the role of genetics and immune mechanisms in the

i

The Role of Genetics and Immune Mechanisms in the

Pathogenesis of Diabetic Retinopathy

A THESIS SUBMITTED TO

UNIVERSITY OF HEALTH SCIENCES IN PARTIAL FULLFILMENT OF THE REQUIREMENT FOR THE DEGREE

OF DOCTOR OF PHILOSOPHY

IN IMMUNOLOGY

By

Dr NADEEM AFZAL (M.B.B.S) MSc MEDICAL IMMUNOLOGY (UK)

Supervised by

Prof. Dr. A. H. NAGI M.B.B.S., Ph.D., FCPS., FRCP., FRCPath., FCPP

Head of Pathology Department, University of Health Sciences

Co-supervisor Prof Dr Ghazala Jaffery

MBBS, PhD Immunology Head, Department of Pathology

Services Institute of Medical Sciences Lahore

UNIVERSITY OF HEALTH SCIENCES

LAHORE, PAKISTAN

ii

CERTIFICATE

It is hereby certified that thesis is based on the results of experiments carried out by Dr.

Nadeem Afzal and that it has not been previously presented for PhD degree. Dr. Nadeem

Afzal has done this research work under our supervision. He has fulfilled all the

requirements and is qualified to submit the accompanying thesis for the degree of PhD in

the subject of Immunology.

Supervisor Professor Dr. A. H. Nagi M.B.B.S., Ph.D., FCPS., FRCP., FRCPath., FCPP Head, Department of Pathology University of Health Sciences, Lahore Pakistan Dated: -------------------------

iii

DEDICATED TO

My late sister, my family and respectable teachers for their continuous support and

assistance.

iv

ACKNOWLEDGEMENTS

All praises and thanks are for Allah Almighty, The Lord of the worlds, The All Merciful

All Compassionate, Who gave me the strength to complete this study. May Peace and

Blessing of Allah Almighty be upon Last Prophet Muhammad, the mercy for all

mankind.

I gratefully acknowledge the invaluable guidance, sympathetic attitude, moral support,

inspiring comments and strong motivation of my supervisor Prof. Dr. Abdul Hanan

Nagi, Department of Histopatholoy, University of Health Sciences, Lahore, whose

insight made me understand the important and essential aspects of my research.

Doing this research project on diabetes was an exciting experience. This would have been

impossible without the help and guidance of all working in Department of

Immunology. I am particularly indebted to my learned supervisor Professor Dr. A. H.

Nagi for always encouraging my efforts during this work and for providing insightful

feedback during all the stages of the research described in this thesis. His vision was

fundamental in shaping my research and I am very grateful for having had the

opportunity to learn from him.

I am always extremely grateful to (Late) Prof. Mahmood Ahmed Chaudary, Chairman

Board of Governors, University of Health Sciences Lahore, Prof. Dr. Malik Hussain

Mubashar, Ex-Vice Chancellor, University of Health Sciences Lahore and Prof I. A.

Naveed, Acting Vice Chancellor, University of Health Sciences Lahore for providing the

opportunities in the University to pursue research excellence.

I cannot fully express my gratitude to Col. Javaid Iqbal, and Dr Ahsan Ullah, Director

Administration, University of Health Sciences Lahore, for their untiring commitments,

passion for work and extraordinary dedication. Their efforts have created congenial

environment in the University.

v

I am extremely grateful to Prof Shakeela Zaman Head Department of Preventive

Medicine, Children Hospital and Institute of Child Health Lahore for her valuable time,

expertise, and patience in guiding and analyzing the data. I am also thankful to Prof Dr

Asim Mumtaz, Head Department of Allied Health Sciences, Dr Saqib Mehmood,

Department of Human Genetics and all my colleagues at UHS for their continuous

support and encouragement. My special gratitude to Dr Abu Zafar; in-charge Amin

Hayat Memoral Center Samanabad Lahore and the staff of this center to obtain samples

from diabetic patients. My heart filled appreciation for all the subjects who donated their

blood and without their assistance this study would not have been possible.

I would like to thank Dr. (Maj) Tipu, Pathologist (Immunologist), Combined Military

Hospital Chunia for his valuable contribution, in the form of time and expertise during

analyzing the data of flowcytometer.

These acknowledgements would be incomplete without mentioning the names of my

colleagues; Ms Afia Abbas, and Khursheed Javeed working in the Department of

Immunology for their valuable contribution in this research project.

