conversion from transplantation was 38

months and 90% of their study patients had a GFR of>40 ml/min at the time of

conversion. The recruitment of patients with eGFR <40ml/min was stopped

because in this group 17% reached the primary end-points of graft or patient

loss post conversion to SRL. They concluded that it was not safe to convert

patients with an eGFR <40/ml/min. In the post-hoc analysis they identified a

subset of patients with GFR ≥40ml/min and PCR <110mg/mmol who showed

improvement in eGFR at 24 months post conversion. (Schena and Pascoe

2009). Due to smaller patient numbers in the current study we did not stratify

the population according to baseline eGFR. However in the current study the

baseline proteinuria and histological features both independently correlate with

eGFR outcomes after conversion to SRL. The CONVERT trial reported only

baseline histological characteristics in their population, but did not correlate the

histological findings with the clinical outcomes post conversion. There is paucity

in the literature correlating the pre-conversion histological correlates with post

SRL conversion clinical outcomes. The current study demonstrated that

145

baseline histological features, in particular higher ‘ct’ scores predict post

conversion eGFR. This could be confirmed larger prospective randomised trials.

3.4.2 Proteinuria Outcomes:

This study demonstrated conversion to SRL is associated with increasing levels

or proteinuria and this is consistent with the published literature. (Table 1.3). In

the current study a pre-conversion proteinuria of >50 mg/mmol predicts

significant proteinuria post-conversion. This result is also consistent with other

published studies that have demonstrated that higher baseline proteinuria is a

predictor of poor outcome after conversion to SRL.(Diekmann, Budde et al.

2004) (Schena and Pascoe 2009).

In the current study, a greater proportion of patients with post-conversion

proteinuria had a longer duration of CNI exposure and also higher ah2/3 scores

(46% vs.24%; Fig 3.14). This observation was not statistically significant

perhaps due to small sample size. However this is a clinically important

question regarding the duration of exposure to a CNI, with higher histological

changes being associated with higher degrees of proteinuria post-conversion,

and certainly argues for earlier conversion from a CNI to mTOR-I to avoid this

problem. The current study was not adequately powered to fully answer this

question. The study also does not indicate whether the proteinuria secondary to

SRL is due to tubular or glomerular mechanisms and again was not designed to

explore the mechanisms of SRL induced proteinuria. In the prospective study

presented in Chapter 4 some aspects of this issue have been addressed.

146

3.4.3 Other Outcomes:

As mentioned earlier, blood pressure did not change and remained within

recommended ranges for optimal CKD disease management in both the

groups. This suggests that the improvement in eGFR was not related to

concurrent alteration in blood pressure or the use of reno-protective anti-

hypertensive agents which also did not differ between the groups before and

after conversion. The blood pressure outcomes reported in this study are

consistent with the findings in the CONVERT trial where no difference in the

systolic of diastolic BP between conversion and follow-up were noted.

The prevalence of the other side effects reported in this study such as edema,

Infections are similar to the published data. Dyslipidaemia is discussed in detail

in Chapter 4.

147

3.5 Strengths of the Study:

i. The study population reflects a real world situation where the decision to

convert to SRL after CNI exposure was based on a clinical decision

designed to improve renal function

ii. This study is the first in RTR to explore both the histological and clinical

features that may predict improvement in eGFR post conversion to an

mTOR-I. 90% of patients had a renal biopsy allowing accurate

histological coding of allograft injury.

iii. The study had a control group exposed to a CNI who were followed up

for a similar duration and had similar entry characteristics to the SRL

group.

iv. Long follow-up (median 5years)

v. The SRL dose and trough levels are consistent with current practice.

(Kasiske, B. L., B. Nashan, et al.2012). We used a standard dosing

protocol and target levels that are less than previously reported for

pivotal studies with this agent.

148

3.6 Study Limitat ions

3.6.1 Study Design

The conversion to SRL was non-randomised and unbalanced and is the major

limitation of this study.

3.6.2 Outcome measures

Follow-up renal biopsy to correlate post conversion clinical outcomes with

histological outcomes was not performed. Hence this study was unable to

demonstrate if the clinical improvement correlated with histological

improvement. Failure to distinguish between albuminuria and total proteinuria

limits patho-physiological interpretation of changes in proteinuria and site of

injury/action by SRL.


Small sample size is a major limitation of this study with reduced power to

detect smaller differences between the groups. Results and interpretation of

certain outcome measures that showed clinically significant differences but

were not statistically significant (Proteinuria, duration of CNI exposure and

histological correlates) could have been due to small sample size. (Type-II

error). ITT analysis was not used.

149

3.7 Conclusion

In conclusion, this study has demonstrated that in RTR with CAN, conversion to

SRL compared with continuing on a CNI:

Stabilises eGFR and was associated with less graft loss over a median

of 5 years follow up.

The severity of chronic tubular injury assessed by renal histology predicts

post conversion eGFR

Proteinuria of greater than 0.5g/day at the time of conversion predicts

post conversion decline in eGFR and worsening of proteinuria.

Conversion to mTOR-I even at 5 years post-transplantation is beneficial.

The combination of renal histology and the clinical parameters of

proteinuria and eGFR provide substantial information to guide clinicians

in making informed clinical decisions regarding continued CNI use or

conversion to an mTOR-I.

150

3.8 Validat ion of Study Hypothesis:

My results confirm the study hypothesis that baseline proteinuria and renal

allograft injury scores independently predict the changes in eGFR and

proteinuria after conversion to SRL.

3.9 Direct ions for Future Research

The optimal timing for SRL conversion based upon a predictive model of

histology and clinical parameters such as eGFR and proteinuria requires

prospective study. This study suggests levels of proteinuria and histology are

useful predictors and should be tested in prospective analysis.

Studies to examine histological changes post mTOR-I conversion and

correlation with clinical and immunological outcomes could be designed.

The mechanisms of mTOR-I induced proteinuria remain to be elucidated and

especially how the changes in tubular injury patterns on histology noted here

associate with proteinuria. Studies designed to elucidate the pathogenesis of

proteinuria and correlating with histological measure could be undertaken. This

will also clarify the role of mTOR-I in proteinuric states both in transplant and

non-transplant population.

Whilst this research mainly focused on the non-immune mediators of CAN,

correlation with immune mediators of CAN and post transplant HLA and non-

HLA antibodies post conversion will help us understand the full spectrum of the

effects of mTOR-I in RTR. This could be explored in future studies.

151

Chapter 4 EFFECT OF MTOR INHIBITOR

SIROLIMUS UPON GLUCOSE & LIPID

METABOLISM IN STABLE RENAL

TRANSPLANT RECIPIENTS.

152

4.1 Hypothesis and Aims:

4.1.1 Hypothesis:

In RTR, SRL has independent and potentially adverse effects upon glucose and

lipid metabolism.

4.1.2 Aim:

To assess the effects of the mTOR inhibitor SRL upon measures of glucose and

lipid metabolism in stable RTR.

4.2 Methods:

This is described in detail in Chapter 2.

In brief, 25 RTR on a CNI based immunosuppressive regimen for a median of 7

years (8 receiving TAC and 17 CyA) who satisfied the inclusion and exclusion

criteria were electively converted to SRL and followed for 12 months.

Standard oral glucose tolerance test (OGTT), fasting lipids, free fatty acids, apo-

lipoproteins A1 and B, Hs - CRP, Body Mass Index (BMI),proteinuria and eGFR

were measured before conversion and at 3 &12 months post conversion to

SRL.

153

OGTT derived i) Insulin sensitivity Index (ISI TX), ii) HOMA- IR, iii) Metabolic

Clearance rate of glucose (MCR) iv) Disposition Index (DI) were calculated at

these time points.

4.2.1 Stat ist ical Methods:

This is described in detail in Chapter 2. Descriptive statistics were summarised

using median, inter-quartile range (IQR) and categorical outcomes were

summarised using frequency distribution. For 3 way comparisons, repeated

measures of ANOVA (r-ANOVA) were used to compare the differences among

the means. If the r- ANOVA was significant, paired t-tests were performed with

Bonferroni adjustment.

4.3 Results:

4.3.1 Entry Clinical Characterist ics

Baseline clinical and histological characteristics are shown in Tables 4.1

and 4.2

24/25 completed 12 months follow-up. One patient stopped SRL and

restarted CNI, 7 months after conversion, because of an acute rejection

episode.

12 months post conversion the mean SRL dosage was 1.59 +/- 0.8

mg/day, with a SRL trough level of 6.7 +/- 2.2ng/ml (therapeutic range =

5-15 ng/ml).

154

Table 4.1 Entry Clinical characteristics of PG

Baseline Characteristics

Age in years* 45 (40,60)

Sex (M:F)** 16 : 9

Duration of CNI exposure in months* 83.4 (32,141)

Pre - conversion CNI (TAC: CyA) **

Pre - conversion MPA : AZA**

Number maintained on Prednisolone**

8: 17

18: 7

17

*Values in median (IQR); ** Values represent actual numbers;

Table 4.1 describes the baseline clinical characteristics of all the RTRs in the prospective study Abbreviations: M – Male; F- Female; CNI – Calcineurin Inhibitor; TAC – Tacrolimus; CyA- Cyclosporin A;

MPA- Mycophenolic Acid; AZA- Azathioprine

155

4.3.2 Entry Histological Characterist ics:

21/25 patients had a renal biopsy prior to conversion. The majority of the

histological changes of allograft injury were coded as mild (grade 1). (Table 4.2)

Table 4.2 Entry Histological Characteristics

Grade 0 Grade1 Grade 2 Grade3

ci * 21 63 16 0

ct * 21 74 5 0

ah * 40 25 25 10

gl * 30 45 15 10

*Values expressed in% Table 4.2 describes the severity of the histological changes at the time of conversion to SRL; Histological changes are based upon Banff 2007 classification Abbreviations: ci- chronic interstitial fibrosis; ct – chronic tubular atrophy; ah- arteriolar hyalinosis; gl-

glomerulosclerosis;

156

4.3.3 Concomitant use of other immunosuppressants:

There was a significant reduction in the dose of the use of the ant-proliferative

agents (AZA & MPA) over the duration of the study however the use of steroids

did not differ significantly. The results are presented in Table 4.3

Table 4.3: Concomitant use of other immunosuppressants

Drug Dose Pre conversion Post-conversion P- Value

MPA* mg 1472+/-469 1208 +/-404 0.03

AZA* mg 68 +/- 19 39 +/- 20 0.005

Prednisolone*mg 5.9 +/- 2.9 4.3 +/-3 0.2

*Values in mg expressed as mean +/- SD; P ≤ 0.05 is significant Table 4.3 shows the prevalent use of other steroids and MPA/AZA before and at 1 year after conversion to SRL Abbreviations: MPA – Mycophenolic Acid; AZA- Azathioprine

157

4.3.4 Use of Antihypertensive agents:

Table 4.4: Use of anti-hypertensive agents and Prednisolone

before and after SRL conversion

Number of RTRS on medications Baseline

(At conversion)

N=25

12 months

(Post-conversion)

n=24

P value

No Anti-hypertensive medications * 3 4 1.0

ACE-I* 12 9 0.3

ARB* 14 18 0.3

β Blocker* 9 5 0.3

Prednisolone*

Diuretics*

17

11

15

13

0.7

0.7

Total anti hypertensive agents** 2 (1, 3.25) 2 (1, 3) 1.0

* Values represent actual number of patients. ** Values expressed as median and IQR P≤0.05 is considered significant Table 4.3 shows the prevalent use of anti-hypertensive agents before and at 1 year after conversion to SRL Abbreviations: ACE-I – Angiotensin Converting Enzyme Inhibitors; ARB – Angiotensin Receptor

blockers;

There was no significant difference in the number or type of anti hypertensive

agents used at baseline and at the completion of the study

158

4.3.5 Use of stat in:

21/25 RTR were maintained on a statin at the time of conversion.

The type and dose of statin used varied depending upon clinician discretion.

3/21 RTR who received statin therapy had their dose increased after conversion

to SRL and one had a fibrate added to statin therapy.

4.3.6 Renal Funct ion (eGFR):

The mean eGFR at the time of conversion was 49.2 +/- 3.8 ml/min. At 3 months

post conversion there was a significant improvement in the eGFR to 55.2 +/- 4.2

ml/min and the effects were sustained at 12 months (53.4 +/- 4.2 ml/min).