vi

List of Abbreviations

ELISA Enzyme linked immunosorbant assay

IL Interleukin

Treg T regulatory cell

nTreg Natural T regulatory cell

Tr1 Type 1 regulatory T cells

HbA1c Glycosylated hemoglobin

WHO World Health Organization

T2DM Type-2 diabetes mellitus

IGT Impaired glucose tolerance

CRP C-reactive protein

BMI Body mass index

IDF International diabetic federation

IR Insulin resistance

PDR Proliferative diabetic retinopathy

DR Diabetic retinopathy

LTA Lymphotoxin-A

eNOS endothelial nitric oxide synthase

ITGA2 Integrin alpha-2

ACE Angiotensin converting enzyme

VEGF Vascular endothelial growth factor

ICAM Intracellular adhesion molecule-1

ADBR3 β3-adrenergic receptor gene

CD Cluster differentiation

EDN1 Endothelin-1

EPO Erythropoietin

ESRD End stage renal disease

HFE Haemochromatosis

SLE Systemic lupus erythmatosus

RA Rheumatoid arthritis

vii

HLA Human leucocyte antigen

GP Glycoprotein

TNF-α Tumor necrosis factor-alpha

Ig Immunoglobulin

IgM Immunoglobulin-M

IgG Immunoglobulin-G

Th cells T-helper cells

TCR T cell receptor

CDR Complementarity determining region

TGF-β Tumor growth factor-beta

GITR Glucocorticoid induced tumor receptor

CTLA-4 Cytotoxic T-lymphocyte Antigen 4

CXCR3 chemokine receptor-3

IPEX Immune dysregulation, polyendocrinopathy,

enteropathy, X-linked syndrome

GITR Glucocorticoid induced tumor necrosis factor

Receptor

PD-L1 Programmed cell death-ligand 1

SDF-1α Stromal cell derived factor-1 alpha

MCP Monocyte chemoattractant protein

ENA Epithelial neutrophils activator

IP Interferon-induced protein

MIP Macrophage inflammatory protein

VCAM Vascular cell adhesion molecule

SS Sjogren syndrome

CEPI Corneal epithelial cell line

AGEs Advanced glycation end products

VH Vitreous hemorrhage

AqH Aqueous humor

EIU Endotoxin-induced uveitis

RPE Retinal pigment epithelium

viii

PVR Proliferative vitreoretinopathy

EAU Experimental autoimmune uveitis

Th-17 cells T-helper 17 cells

NKT Natural killer T cells

iNKT Invariant natural killer T cells

GM-CSF Granulocyte monocyte colony stimulating factor

MCP-1 Monocyte chemotactic protein 1

CIA Collagen induced arthritis

EAE Experimental induced encephalomyelitis

IRBP Intra-retinal binding protein

UA Ursolic acid

IBD Inflammatory bowel diseases

CD Crohn’s disease

UC Ulcerative colitis

ESCC Oesophageal squamous cell carcinoma

ANCA Anti-neutrophil cytoplasmic antibody

AAV ANCA-associated vasculitis

FALS Forward angle light scatter-side scatter

SSC Side scatter

BD Becton Dickinson

MoA Monoclonal Antibodies

FITC Fluorescein isothiocyanate

PE Phycoerythrin

PerCP Peridinin-chlorophyll-protein

COPD Chronic obstructed pulmonary disease

°C Degree Centigrade

µ Micron

ANOVA Analysis of Variance

CI Confidence Interval Fig Figure

IQR Interquartile Range

ix

mg Milligram

SPSS Statistical Package for Social Sciences

Std. Error (S.E) Standard Error

WHO World Health Organization

HTM Human trabecular meshwork

PCR Polymerase chain reaction

RFLP Restriction fragment length polymorphism

HbA1c Glycosylated hemoglobin

x

List of Appendices ----------------------------------------------------134

Appendix A ----------------------------------------------------------------------------------134

Consent form

Appendix B --------------------------------------------------------------------------------------------------------------------------135

Patient history sheet

xi

List of Figures

1. Calibration and fluorescence signal compensation using CellQuest Pro software (BD)

and Calibrite Beads ----------------------------------------------------------------------------50

2. Electronic adjustment and fluorescence signal compensation of cytometer using

CellQuest Pro software.-----------------------------------------------------------------------51

3. FALS-SSC two parameter dot-plot showing the circumscribed gate (R1) containing

lymphocytes --------------------------------------------------------------------------------------52

4. CD45-SSC two parameter dot-plot showing the circumscribed acquisition gate (R2)

containing lymphocytes. ---------------------------------------------------------------------52

5. CD4-CD25 two parameter dot-plot showing that CD4+CD25+ T cell population is not

discernable from CD4+CD25- T cells. -----------------------------------------------------53

6. Determination of criteria for cells to be CD25 positive. ---------------------------------54

7. Determination of criteria for CD4 negative and CD4 positive cells. -------------------55

8. Histograms showing gating strategy using isotype control and statistics of

histogram ---------------------------------------------------------------------------------------56

9. Histograms showing gating strategy using isotype control and statistics of Histogram

----------------------------------------------------------------------------------------------------57


----------------------------------------------------------------------------------------------------58


----------------------------------------------------------------------------------------------------59


----------------------------------------------------------------------------------------------------60

xii


----------------------------------------------------------------------------------------------------61


----------------------------------------------------------------------------------------------------62

15. IL-6 ELISA Standard Curve Report --------------------------------------------------------67

16. IL-17 ELISA Standard Curve Report -------------------------------------------------------68

17. Bgl-II polymorphism of different subjects -------------------------------------------------75




xiii

List of Tables

1. Sequences of primers for the amplification of loci -------------------------------------45

2. Different standards and their concentrations used for the determination of IL-6 and

IL-17 cytokines in ELISA technique -----------------------------------------------------66

3. Demographic data of the subjects ---------------------------------------------------------71

4. Comparisons of different variables in different groups --------------------------------73

5. Frequency of Bgl-II Polymorphism in Group-I, Group-II and Group-III by PCR ----

--------------------------------------------------------------------------------------------------80

6. Comparison of variables (Cytokines) in different groups ------------------------------82

7. Comparison of CD4CD25 T cells and Treg cells (by Flow cytometer) among different groups ------------------------------------------------------------------------------84

8. Logistic Regression Model for Group-II and Group-III---------------------------------86

9. Logistic Regression Model for Group-I and Group-III---------------------------------89

xiv

CONTENTS

Acknowledgements ----------------------------------------------------------------------------iv

List of abbreviations --------------------------------------------------------------------------------------------------------------vi

List of appendices ------------------------------------------------------------------------------x

List of figures ------------------------------------------------------------------------------------xi

List of tables -----------------------------------------------------------------------------------xiii

Abstract ------------------------------------------------------------------------------------------xix

Introduction and Literature Review----------------------------------------------------1