4.3.7 Proteinuria

There was a progressive increase in proteinuria measured both as PCR and

ACR. The PCR and ACR increased from 18.7 and 6.9mg/mmol from baseline to

56.7 and 45.2 mg/mmol respectively at 12months post conversion. (Fig 4.1)

159

Fig 4.1 Proteinuria Change post SRL conversion

Fig 4.1 shows the change in protein: Creatinine ratio (blue) and Albumin: Creatinine ratio (red) From baseline and at 3 and 12 months following conversion to SRL X axis: specific time points (Bas: At conversion; 3 and 12 months after conversion to SRL) Y Axis: PCR/ACR measured in mg/mmol Abbreviations: ACR - Albumin: Creatinine ratio; PCR - Protein: Creatinine ratio; Bas – Baseline; 3mon - 3

months post conversion; 12mon- 12 months post conversion

The increase in PCR/ ACR is statistically significant, however the increase is

not considered clinically significant because these levels of proteinuria remain

at low levels. In the cross-sectional study presented in chapter 3, the SG were

divided in two groups based on the baseline PCR of ≤ 50mg/mmol and a

baseline PCR >50mg/mmol was associated with a clinically significant post

conversion PCR. In the current study 1/25 had a baseline proteinuria >

50mg/mmol and at 12months 4 patients, (including the one patient with a PCR >

50 mg/mmol at baseline) had developed a clinically significant proteinuria

(previously defined as PCR >100mg/mmol).

ACR formed 38% of the total PCR at baseline and this value increased to 41%

at 3 months and 80% at 12 months. (ANOVA p-value 0.04). This denotes that

albuminuria increased at a higher proportion than the non-albumin proteinuria.

0

10

20

30

40

50

60

Bas 3mon 12mon

18.1

36.2

56.7

6.9

26.6

45.2

PCR

ACR

P<0.001

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4.3.8 Effect of SRL conversion upon measures of

glucose metabolism:

4.3.8 .1 Fasting Glucose, Insulin, C-Peptide levels and Glycated

Haemoglobin:

In this study there was no difference in fasting glucose or insulin levels

measured at baseline when compared with those measured at 3 and 12 months

post conversion to SRL. (Table 4.5)

Table 4.5 Fasting Glucose, Insulin, C-peptide and Glycated Hb

levels post SRL conversion

Baseline 3 month 12 month ANOVA

P- Value

Referenc

e Range

Glucose (mmol/L)* 5.0+/-0.1 4.9 +/- 0.1 5.0 +/- 0.1 0.4 <5.6

Insulin mU/L* 8.7 +/- 1 9.0+/- 1.3 8.0 +/- 0.6 0.6 <12

C-Peptide nmol/L* 0.78 +/-0.7 0.72 +/-0.08 0.86+/-0.08 0.03 0.2-0.9

Glycated Hb (%)* 5.67+/- .72 5.6 +/-0.8 5.7 +/- 0.8 0.6 <6%

*Values expressed as mean ± SD P≤0.05 is significant Table 4.5 shows the change in the measures of glucose metabolism from baseline and at 3 and 12 months following conversion to SRL.

161

The mean value of C-Peptide decreased at 3 months compared with baseline

and subsequently increased at 12 months. Since the ANOVA p- value reached

statistical significance for C-peptide measurements, a 3-way, paired sample T-

test was performed. This test did not show any significant difference between

the baseline, 3 and 12 month values (Table 4.6).

Table 4.6 Changes in Fasting C-peptide levels with time

Baseline & 3 mon Baseline & 12 mon 3 & 12 mon

C-Peptide (P-value) 0.3 0.9 0.06

Table 4.6 shows the p values of the 3 way paired T-Test analysis; P ≤0.02 is significant Abbreviations: 3 & 12 mon - 3 and 12 months post conversion to SRL.

The C-peptide findings could be interpreted in two ways:

I. The changes in C-peptide levels were within the reference range and

moved in both directions hence the changes are probably not significant.

II. The small sample size of the study was not powered to detect the

changes in C-Peptide.

It is most likely these changes are not clinically significant particularly when

considered with the absence of change in other parameters of beta-cell function

and glucose and insulin disposition.

162

4.3.8 .2 Strat ificat ion based on ADA /WHO classificat ion of

disturbances in Glucose metabolism:

Based upon the ADA/ WHO classification of Diabetes no RTR was diabetic at

the time of entry and no patient developed new-onset diabetes after transplant

(NODAT) at 12 months.

However at baseline during the standard OGTT, 9/25 (36%) patients either had

a fasting glucose level between 5.6 and 6.9mmol/l or a 2 hour glucose of 7.8 -

11.0 mmol/l. which classifies them at increased risk of diabetes (American

Diabetes Association 2010). At 12 months there was a significant improvement

in these figures and only 3 of the original 9 remained at an increased risk of

diabetes (P= 0.02), while 6/9 resumed normoglycaemia. (Table 4.7) 16/25 had

normal OGTT values throughout.

Table 4.7 Improved Impaired Glucose tolerance and insulin

resistance post-conversion

Baseline 12 months P-value

IGT (ADA)* 9 3 0.02

HOMA-IR>2.5* 6 5 0.6

*Values represent actual number of patients P≤0.05 is significant Table 4.7 shows the changes in the measures of insulin resistance from baseline to 12 months following conversion to SRL. Abbreviations: IGT – Impaired Glucose Tolerance; ADA – American Diabetes Association; HOMA-IR –

Homeostasis Model assessment score for Insulin resistance

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4.3.8 .3 OGTT derived measures of Insulin resistance and

sensit ivity:

HOMA –IR: There was no significant change in the HOMA scores from baseline

compared with 3 and 12 months post conversion. 6/25 patients had HOMA-IR

scores >2.5, (classifying them as IR) at baseline and 3 months and 5 were IR at

12 months. (Table 4.7)

Disposition Index: There was no change in the DI values measured at baseline

and those measured at 3 and 12 months post conversion. This indicates that

pancreatic beta cell function remains intact and is able to adequately and

appropriately respond to the glucose load. An Increase in the DI, which means

an increase in glucose intolerance due to reduced pancreatic β- cell function,

was not seen in our study. This supports the findings that changes in C-peptide

levels observed in this study over time are not significant. (Table 4.8)

Metabolic Clearance Rate of Glucose: This measures both pancreatic β cell

function and peripheral insulin resistance. Declining MCR values represent

increasing insulin resistance. In my study, there was no change in the metabolic

clearance rate of glucose compared with baseline and at 3 and 12 months post

conversion, indicating that there was no change in the insulin resistance. (Table

4.8)

164

Insulin Sensitivity Index ISItx:

There was no change in the ISItx indices from baseline to 3 and 12 months post

transplantation. ISItx is inversely related to IR and is consistent with the other

measures of IR reported. (Table 4.8)

Table 4.8 OGTT derived indices post SRL conversion

*Values expressed as mean ± SD P≤0.05 is significant Table 4.8 shows the changes in the measures of insulin sensitivity and resistance from baseline to 3 &12 months following conversion to SRL. (Section 4.3.8.3 for explanation) Abbreviations: ISI Tx – Insulin Sensitivity Index; DI- Disposition Index; MCR – Metabolic Clearance rate

of glucose; HOMA-IR –Homeostasis Model assessment score for Insulin resistance

Baseline 3month 12 month ANOVA

P-value

ISI TX * 0.09+/0.01 0.09+/- 0.01 0.09+/- 0.01 0.6

DI* 94.8 +/- 9.2 91.9 +/- *.4 93.8+/- 9.5 0.9

MCR (ml/kg/min)* 9.2 +/- 0.4 9.0 +/- 0.4 9.3 +/- 0.4 0.6

HOMA -IR* 1.97 +/-0. 2 2.0+/- 0.3 1.83 +/- 0.2 0.3

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4.3.8 .4 BMI, Free Fatty Acid levels and Hs CRP

Table 4.9 Changes in BMI, Hs CRP & FFA post SRL conversion

*Values expressed as mean ± SD P≤0.05 is significant Table 4.9 shows the changes in BMI, FFA and the inflammatory marker Hs- CRP from baseline to 3 &12 months following conversion to SRL. (Section 4.3.8.3 for explanation) Abbreviations: BMI – Body Mass Index; FFA- Free Fatty Acid; Hs CRP- Highly Sensitive C- Reactive

Protein

There was no significant change in the BMI, or FFA between baseline and at 3

and 12 months. However the FFA levels did rise with time and the Hs CRP

showed a trend towards increasing from the baseline value. (Table 4.9) This

might suggest an effect of increased inflammation and a larger patient group

may have been informative.

Baseline 3 months 12 months ANOVA

P-Value

Reference

Range

BMI (kg/m2)* 25.2 +/- 0.9 25.4 +/- 0.7 25.7 +/- 0.8 0.12 20-25

FFA (mmol/l)* 0.21+/- .02 0.24 +/- 0.03 0.27 +/- 0.03 0.2 0.1-0.6

Hs CRP* 3.8 +/- 1 5.4 +/- 1.3 6.8 +/- 1.6 0.07 -

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4.3.8 .5 Effect of SRL conversion upon lipid and lipoproteins:

There was a significant increase in the Total Cholesterol, Triglycerides, LDL-

Cholesterol and Apolipoprotein B levels evident at 3 and maintained at 12

months post conversion compared with baseline. There was no change in HDL-

cholesterol or Apolipoprotein A1 levels at 3 or 12 months after conversion

compared with baseline. The calculated non-HDL levels increased significantly

and Apo-A1 / Apo-B ratio decreased significantly, indicating that the changes in

the lipids after conversion are due to an increase in Apo-B containing non-HDL

lipid fractions. (Table 4.10)

Table 4.10 Changes in Lipids and Lipoproteins post SRL

Conversion

Baseline* 3months* 12 months * ANOVA

P-Value**

Reference

Range

TC (mmol/l)* 4.4+/- 0.2 5.0+/- 0.2 5.1+/-0.2 0.03 <5.5

LDL (mmol/l)* 2.2 +/- 0.2 2.6 +/- 0.2 2.9 +/- 0.2 0.003 <3.0

Apo-B (g/l)* 0.78+/-0.05 0.92 +/-0.05 0.92+/-0.05 <0.0001 <1

TGL(mmol/l)© 1.42 +/-0.2 1.95 +/-0.3 2.02 +/-0.3 0.008 <1.7

HDL (mmol/l)* 1.45 +/- 0.1 1.58 +/- 0.2 1.36 +/- 0.1 0.06 >1.0

Apo-A1 (g/l)* 1.53+/- 0.08 1.58 +/- 0.1 1.59 +/- 0.1 0.4 >1.15

Non-HDL Cholesterol* 2.9+/-0.2 3.4 +/- 0.2 3.7 +/-0.2 0.008 -

Apo A1/Apo B ratio* 2.1 +/-0.2 1.8 +/-0.2 1.8 +/- 0.1 <0.0001 -

*Values Expressed as Mean +/- SD; © Logarithmic Transformation ** P<0.05 is significant Table 4.10 shows the changes in Lipid sub fractions and lipo proteins from baseline to 3 &12 months following conversion to SRL. (Section 4.3.8.5 for explanation) Abbreviations: TC- Total Cholesterol; LDL – Low Density Lipoprotein; Apo-B- Apo-lipoprotein –B TGL-

Triglyceride; HDL- High density Lipoprotein; Apo-A1- Apo-lipoprotein A1;

167

4.3.8 .6 Changes in Lipids w ith t ime

Table 4.11 Significance of the difference among baseline, 3 and

12 month lipid and lipoprotein values

Base & 3 months Base & 12 months 3 &12 months

TC mmol/L 0.02 0.002* 0.8

LDL mmol/L 0.04 0.001* 0.6

Apo B g/L <0.001* 0.001* 1.0

TGL mmol/L 0.006* 0.007* 0.5

Non-HDL mmol/L 0.007* 0.03 0.2

Apo A1: Apo B <0.0001* 0.001* 0.7

P < 0.02 is statistically significant (Bonferroni Correction for 3-way analysis) *Denotes significant P- values. Table 4.11 shows the Bonferroni correction for the parameters with significant P-value in ANOVA showed in Table 4.10. (Section 4.3.8.6 for explanation) Abbreviations: TC- Total Cholesterol; LDL – Low Density Lipoprotein; Apo-B- Apo-lipoprotein –B TGL-

Triglyceride; HDL- High density Lipoprotein; Apo-A1- Apo-lipoprotein A1;

The changes in the lipid profile were evident by 3 months post conversion and

remained stable by 12 months. (Table 4.11)

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4.4 Discussion:

4.4.1 eGFR

This study demonstrated that eGFR improved after conversion to SRL. The

improvement in eGFR was seen at 3 months and was sustained at 12 months.