1.1. Diabetes mellitus -------------------------------------------------------------------------------1

1.2. Type-2 diabetes mellitus-----------------------------------------------------------------------1

1.3. Ethnicity and predisposition to diabetes -----------------------------------------------2

1.4. Diabetes and pregnancy -----------------------------------------------------------------------3

1.5. Factors contributing to development of diabetes ------------------------------------------3

1.6. Inflammatory markers -------------------------------------------------------------------------3

1.7. Immunological abnormalities ----------------------------------------------------------------4

1.8. Complications of diabetes---------------------------------------------------------------------4

1.9. Diabetic retinopathy ----------------------------------------------------------------------------5

1.10. Factors contributing to diabetic retinopathy -----------------------------------------------6

1.10.1. Duration of diabetes ------------------------------------------------------------------------6

1.10.2. Platelets --------------------------------------------------------------------------------------6

1.11. Diagnosis of diabetic retinopathy -----------------------------------------------------------7

1.12. Genetic Basis of Diabetic Retinopathy ----------------------------------------------------7

1.12.1. Candidate genes -----------------------------------------------------------------------------8

1.12.1.1. Endothelin-1 (EDN1) --------------------------------------------------------------------8

1.12.1.2. Leptin --------------------------------------------------------------------------------------8

1.12.1.3. Erythropoietin ----------------------------------------------------------------------------8

1.12.1.4. Hemochromatosis (HFE) gene ---------------------------------------------------------9

xv

1.12.1.5. Prolactin ---------------------------------------------------------------------------------9

1.12.1.6. α2β1 gene -------------------------------------------------------------------------------10

1.12.1.7. Association of Bgl II polymorphism with diabetic retinopathy ------------------11

1.13. Changing concept of type 2 diabetes mellitus ------------------------------------------12

1.14. Diabetic retinopathy and autoimmunity -------------------------------------------------13

1.15. Gender bias in autoimmunity -------------------------------------------------------------14

1.16. T regulatory cells (Tregs) ------------------------------------------------------------------16

1.16.1. Treg and autoimmunity ------------------------------------------------------------------16

1.16.2. Types of Treg cells -----------------------------------------------------------------------16

1.16.3. Murine CD4+ T cells ---------------------------------------------------------------------17

1.16.4. Regulation of Treg cells -----------------------------------------------------------------17

1.16.5. Foxp3 ---------------------------------------------------------------------------------------18

1.16.6. Surface markers for Treg cells ----------------------------------------------------------19

1.16.7. Role of co-stimulatory molecules -------------------------------------------------------19

1.17. Cytokines ------------------------------------------------------------------------------------20

1.17.1. IL-6 -----------------------------------------------------------------------------------------20

1.17.1.1. Production and action of IL-6 --------------------------------------------------------20

1.17.1.2. IL-6 and Eye ----------------------------------------------------------------------------21

1.17.1.3. IL-6 and diabetic retinopathy ---------------------------------------------------------21

1.17.1.4. IL-6 in the eye and in the serum ------------------------------------------------------22

1.17.1.5. IL-6 disturbs immune privilege site --------------------------------------------------23

1.17.1.6. Anti-IL-6 as treatment modality ------------------------------------------------------24

1.17.1.7. Role of IL-23 ----------------------------------------------------------------------------24

1.17.1.8. IL-6 and Treg cells ---------------------------------------------------------------------25

1.17.1.9. IL-6 and Th17 cells ---------------------------------------------------------------------26

1.17.2. IL-17 ----------------------------------------------------------------------------------------26

1.17.2.1. Role of IL-17 ----------------------------------------------------------------------------26

1.17.2.2. Pro-inflammatory cytokine ------------------------------------------------------------27

1.17.2.3. Th1 vs Th17 -----------------------------------------------------------------------------27

1.17.2.4. IL-17 in human diseases and in animal models ------------------------------------28

1.17.2.5. Concepts about IL-17 formation ------------------------------------------------------29

xvi

1.17.2.6. Role of IL-6 in IL-17 production -----------------------------------------------------29

1.17.2.7. IL-27 --------------------------------------------------------------------------------------30

1.17.2.8. IL-23 --------------------------------------------------------------------------------------31

1.17.2.9. IL-21 --------------------------------------------------------------------------------------31

1.17.2.10. Plasticity of Th17 ----------------------------------------------------------------------32

1.17.2.11. Difference of IL-17 in humans and animals ---------------------------------------33

1.17.2.12. γδ T cells and Th17 -------------------------------------------------------------------33

1.17.2.13. Invariant natural killer T cells -------------------------------------------------------34

1.17.2.14. IL-17 and diseases --------------------------------------------------------------------34

1.17.2.15. IL-17 and type-1 diabetes ------------------------------------------------------------35

1.17.2.16. Prognostic value of IL-17 ------------------------------------------------------------36

1.17.2.17. IL-17 Foxp3 Treg cells ---------------------------------------------------------------37

1.17.2.18. Variation in the therapeutic effect of targeting IL-17 ----------------------------37

1.17.2.19. IL-17 and other cytokines manipulation -------------------------------------------38

1.17.2.20. Protective side of IL-17 --------------------------------------------------------------38

2. Hypothesis ------------------------------------------------------------------------------------40

3. Aims and Objectives --------------------------------------------------------------------40

4. Material and Methods ----------------------------------------------------------------41

4.1. Study design -----------------------------------------------------------------------------------41

4.2. Setting ------------------------------------------------------------------------------------------41

4.3. Duration ----------------------------------------------------------------------------------------41

4.4. Sample size ------------------------------------------------------------------------------------41

4.5. Sample size ------------------------------------------------------------------------------------41

4.6. Sampling technique ---------------------------------------------------------------------------41

4.7. Sample selection ------------------------------------------------------------------------------41

4.7.1. Inclusion criteria ----------------------------------------------------------------------------41

4.7.2. Exclusion criteria ---------------------------------------------------------------------------42

4.8. Genotyping of Bgl II Polymorphism -------------------------------------------------------42

xvii

4.9. Analysis of cytokines ------------------------------------------------------------------------42

4.10. Analysis of T regulatory cells -------------------------------------------------------------42

4.11. Blood Sample collection -------------------------------------------------------------------43

4.12. DNA extraction------------------------------------------------------------------------------43

4.12.1. Protocol -------------------------------------------------------------------------------------43

4.12.2. dNTPs ---------------------------------------------------------------------------------------44