This finding is consistent with other published studies such as CONVERT which

suggest if the eGFR at the time of conversion is >40ml/min there is an

improvement in eGFR post conversion.(Schena and Pascoe 2009). The results

of the retrospective study presented in Chapter 3 show that the eGFR stabilised

rather than improved following conversion. The results of the current

prospective study could be interpreted as an initial improvement in eGFR

following CNI withdrawal. In this study the duration of follow-up was 12 months.

Longer follow-up would help clarify whether the eGFR improvement is sustained

in this population. The current study population also had low PCR and “ct”

scores both of which were predictors of good outcome in the retrospective

study. This could be another possible explanation for the improved eGFR seen

in this cohort.

4.4.2 Proteinuria vs. a lbuminuria .

Following conversion to SRL, there was an increase in proteinuria (PCR and

ACR) with 4/25 patients (16%) of the patients developing significant proteinuria

at 12 months post conversion. The absolute values of both PCR and the ACR

increased and the albuminuria component of increased significantly compared

with the non-albumin proteinuria. There could be several explanations for this

differential change in the composition of urinary protein. The non-selective

169

nature of the proteinuria and increased in albuminuria could suggest either a

glomerular mechanism or altered tubular handling of protein reabsorption or

both. This could be an effect of the CNI withdrawal leading to arteriolar vaso-

dilatation and increased glomerular filtration pressure leading to proteinuria. If

this was only a CNI withdrawal effect one might expect an early increase and

then a stabilisation of proteinuria with time. The ACR changes were still

increasing at 12 months, suggesting that in addition to the effect of CNI

withdrawal other factors might influence these changes. These findings are

consistent with other published studies and as explained in section 1.6.3, SRL

induced proteinuria could be a result glomerular injury either due to podocyte

damage, increased VEGF expression or due to loss of nephrin expression.

Apart from suggesting that proteinuria following SRL conversion is non-selective

and may involve glomerular or tubular mechanisms, defining the mechanism of

proteinuria and correlating this to histological scores could be explored in future

studies.

170

4.4.3 Effect of SRL conversion upon Glucose and

Insulin metabolism:

The results of this study did not demonstrate that conversion from a CNI to SRL

had a significant adverse effect upon glucose metabolism. There was no

significant change in measures of insulin resistance, insulin secretion or

clearance. In fact conversion to SRL seemed beneficial. No patient developed

new onset diabetes and the majority of those with IGT at baseline showed

improvement. The concurrent use of other medications which may also

influence glucose metabolism (corticosteroids, beta-blockers, angiotensin

converting enzyme inhibitors or Angiotensin II receptor blockers) did not differ

between conversion and 12 months post conversion. None of the patients were

on oral hypoglycaemic agents. Overall, these results demonstrate that

cessation of CNI and SRL conversion did not have a significant impact upon

measures of glucose metabolism in RTRs and thus rejects the study hypothesis

that SRL conversion has adverse effects on glucose metabolism in RTRs.

Studies in RTRs examining the effects of SRL upon glucose metabolism have

demonstrated the variable effects of mTOR –I (Table 1.4). Most of these studies

were retrospective and measures of glucose metabolism or NODAT were not

the primary end-points and the limitations of these studies have been described

in detail in 1.4.6

In my study there was no change in glucose homeostasis following CNI

withdrawal and conversion to SRL. Both CNI inhibitors CyA and TAC decrease

insulin sensitivity and increase insulin resistance, although TAC has the more

171

potent effect upon glucose and insulin metabolism. There is evidence that

reducing or stopping these agents may improve glucose homeostasis.

Therefore, if SRL did not have any adverse impact on glucose homeostasis it is

possible there may be improvement in the measures of glucose sensitivity and

insulin resistance due to the CNI withdrawal. However this study demonstrates

that the effect of stopping CNI and immediately starting SRL did not adversely

affect the measures of glucose metabolism. A possible explanation is that SRL

has an effect similar to that of CNI on glucose homeostasis, at least in the

doses reported here. But this study was not designed to examine that

hypothesis which would require randomisation to these agents.

The only study to prospectively examine the impact of CNI withdrawal and

conversion to SRL upon glucose metabolism in RTRs was published by

Teutonico et.al in 2005. (Teutonico, Schena et al. 2005).They followed 26 RTRs

with biopsy proven CAN for 6 months after conversion to SRL from CyA a

median of 38 months after transplantation. They studied another 16 RTRs who

were treated with low dose TAC and SRL combination and studied the effect of

TAC withdrawal. In their study, 2 patients in each group developed PTDM as

defined by ADA criteria. In addition there was a decrease in the ISItx, MCR and

DI after conversion to SRL. They concluded that SRL increased peripheral

insulin resistance and impaired pancreatic beta cell response to glucose, which

resulted in deterioration in glucose homeostasis. (Teutonico, Schena et al.

2005) Compared with the study by Teutonico, where 4 people with IGT

developed NODAT, in my study 67% (6/9) with IGT, normalized after

conversion to SRL and none developed NODAT. There are several reasons

why the study results of Teutonico et al differ from those reported in this thesis.

172

1) The mean dose of SRL was much higher in the Teutonico study (3.8mg/day

vs. 1.6 mg/day) which led to significantly higher achieved trough levels (11.4

ng/dl vs.6.72 ng/dl).

2) Teutonico included more patients with impaired fasting glucose and IGT

(44% and 32 %) at entry compared with 28% and 8% respectively in this study.

The present cohort comprised RTRs with a reduced risk of developing diabetes

and glucose intolerance because we designed the study to exclude existing

diabetes at the time of conversion, although patients with IGT were not

excluded.

3) Teutonico et al may have included RTRs with more severe reduction in renal

function (Creatinine clearance 37ml/min) at conversion than was recorded in

this cohort (eGFR 50ml/min), although due to differing measures of reporting

kidney function (Cr Cl vs. eGFR) the magnitude of this difference is uncertain.

4) Conversion to mTOR-I occurred earlier in their study, at a median of 38 vs.

84 months. It is possible that the late conversion of this study, selected a cohort

of patients who had stable renal function and had inherently lesser risk for

developing diabetes.

5) The biopsy findings or proteinuria outcomes were not mentioned by

Teutonico. It is possible that their cohort consisted of patients with higher

histological grades of CAN and higher degrees of proteinuria in addition to the

reduced Creatinine Clearance.

6) Because reduced GFR and proteinuria are each independently associated

with insulin resistance this may also have contributed to the differing outcome

and conclusion. In RTRs, similar to the general population, IR is associated with

elevated FFA levels. (Armstrong 2005).Following mTOR-I conversion there was

a significant increase in both serum TGL and FFA in the Teutonico study in

173

contrast to this study where conversion to SRL was not associated with a

significant rise in FFA, suggesting that IR was more significant in the Teutonico

patients.

4.4.4 Effect of SRL conversion upon Lipid Metabolism :

Mixed Dyslipidaemia (hyper-cholesterolaemia and hyper-triglyceridaemia) are

adverse effects of SRL therapy (Kasiske 2008) and the severity of this is dose-

dependent.(Blum 2000). Early studies of SRL used much higher target levels of

SRL(15-30ng/ml) than in current use and were associated with often severe

hypercholesterolaemia and triglyceridaemia (Groth 1999), which was cited as

one of the major adverse effects of SRL therapy leading to cessation of the

drug.

The results reported in this thesis are consistent with these previous studies

confirming that SRL induces a mixed pattern of dyslipidaemia. The severity of

these changes may have be attenuated by targeting lower therapeutic levels

(<15ngml). In this study, SRL increased TGL, TC, LDL, non-HDL and Apo B

whilst HDL-cholesterol, Apo A1 and FFA levels did not significantly differ. The

Apo A1: Apo B ratio decreased significantly. These results are consistent with

the study hypothesis, that SRL has significant adverse effect upon lipid

metabolism in RTRs. A rise in Apo B containing lipids measured as an increase

in Total, LDL and non-HDL cholesterol, and the decrease in the ApoA1/Apo B

ratio are potentially atherogenic, and would normally be considered to increase

a patient’s cardiovascular risk. Indeed these changes occurred when the

majority of RTRs were already receiving a lipid modifying agent in recognition of

174

their heightened CVD risk. These changes are therefore potentially adverse and

would warrant additional therapeutic intervention in order to modify CVD risk.

4.4.4 .1 Mechanisms of SRL induced dyslipidaemia:

The pathogenesis of SRL induced dyslipidaemia is not fully elucidated and

studies in RTRs exploring the pathogenesis of SRL induced dyslipidaemias are

limited. Morrisett et.al prospectively examined 6 RTRs who were maintained on

10mg/day of SRL and found that plasma cholesterol levels increased by 50%,

TGL by 90%, Apo B by 28% and plasma FFA by 42.3% after 6 weeks of

treatment. They did not study insulin metabolism but speculated that increase in

TGL and VLDL could be due to an increase in hepatic synthesis of TGL with

increased secretion of VLDL. They concluded that SRL alters the insulin

signaling pathway to increase the plasma adipose tissue lipase activity and

decrease lipoprotein lipase activity, resulting in a mixed dyslipidaemia and an

increase in the FFA pool. (Morrisett, Abdel-Fattah et al. 2002; Morrisett, Abdel-

Fattah et al. 2003) .

The current study has demonstrated that SRL increased TC, LDL, non- HDL

and Apo-B levels without changing the HDL-cholesterol or Apo-A1

concentrations. In contrast to the studies by Morrisett et.al, there was a rise in

TGL without a change in measures of IR or a clear expansion of the plasma

FFA pool (although there was a trend towards an increase in FFA it did not

reach significance). This suggests that the rise in TGL may be caused by

mechanism(s) independent of insulin production or disposition.

175

There are several reasons why the more extreme changes in lipid measures

described by Morrisett et.al were not identified in the present study. These

include the very high dose or SRL (10mg/day) compared with only 1.6mg/day in

this study. In addition, a longer follow-up (12 months vs 6 weeks) and the high

prevalence of statin use in the current patient group are likely important. It is

known that SRL induced dyslipidaemia responds to statins and attenuates with

time (Kasiske 2008). In my study the rise in TC is best explained by an increase

in the non-HDL-cholesterol fractions (including measured LDL-cholesterol as

noted here) and an increase in Apo B particles. This could be due to either an

increase in production or a decreased clearance of Apo B containing lipids.

Hoogeveen et.al performed metabolic studies in 5 RTRs who received high

dose SRL (10mg/day). They performed a kinetic turn over study that showed

that an increase in VLDL-apoB100 concentrations was due to a significant

reduction in the fractional catabolic rate of VLDL- apoB100, rather than an

enhanced VLDL-apoB100 synthesis. They concluded that SRL induced

dyslipidaemia was due to the reduced catabolism of Apo-B containing

lipoproteins. (Hoogeveen, Ballantyne et al.) The findings of this thesis are

consistent with Hoogeveen et.al, that SRL increases Apo-B containing lipids.

Animal studies have demonstrated that chronic SRL treatment causes IR and

hyperlipidaemia by up-regulating the hepatic gluconeogenesis and impaired

lipid deposition in adipose tissue.(Houde, Brule et al. 2010).This effect is

mediated through the mTORC1/S6K1 pathway (Pathway 3 Fig 1.10) Using cell

cultures, Ma et.al have demonstrated that SRL decreases the LDLr expression

by hepatocytes and this could be a possible explanation of SRL induced

hypercholesterolaemia. (Ma, Ruan et al. 2007) LDL comprises 90% of Apo B

176

containing lipids and is metabolized via the LDLr expressed by the hepatocytes.

The current study confirmed a rise in Apo-B containing lipids post conversion to

SRL. Only Apo B100 and not 48 binds to the LDLr. So if SRL induces

hypercholesterolaemia by reduction of LDLr, Apo B100 should be selectively

increased. However, Apo B fractions were not measured in this study and

hence this mechanism could not be specifically tested.