4.12.3. TE buffer -----------------------------------------------------------------------------------44

4.12.4. Primers --------------------------------------------------------------------------------------44

4.13. Electrophoresis ------------------------------------------------------------------------------45

4.14. DNA Recipe ---------------------------------------------------------------------------------45

4.15. Polymerase Chain Reaction (PCR) -------------------------------------------------------45

4.16. Restriction Fragment Length Polymorphism (RFLP) ----------------------------------45

4.17. Cytokine determination ---------------------------------------------------------------------46

4.17.1. Kit contents --------------------------------------------------------------------------------46

4.17.2. Reconstitution and Reagents Preparation ----------------------------------------------46

4.17.3. ELISA protocol ----------------------------------------------------------------------------47

4.17.4. Calculation of results ---------------------------------------------------------------------48

4.17.5. Cross reactivity ----------------------------------------------------------------------------48

4.18. Flowcytometry -------------------------------------------------------------------------------48

4.18.1. Immunostaining procedure --------------------------------------------------------------48

4.18.2. Flowcytometry / Immunophenotyping -------------------------------------------------49

4.19. Data Acquisition -----------------------------------------------------------------------------51

4.20. Sample analysis ------------------------------------------------------------------------------53

4.21. Markers used for Immunophenotyping ---------------------------------------------------63

4.22. Gating strategy to identify CD4dimCD25bright T cells -----------------------------------63

4.23. Reagent preparation ------------------------------------------------------------------------64

4.23.1. DNA Extraction ---------------------------------------------------------------------------64

4.23.1.1. Reagents Required ----------------------------------------------------------------------64

4.23.1.2. dNTPs -----------------------------------------------------------------------------------64

4.23.1.3. Preparation of working solution of dNTPs ------------------------------------------64

4.23.1.4. TE buffer ---------------------------------------------------------------------------------65

xviii

4.23.1.5. Preparation of Master Mix for primers ----------------------------------------------65

4.24. ELISA IL-6 and IL-17 ----------------------------------------------------------------------66

4.24.1. Statistical Analysis of IL-6 --------------------------------------------------------------67

4.24.2. Statistical Analysis of IL-17 -------------------------------------------------------------68

4.25. Data Analysis --------------------------------------------------------------------------------69

5. Results -----------------------------------------------------------------------------------------70

5.1. Demographic data of the subjects ----------------------------------------------------------70

5.2. Different continuous variables --------------------------------------------------------------72

5.3. Comparisons of different variables among the groups -----------------------------------72

5.4. Frequency of BglII Polymorphism in Group-I, Group-II and Group-III by PCR/RFLP

---------------------------------------------------------------------------------------------------------74

5.5. Cytokines Assessment -----------------------------------------------------------------------81

5.6. Data of Assessment of Cells by Flow cytometer -----------------------------------------83

5.7. Logistic Regression Model for Group-II and Group-III ---------------------------------85

5.8. Logistic Regression Model for Group-I and Group-III ----------------------------------87

6. Discussion ------------------------------------------------------------------------------------89

7. Conclusion ----------------------------------------------------------------------------------106

8. Suggestions ---------------------------------------------------------------------------------107

9. References ----------------------------------------------------------------------------------108

10. List of Appendices ---------------------------------------------------------------------136

Appendix A --------------------------------------------------------------------------------------136

Consent form

Appendix B --------------------------------------------------------------------------------------137

Data form

xix

ABSTRACT

Diabetes mellitus affects millions of people worldwide especially in Asia, Africa and

South America. It can cause many serious complications such as retinopathy and

nephropathy. Diabetic retinopathy is a terrible prospect to these patients which is

diagnosed with the onset of microaneurysms, haemorrhages and development of cotton

wool spots in the retina.

Mechanisms underlying pathogenesis of diabetic retinopathy are not completely

understood. Integrin α2β1 is a receptor for collagen on platelet cell membrane.

Polymorphism in intron 7 of integrin gene produces change in α subunit and this makes

retina vulnerable for platelet attachment during chronic hyperglycaemia in diabetes.

Earlier studies have established a relationship between variants of α2β1 gene and diabetic

retinopathy in Japanese and Caucassions. Derangements of several cytokines and

chemokines have been reported in diabetic retinopathy.

There are many studies that evaluate the role of IL-6 in the development of ophthalmic

complications but they determined the level of IL-6 in the vitreous fluid and majority of

them have emphasized the involvement of this cytokine in the development of eye

complications. Interleukin 6 increases vascular permeability and neovascularisation and

attracts macrophages. A study was performed in Type-I diabetes mellitus to determine its

role in diabetic retinopathy whereas some of them have correlated IL-6 with proliferative

diabetic retinopathy. In the literature there are a few studies that tried to determine the

level of IL-6 in the serum of diabetic retinopathy patients but some of them could not

determine its level in the serum while others found its level much less than in the vitreous

fluid.

The comparatively newly diagnosed subset of T cells known as Th17 cell secretes IL-17

which is a family of six cytokines (IL-17A-E). It is a pro-inflammatory cytokine and

mediates inflammation by attracting neutrophils. It has been documented that Th17 cells

have major contribution in different human diseases that are related to inflammation and

tissue destruction such as rheumatoid arthritis, psoriasis, Crohn’s disease, and multiple

sclerosis. Therefore it has also been suggested that IL-17 has got the potential to be used

as a treatment option as well.

xx

It has been suggested that some early aspects of pathogenesis of diabetic retinopathy

could be due to loss of self-tolerance. At the beginning of retinopathy, anti-pericyte and

anti-endothelial cell auto-antibodies have been detected in the circulation of diabetic

patients. There were increased vitreous concentrations of IL-6 and IL-8 in the patients of

diabetic retinopathy while in the serum there were elevated levels of IL-8, TNF-alpha,

and soluble IL-2 receptor. T regulatory (Treg) cells: a subset of CD4+ T cells, down

regulates the process of autoimmunity. It has been documented that Treg cells are

involved in the development of various autoimmune disorders.

Two hundred and twelve (212) subjects were divided into three groups i.e. (Group-III)

diabetic patients with retinopathy (152), (Group-II) diabetic patients without retinopathy

(30) and (Group-I) healthy control without diabetes (30). Blood was drawn after their

consent and integrin gene polymorphism was studied by restriction fragment length

polymorphism analysis. Concentration of IL-6 and IL-17 was determined by ELISA

technique. CD4+CD25+ (T regulatory cells) were enumerated by flow cytometer.