Chakrabarti et.al, using a mouse model have shown that i) mTOR stimulation

promotes fat storage by suppressing lipolysis and promoting lipogenesis and ii)

mTOR inhibition by SRL promotes lipolysis and suggested this as a potential

mechanism of SRL induced hypertriglyceridaemia. In their study they used very

high doses of SRL (5mg/kg). (Chakrabarti, English et al. 2010). In my study

there was no significant evidence of enhanced lipolysis as measured by

expansion of the FFA pool following conversion to SRL, although there was a

small trend in this direction. Smaller patient numbers and the low levels of SRL

achieved in this study are possible explanations.

The other mechanism which could explain hypertriglyceridaemia without

involving insulin pathways, would be direct reduction in lipoprotein lipase activity

(LPL) or hepatic lipase activity (HPL) caused by SRL. However previous studies

have demonstrated that SRL treatment did not alter LPL or HPL levels.

(Hoogeveen, Ballantyne et al.). In this study we did not measure LPL or HPL so

cannot test this potential mechanism.

The increase in TGL may be due to the increase in VLDL secondary to the

decreased catabolism of Apo-B containing lipids. The increase in non-HDL

cholesterol in the current study suggests that this mechanism is possible and

177

this requires further exploration by direct measurements of lipid sub-fractions or

most accurately lipid turnover studies.

4.4.5 Cardio-vascular risk profile follow ing conversion

to SRL

The changes in the lipid profile following conversion to SRL points towards an

increased CV risk. RTRs have a 10-fold increased risk of cardiac deaths

compared with the general population. (Liefeldt and Budde 2010). Hence the

changes in the lipid fractions should be interpreted in the context of the patients

cardio-vascular risk profile. PTDM is associated with increased major coronary

artery events (MACE).(Lentine, Brennan et al. 2005) Holme et.al demonstrated

non-HDL cholesterol is associated with increased incidence of MACE in RTRs.

(Holme, Fellstrom et al. 2010) The other non-traditional risk factors that predict

MACE in RTR include graft dysfunction, graft loss albuminuria, non-albumin

proteinuria and inflammatory markers. (Jardine, Fellstram et al. 2005) (Lentine,

Brennan et al. 2005),.(Halimi, Matthias et al. 2007; Prasad, Bandukwala et al.

2009)

The current study has demonstrated that SRL increases non- HDL cholesterol,

HsCRP, albuminuria and non-albumin proteinuria and decreases the ApoA1 / B

ratio, which are known cardiac risk factors. This study has also demonstrated

that SRL improves eGFR and does not interfere with glucose and insulin

homeostasis. This latter effect of improved eGFR could possibly mitigate to

some extent the CV risk profile and offset the adverse effects of increased

dyslipidaemia and proteinuria upon MACE. Although the current study was not

178

designed to examine the cardiovascular disease risk, nevertheless these factors

remain important considerations for clinical implications of a choice to switch

from a CNI to an mTOR-I. Further this study did not examine other markers of

inflammation such as IL-6 and TNF α and markers of endothelial dysfunction

and hence assessing cardio-vascular risk profile post SRL conversion based

exclusively on the current study results is not possible. This could be explored

in future studies.

4.5 Strengths of the study

1) This study is the first in RTR to prospectively explore the effects of mTOR

inhibitors upon glucose and insulin metabolism and their relationship to the

derangements in lipid metabolism.

2) The study population represent a real world clinical group where the decision

to convert to SRL is based on a clinical indication to improve renal function and

improve allograft survival

3) The SRL dose and trough levels are consistent with current

recommendations and practice. (Kasiske, B. L., B. Nashan, et al.2012).

We used a standard dosing protocol and target levels that are less than

previously reported for pivotal studies with this agent.

179

4.6 Limitat ions of this Study:

4.6.1 Study Design:

The conversion to SRL was non-randomised and is a major limitation of this

study. The clinical decision to convert to SRL could have been influenced by the

clinicians pre-existing bias and only those patients with better graft function

were converted to SRL and this could have impacted upon the outcomes. The

majority of the patients were on a statin therapy and there was no control group.

4.6.2 Outcome measures:

Though the original aim was into include measures of waist: hip ratio because

this measure better correlates with IR, this measurement was obtained in only

50% of the study population at differing time points and hence the results are

not reported.

Lipid and Lipoprotein sub-fractions were not measured. Measuring VLDL and

also LPL/HPL would have further considered the mechanisms of lipid

derangements secondary to SRL.

Measuring Apo-B 100 and Apo B48 and Apo-C levels would have helped in

further elucidating the mechanisms lipid derangements.

180


The small sample size is a major limitation of this study and restricts power to

show smaller differences, even when they may be present. Results and

interpretation of certain outcome measure that showed clinically significant

difference but were not statistically significant (C-peptide, HsCRP) could have

been due to small sample size.

Because multiple tests have been performed in this study there is a probability

that some of the tests have shown statistical significance when no such

relationship exists (type 1 error) although where possible we have adjusted for

multiple comparisons.

4.7 Conclusion

In conclusion, this study has demonstrated that in RTRs, conversion to SRL

based on current recommended SRL therapeutic levels in patient s receiving a

statin:

Improved eGFR

Increased proteinuria measured as total protein or albumin

Did not alter insulin or glucose disposition

Did not cause NODAT

Did not worsen markers of IR.

Caused mixed dyslipidaemia, but to a lesser extent than previously

published, which might be due to lower dose of SRL or concomitant

statin use or both

181

Dyslipidaemia secondary to SRL

o was associated with an increase in Apo- B containing lipids either

due to increased production or delayed catabolism

o was not associated with glucose or insulin disposition.

Impact upon CV risk profile is uncertain but potentially adverse.

Further studies are needed to clarify the mechanisms of SRL induced

dyslipidaemia, glucose and insulin metabolism and the impact of SRL

upon traditional and non-traditional cardio-vascular risk factors.

4.8 Validat ion of the study Hypothesis:

The study hypothesis that SRL has independent and potentially adverse

outcomes upon lipid metabolism in RTR is validated but the hypothesis that

SRL has adverse outcomes upon measures of glucose metabolism is rejected.

182

4.9 Direct ions for Future Research

Results of this study results have led to generating hypotheses and potential to

design future studies.

This small non-randomised study showed that SRL did not alter glucose or

insulin metabolism. A larger RCT comparing maintenance on a CNI with SRL

would be required to examine this more comprehensively.

This study has not suggested possible mechanisms by which SRL might

influence glucose homeostasis. mTOR inhibition can have varied effects upon

glucose homeostasis, depending upon the metabolic state of the individual and

chronicity of the inhibition. Future studies can be designed to identify the

characteristics of RTRs who are at higher risk of developing derangements in

glucose homeostasis following mTOR-I.

Studies examining the lipid sub-fractions; apo-lipoprotein sub-fractions and lipid

kinetics could be designed to explore the mechanisms of SRL induced

dyslipidaemia.

The mechanisms and origin of the increased proteinuria demonstrated require

additional evaluation.

Cardio-vascular risk profile of SRL needs to be explored further. This opens up

the possibility of multi-centre trials with hard cardio-vascular endpoints to

explore the association of MACE with traditional and non-traditional risk factors

in RTR.

Studies evaluating the impact of SRL upon inflammatory markers such as IL-6,

TNF α, markers of endothelial dysfunction and examining the association of

these with measures of glucose and Insulin metabolism will help us understand

the vascular risk profile of mTOR-I.

183

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Appendices

214

Appendix 1

215

Appendix 2

An evaluation of determinants of renal and metabolic functions in Renal

Transplant Recipients and the effects of conversion from Calcineurin Inhibitors

to Sirolimus

Principal Investigator: Dr. Ramyasuda Swaminathan

PATIENT INFORMATION SHEET

Dear Patient,

Your Nephrologist has decided to change your current immunosuppression

medication to a new immunosuppressive medication called Sirolimus. During

this time we will ask you to contribute to an observational study examining the

benefits and risks of changing to this drug.

Study Purpose

Based on your current condition of your kidney transplant your nephrologist has

decided to change you over from your current immunosuppressive treatment to

a drug called Sirolimus. The benefits of Sirolimus in kidney transplantation have

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been well established and your nephrologist would have explained to you the

benefits and potential side-effects related to Sirolimus.

All the immunosuppressive medications (including Steroids, Cyclosporine,

Tacrolimus and Sirolimus) can have significant effects on the glucose (sugar)

and cholesterol (fats) levels by affecting different metabolic pathways. In

addition sirolimus may affect the production and action of hormones associated

with ovarian and testicular function. The aim of this audit is to monitor if and

how your glucose, cholesterol and certain hormone levels change after you

have been converted to Sirolimus from your previous medication.

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Will your treatment be affected?

Participation in this audit will not change your treatment in any way. The

decision to convert you to Sirolimus and continue the treatment will be

determined by your nephrologist. Participation in this audit will in no way

influence the decision-making process.

What information is needed from you?

We would need to measure your height, weight and blood pressure, and waist

and hip circumferences at the time of conversion and at approximately three

and twelve months after conversion to Sirolimus. At the same time you would

need to have blood and urine tests. Most of these tests and physical

examination are already part of your routine post transplant care and will be

done during your routine visit to your nephrologist. The main difference will be

that you are requested to do an oral glucose tolerance test on three occasions

over a 12 month period (i.e at the time of change over to Sirolimus, three and

twelve months after change-over). This test determines your risk of diabetes

and measures your glucose and insulin levels when fasting and at 1 and 2

hours after ingestion of a sugar solution. This extra test means that you will

need to provide three additional sets of blood samples (10ml or approx 2 tsp)

over and above what you would normally expect to provide. At the same time

we would also measure the hormones and cholesterol (fats) in your blood. We

would ask you to fill in a simple Questionnaire, which enquires about the

common side effects of Sirolimus and changes in health after the changeover of

medication.

How will the information collected be used?

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The information collected during this audit will be kept confidential. The data will

be analysed by the Principal Investigator (PI) and used in a thesis titled “An

evaluation of determinants of renal and metabolic functions in Renal Transplant

Recipients and the effects of conversion from Calcineurin Inhibitors to

Sirolimus” which will be submitted to the University of Western Australia. The

results may also be published in a medical journal as intended, but no reader

will be able to identify the individual patients.

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Further information

If you require any further information you can contact the Principal Investigator

through Royal Perth Hospital on 08 9224 2244 during normal business hours.

This audit has been approved by the Royal Perth Hospital Ethics Committee.

For questions relating to Ethical approval you can contact the Chairman of the

Ethics committee through Royal Perth Hospital on 08 9224 2244 during normal

business hours.

Thank you for agreeing to participate in this study.

CONSENT TO PARTICIPATION IN THE AUDIT

I,........................................................................ agree to participate in the above

study. I have read and understood the attached Information Sheet and I have

retained a copy of the signed document. I have been given the opportunity to

ask questions about the study by the investigator. I give consent for my medical

records being accessed by the Principal Investigator.

Signed................................................………………......................................

Date...........................

Signature of Investigator/Coordinator.............................................................

Date...........................

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Appendix 3

Abstracts:

1. R. Swaminathan & A. Irish “Outcomes of conversion to Sirolimus from

CNI in renal transplant recipients with Allograft dysfunction due to CNI

toxicity &/or Chronic Allograft Nephropathy” Tumour & Cell Biology,

March 2007

2. R. Swaminathan & A. Irish “Factors predicting renal outcomes after

conversion to Sirolimus from CNI in renal transplant recipients with

allograft dysfunction due to Calcineurin inhibitor toxicity and/ or Chronic

allograft nephropathy” JASN October 2007 (Abstracts)

3. R. Swaminathan & A. Irish “Outcomes of conversion from CNI based

therapy to sirolimus in renal transplant recipients with allograft

dysfunction due to calcineurin inhibitor toxicity and/ or Chronic allograft

nephropathy” JASN October 2007 (Abstracts)

4. R. Swaminathan & A. Irish “Renal outcomes and factor predicting the

outcomes after conversion to Sirolimus form calcineurin inhibitors in

chronic allograft dysfunction” – ATC Boston, June 2009

5. R. Swaminathan & A. Irish “Effect Of M-Tor Inhibitors Upon Glucose &

Lipid Metabolism In Renal Transplant Recipients” TSANZ Canberra,

2010

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