There were 77 males and 135 females and their age distribution was from 20 years to 75

years. 109 patients had history of diabetes between 5 and 10 years whereas 73 patients

had diabetes for more than 10 years. The percentage of HbA1c was between 5.5% and

15.4%. The mean age of the studied population was 34.66, 49.46, and 50.88 years in

Group-I, Group-II and Group-III respectively. There was statistically significant

difference of mean age among the three groups. The mean CD4+CD25+ count was 14.53,

14.68, and 16.47 in Group-I, Group-II and Group-III respectively and on comparison of

CD4+CD25+ count among the three groups, there was statistically significant difference.

The mean of Treg cells was 2.91, 3.07, and 2.88 in Group-I, Group-II and Group-III

respectively and there was no statistically significant difference of Treg cells among the

three groups,. The mean level of IL-6 was 133.98, 1341.78, and 718.66 in Group-I,

Group-II and Group-III respectively and there was statistically significant difference of

IL-6 among the three groups. The mean level of IL-17 was 718.05, 415.01, and 375.95 in

Group-I, Group-II and Group-III respectively and there was statistically significant

difference of IL-17 among the three groups. Mean duration of diabetes was 7.76 and

10.51 years in Group-II and Group-III respectively. There was statistically significant

difference of duration of diabetes between these two groups. Mean percentage of HbA1c

xxi

was 8.54% and 8.83% in Group-II and Group-III respectively and there was no

statistically significant difference in percentages of HbA1c between these two groups.

There was statistically significant difference in the gender and age of the subjects in all

parameters between Group-I and Group-II. There was statistically significant difference

in the gender, age, level of IL-6 and the level of IL-17 among the subjects (p<0.05). By

comparing Group-II and Group-III, we could find statistically significant difference in the

percentage of Treg cells, the level of IL-6 and the duration of diabetes in the studied

subjects. Regarding Bgl II polymorphism, 33 (15.6%), 104 (49.05%), and 75 (34.90%)

subjects had + +, + -, and - - phenotypes respectively. On comparing Bgl II

polymorphism among the three groups, there was no statistically significant difference.

By applying logistic regression model between Group-II and Group-III there was

statistically significant difference in the percentage of Treg cells and the level of IL-6 in

these groups. When the logistic regression model was applied between Group-I and

Group-III, significant difference was found in the age of the subjects, the level of

CD4+CD25+ cells and the level of IL-6 in these groups. Therefore, it is suggested that age

and gender of the subjects, duration of diabetes, levels of IL-6, IL-17, CD4+CD25+ cells

and the percentage of Treg cells can contribute towards the development of diabetic

retinopathy.

1

1. INTRODUCTION AND LITERATURE REVIEW

1.1. Diabetes mellitus: Diabetes mellitus is present all over the world and its increased

prevalence no doubt represents a huge burden on the health of human beings because this disease

has many and sometimes serious outcomes such as retinopathy, nephropathy, and cardiovascular

disease. Most of the times it is the hyperglycemia, which initiates diabetic complications such as

retinopathy, nephropathy and neuropathy and it sometimes leads to the development of

cardiovascular diseases. Many risk factors have been associated with diabetes and its

complications such as diet, sedentary life-style, age, obesity and genetic profile of a person

(Akramet al 2011, Cockram et al 2000, Caballero et al 2005). World Health Organization

(WHO) suggested in 1999 that diagnosis of diabetes mellitus should include determination of

blood glucose levels of both fasting and after two hours of 75g glucose load (World Health

Organization Expert Committee, 1999). There are also increased chances for the development of

macro vascular diseases in impaired glucose tolerance. It is type-2 diabetes mellitus (T2DM) that

is one of the leading causes of morbidity and mortality in all over the world. It is estimated that

this disease affects more than 170 million people every year throughout the world. It is estimated

that currently diabetes mellitus is affecting about 240 million people worldwide and this figure

may increase up to 380 million by the end of 2025. Surprisingly more than 80% of its burden is

seen in low and middle income countries (International Diabetic Federation, 2006). It is believed

that Pakistan is among the areas where diabetes is highly prevalent. It is estimated that Pakistan

has 6.9 million people affected with this disease and the estimated figure is expected to double

by the end of year 2025 and it may affect more than 11.5 million people (Qidwai et al 2010). In

the United States of America the prevalence of diabetes was 13.7% and 11.7% among men and

women of ≥ 30 years of age respectively and diabetes was suggested as the sixth leading cause of

death in the US (Danaei et al 2009).

1.2.T2DM: T2DM is relatively more common and most of the times it is present in adult

population. T2DM is now being considered as an epidemic of young, swiftly spreading globally

and therefore its serious health issues are coming up (Fagot-Campagna et al 2001). At the

moment, T2DM is affecting people of all age groups. There are reports of children of eight years

of age or even younger are having this disease (Pihoker et al 1998). There are more reports about

T2DM and impaired glucose tolerance (IGT) in the young age group and in young adults from

2

the developing world (Chan et al 2009). Dramatic rise of T2DM in all age groups is associated

with the increased prevalence of obesity which is linked to the change in dietary and lifestyle

patterns. There are reports about more and more childhood T2DM than type-1 diabetes in Japan

and Taiwan (Wei et al 2003). Similarly, in the USA, T2DM is becoming more prevalent as

compared to type-1 diabetes (Kahn et al 2000). Many studies have documented strong family

history association among the affected young people. About 45% - 80% have at least one parent

suffering from diabetes and from 74% - 100% had either first or second degree relative suffering

from T2DM (Kahnet al 2000, Silverman et al 1995). It is suggested that in 20 years time T2DM

may account for the 60% of disease load in non-communicable disease group in the developing

world (Caballero et al 2001).

1.3. Ethnicity and predisposition to diabetes: It is well documented that Asian people have

lower rates of overweight and obesity as compared to people living in the Western countries

(Chan et al 2009). In spite of the fact that Asians have lower body mass index (BMI), it has been

observed that some Asian countries have similar or even higher prevalence of diabetes mellitus

as compared to Western countries. It is suggested that the risk to developT2DM begins at the

lower level of BMI for Asians as compared to the individuals living in the European countries.

It is documented that in China, the prevalence of overweight in adult population increased from

14.6% to 21.8% (Chan et al 2009) during the year 1992 to 2002. In fact an increased trend of

childhood obesity in the Asian population puts many young individuals of these countries at a

higher risk of developing T2DM in early young age. Asian populations as a whole but especially

the people of South Asian origin are prone to abdominal obesity and they have low muscle mass

with increased insulin resistance as compared to the people living in Western countries.

Therefore, waist circumference that indicate central obesity can be used as a tool to determine

obesity that is a risk to develop T2DM, and it can be used more effectively for those individuals

who have normal values of BMI (Chan et al 2009).

Infect, it is the Asia-Pacific region which is thought to be heavily affected by epidemic of

diabetes. The risk of developing diabetes mellitus seems to be a combination of genetic factors

and change in life style. Lifestyle changes are reflected by the changes in dietary habits and lack

3

of physical activity. The reason for observing diabetes particularly in younger people can be

easily associated with obesity and in particular central obesity (Cockram et al 2000).

1.4. Diabetes and pregnancy: It has been documented by animal studies that increased level of

glucose during pregnancy may lead to glucose intolerance, impaired insulin secretion, and even

in some cases increased insulin resistance (IR) in the offspring of that pregnancy(Dyck et al

2001). In humans there are increased rates of T2DM in the offspring’s of those mothers who

developed gestational diabetes mellitus. There are also increased rates of impaired glucose

tolerance among the offspring of those mothers (Aerts et al 1988). There are reports suggesting

that both the babies of low and high birth weight are likely to develop T2DM in their later life.

1.5. Factors contributing to development of diabetes: In T2DM, there is an increased

resistance to insulin along with an inability of pancreatic beta cells to secrete enough insulin to

maintain hemostasis.There are reports about high association among insulin resistance, obesity

and physical inactivity. Many studies have documented heritability of T2DM where both genetic

and environmental factors play their roles (Kahnet al 2000, Silverman et al 1995). There are

assumptions that genetic susceptibility contribute strongly towards the development of T2DM in

different populations. It has been observed that 15% - 25% of first degree relatives of T2DM

patients may develop impaired glucose tolerance or diabetes mellitus (Pierce et al 1995).

The study performed to determine the prevalence of diabetes in eight European countries

documented that all age prevalence in the network population was lowest in Slovenia and highest

in Belgium (Fleming et al 2004). For the development of T2DM, different risk factors have been

suggested by Manzella et al (2010) which include obesity, sedentary life style, unhealthy eating

life style, family history and genetics, increasing age, high blood pressure and high cholesterol,

and history of gestational diabetes in females. In the recent past evidence has emerged linking

T2DM with systemic inflammation (Kolb et al 2005)

1.6. Inflammatory markers: It has been observed that there is an increased level of

inflammatory markers in healthy individuals who eventually develop T2DM in the later part of

their lives (Vozarova et al 2002). It suggests that the process of inflammation may start much

4

early, may be during the phase of impaired glucose tolerance which might be there much before

the diagnosis of T2DM. Individuals with high white blood cell counts and increased level of

inflammatory markers such as IL-6 and C-Reactive Protein (CRP) are expected to develop

T2DM in the next 20-years and 4-years time respectively as compared to those individuals who

do not have white blood count and inflammatory markers at the higher levels (Pradhan et al

2001).

There is increased level of inflammatory markers in healthy individuals who are likely to

develop type 2 diabetes. It suggests that inflammation is present during the period of impaired

glucose tolerance prior to the development of type 2 diabetes (Vozarova et al 2002, Pradhan et al

2001, Thorand et al 2003) (Reviewed by King et al 2008). In the current study, two of the

cytokines i.e. IL-6 and IL-17 have been selected to determine their contribution towards the

development of diabetic retinopathy.

1.7. Immunological abnormalities are associated with the complications of both type 1 and

T2DM. It is suggested that in T2DM, inflammation and activation of monocytes are crucial

factors responsible for the development of insulin resistance and they are thought to add to the

loss of insulin secretary function by islet cells (CDC 2008). There are many other factors that can

increase insulin resistance for example genetic predisposition, sedentary life style, obesity,

chronic inflammation and infection (Mooradian et al 2001). During inflammation there are

factors such as activated monocytes and high level of inflammatory cytokines, CRP, and

plasminogen activator inhibitor-1 that have been documented to contribute in the development of

insulin resistance, even without diabetes mellitus (Shoelson et al 2006). It was though that there

could be abnormalities in the innate immune system may also take part in the development of

complications in diabetes mellitus (Reviewed by King et al 2008).

1.8. Complications of diabetes: Many complications of diabetes mellitus have been suggested

that could be either macro vascular or micro vascular and that are supposed to take place due to

the process of enhanced atherogenesis (Zimmet et al 2001). It is estimated that in T2DM the

morbidity because of cardiovascular problems might be two to four times more as compared to

5

subjects without diabetes. Further a family history of diabetes also increases the chances up to

2.4 fold for the development of T2DM (Pierce et al 1995).

In the literature, several mechanisms have been proposed for the pathogenesis of diabetes that

include increased non-esterified fatty acids, increased levels of inflammatory cytokines, and

dysfunction of mitochondria contributing to insulin resistance (Kelley et al 2002). Furthermore

lipotoxicityalong with glucotoxicity and amyloid formation have also been implicated in beta-

cell dysfunction in diabetes (Stumvoll et al 2005).Various complications of diabetes include

microvascular e.g. nephropathy, neuropathy and retinopathy and macrovascular e.g.

cerebrovascular diseases, peripheral vascular diseases and cardiovascular complications (Nichols

et al 2008).

1.9. Diabetic retinopathy: Apart from many complications of diabetes mellitus, diabetic

retinopathy is also a horrifying prospect to patients (Singh et al 2004). It is expected that number

of people who are at risk to develop this particular complication of diabetes would double in the

next 30 years (Wild etal 2004). Retina is a transparent layer of neural tissue placed between

vitreous body and retinal pigment epithelium (Bito et al 1978). The unique structure of retina

gives it special physiologic constraints e.g. retinal axons are not en-sheathed by myelin, therefore

un-myelinated nerves need more energy for membrane potential (Bristow et al 2002). The

density of blood vessels that can absorb light is low, hence oxygen tension in the inner retina is

hypoxic i.e. only about 25mmHg (Wangsa-Wirawan et al 2003). The pO2 gradient of retina

decreases as it moves from outside to the inner side of retina (Pournaras et al 1995). Further,

inner retina contains a few mitochondria that have light absorbing hemebased cytochrome

proteins (Gremer et al 1998, Bentmann et al 2005). Therefore inner retina depends on glycolysis

which is a less potent way of generating ATP as compared to oxidative phosphorylation that is

present at the outer retina, where pO2 is about 80mmHg (Pournaras et al 1995, Ahmed et al

1993). In spite of low vascularity and pO2 the retina has one of the highest metabolic demands.

Therefore, increased metabolic demands and low vascular supply limit the inner retina’s ability

to cope with the metabolic stress of diabetes (Cohen et al 1965).

It is documented that in the United States, it is the diabetic retinopathy which is the leading cause

of blindness in adult population under the age of 65 years and in the developing world this

6

diabetic retinopathy is the major reason for the vision loss (Kempen et al 2004). It is claimed that

diabetes might affect more than 300 million subjects worldwide by the year 2025, and it is

estimated that about 10% might probably develop visual impairment which will be secondary to

this diabetic retinopathy (WHO Fact sheet 2002).

Diabetic retinopathy and especially proliferative diabetic retinopathy (PDR) is an important

reason for adult blindness, and this condition is characterized by the development of

neovascularization. These new vessels which are formed are actually fragile and these vessels

also lack normal barrier function, therefore these vessels allow extra vascular leakage of different

components of blood. Since diabetic retinopathy is one of the serious complications and the

precise mechanisms involved in the aetiopathogenesis of PDR/DR are not known (Funatsu et al

2005). Therefore it is necessary to develop better means for identification, prevention and

treatment of diabetic retinopathy before the onset of vision loss (Singh R et al 2004).

1.10. Factors contributing to diabetic retinopathy

1.10.1. Duration of diabetes: Several experimental and epidemiological studies have indicated

that it is the duration of diabetes and the level of glucose that can be blamed as major

contributors for the development of diabetic complications such as retinopathy or nephropathy

(Diercks et al 2002). If the state of hyperglycemia is there for a longer duration of time, then

there could be alterations in the retinal or in the renal blood flow. There could be metabolic

changes, or even hemostatic abnormality (Monster et al 2002, Konen et al 1993), and there could

have been no enzymatic glycosylation of long-lived tissue proteins. All these changes are labeled

as vascular dysfunctions seen in the microcirculation and are supposed to play a major role in the

development of diabetic retinopathy and nephropathy (Tong et al 2008). The complication of

diabetic retinopathy has been suggested among individuals having diabetes at young age and

after 5 to 10 year of their disease duration (Krakoff et al 2003, Reviewed by Singh et al 2004).

1.10.2. Platelets have been documented and are said to be responsible in the development of

diabetic complications such as retinopathy and nephropathy. It is suggested that in diabetic

patients hyper reactive platelets might interact with the damaged vessels and especially to the

exposed sub endothelium and it is the area that causes enhanced micro thrombus formation or

7

occlusion of small vessels (Powell et al 1964, Glustina et al 1998, Barnett et al 1984). It might

become the reason for the change in the blood flow of retinal or renal tissues. Further there are

reasons to believe in the favourable effects of anti-platelet treatment in patients suffering from

retinopathy and nephropathy as it points towards the contribution of platelets in the pathogenesis

of microangiopathy (Matsubara et al 2000).

1.11. Diagnosis of diabetic retinopathy: Clinically, the condition of diabetic retinopathy can be

diagnosed at the development of micro aneurysms, hemorrhages and development of cotton wool

spots. It is characterized by amplified vascular permeability, abnormalities in the hemostatic

conditions, more tissue ischemia and neo-angiogenesis. It has been suggested that functional

defects often presents much earlier than the actual defects are observed in one of the above

mentioned categories. It was further suggested that this is the time when better results can be

achieved in treating the patients while there are no symptoms of visual impairment to the patients

(The New Eng. J Med 1993).

1.12. Genetic Basis of Diabetic Retinopathy

Although role of chronic hyperglycemia is well established in the pathogenesis of diabetic

retinopathy, but genetic aspects also contribute in determining susceptibility toward retinopathy

(Frank et al 2004). Genetics along with environmental elements and intra-uterine signals for low

birth weight and gestational diabetes are thought to be the major reasons for the high prevalence

of type-2 diabetes in Pakistan. Better understanding of various contributing factors in the

pathogenesis DR have suggested that prevention of the disease should infect begin much before

the start of the disease process (Hakeem et al 2010). It is well known that genetic susceptibility

contributes in the development of type 2 diabetes mellitus in certain populations (Dedousis et al

2007). Familial aggregation is a useful marker in determining genetic susceptibility to diabetic

retinopathy. The risk of developing severe diabetic retinopathy increases in the siblings of

affected individuals (Leslie et al 1982). It has also been found that frequency of diabetic

retinopathy varies with ethnicity and race. Therefore, so far several genes have been studied to

determine the association with diabetic retinopathy but only a few of them have been found to be

associated (Warpeha et al 2003).

8

1.12.1. Candidate genes: Different researchers have investigated a number of genes and they

have suggested association of more than 30 genes in various metabolic and functional pathways

in the development of diabetic retinopathy. But there are only a couple of them that have

revealed reliable associations with the development of diabetic retinopathy or with the severity

of DR. Aldosereductase (AR2) gene polymorphism at the (CA)n micro satellite marker (the 5’

end) has been repeatedly associated with DR (Warpeha et al 2003). Some other genes that have

been studied for an association includes endothelial nitric oxide synthase, lymphotoxin-a,

integrin alpha-2, angiotensin converting enzyme, vascular endothelial growth factor, intracellular

adhesion molecule 1/CD45, β3-adrenergic receptor gene and endothelin-1. (Li et al 2008) There

is a strong correlation of diabetic retinopathy with aldose receptor, advanced glycation end

products receptor, vascular endothelial growth factor, intercellular adhesion molecule 1, beta3

adrenergic receptor gene, hemochromatosis, and alpha2 beta1 integrin (Uhlmann et al 2006).

1.12.1.1. Endothelin-1 (EDN1): Polymorphism of EDN1 gene (Lys198Asn) has been suspected

to be associated with DM because this gene is often correlated with hypertension which is

considered to be one of the risk factors fordiabetic retinopathy (Rabineau et al 2003). There was

significantly higher frequency of EDN1 Asn/Asn genotype in controls as compared to the DR

patients. (Li et al 2008). Uhlmann et al (2006) concluded that further studies are required for the

analysis of these genes in order to have better understanding of path physiology of diabetes

(Uhlmann et al 2006).

1.12.1.2. Leptin is considered to be associated with obese (ob) gene expression which is present

on chromosome 17 and it is involved in the regulation of different metabolisms and body weight

(Pelleymounter et al 1995). Leptin gene has been associated with many states such as diabetes,

glucose metabolism and insulin metabolism. Polymorphism of leptin gene (C2549 A) has been

associated in Chinese population in patients of T2DM. (Wei et al 2004)

1.12.1.3. Erythropoietin: In the experimental studies performed in diabetic human beings and

also in the eyes of mouse model, erythropoietin (EPO) has been observed as a potent angiogenic

factor. In the three European-American cohorts that were performed on the promoter region of

EPO gene; (T allele of SNP rs1617640) it was documented that there is a significant association

9

with PDR and end stage renal disease (ESRD). It was further suggested that the concentration

EPO in the human vitreous body was 7.5 times more than healthy normal subjects and they

exhibited TT risk genotype as compared to those individuals that had GG genotype (Tong et al

2008).

1.12.1.4. Hemochromatosis (HFE) gene: Hereditary hemochromatosis is an autosomal

recessive disorder which exhibit a defect in the gene of hereditary hemochromatosis (HFE) that

leads to an increased intestinal absorption of dietary iron and ultimately there is an accumulation

of iron (Peterlin et al 2003). First of all in 1978, an association between diabetic retinopathy and

idiopathic hemochromatosis was established (Walsh et al 1978). Until recently, hereditary

hemochromatosis has been significantly correlated with the two of 37 allelic variants of HFE

gene i.e. C282Y andH63D (Hanson et al 2001).

There was a significant higher frequency of C282Y heterozygotes in the subjects suffering from

proliferative diabetic retinopathy (PDR) as compared to the healthy individuals but there was no

association between H63D genotype and PDR. Therefore C282Y mutation was considered to be

a significant independent risk factor for the causation of PDR (Peterlin et al 2003). Similarly,

hetrozygosity of C282Y was thought to be a risk factor for the development of PDR in

Caucasians having T2DM. (Peterlin et al 2003) 1245 T2DM patients were tested for

heterozygosity of H63D in C282Y and mutation of C282Y HFE gene to determine prognostic

significance of HFE gene mutation in T2DM as well as to determine its prevalence (Davis et al

2008). It was cross sectional and longitudinal study but they could not identify an independent

positive association between HFE gene and vascular complications. Davis et al concluded that

HFE gene could not independently predict cardiac or other causes of mortality (Davis et al

2008).

1.12.1.5. Prolactin: is a hormone and its gene is located on chromosome 6 that can affect

various functions. Many cells of the body such as T-lymphocytes, B-lymphocytes and even

thymocytes have been documented to produce this hormone that can perform the functions of

pro-inflammatory cytokine in the body (Ben-Jonathan et al 1996). Increased secretion of

prolactin has been labeled for different autoimmune disorders such as systemic lupus

10

erythematous and rheumatoid arthritis (Jaraet et al 1992).It has been shown that there is linkage

disequilibrium between HLA-DR and prolactin gene (Brennan et al 1997). Therefore, it was

suggested that polymorphisms of prolactin gene may have an association with HLA gene. A Bgl

II polymorphism has been documented in prolactin gene (Stevenes et al 1999). Still further

studies are required in other ethnic populations to check its relationship between α2β1

polymorphism and diabetic retinopathy.

1.12.1.6. α2β1 gene: Concentrations of β-thromboglobulin and platelet factors have been found

high in diabetic patients as compared to normal controls that lead to hyper activation of platelets

in diabetic patients to collagen, epinephrine and thrombin (Barnettet al 1991). Among these,

collagen is a potent physiological activator of platelets. After their activation, a cascade reaction

starts in platelets which trigger integrin and platelet aggregation (Winocour et al 1992, Mustard

et al 1984). It has been established that polymorphism in intron 7 of α2β1 gene produces

polymorphism in α subunit of collagen receptor and makes retina vulnerable during

hyperglycemia (Jung et al 2000, Matsubara et al 2000). In Japanese and Caucasians populations,

association of genetic variations in α2β1 integrin and diabetic retinopathy has been well

established (Petrovic et al 2003).

It was suggested that integrin α2β1 is one of the under investigation gene, for its association with

retinopathy. Human platelet glycoprotein (GP) plays a vital part in platelet adhesion and

aggregation, and these are important steps in the development of thrombosis and hemostasis.

Therefore variation in the density of platelet GP may assume as a risk factor for hemostatic

dysfunction. Basically integrin α2β1 is a glycoprotein which acts as a receptor for collagen

present on the membranes of platelets (Jung et al 2000).

Platelet 2β1 density is genetically determined that affects adhesion of platelet to collagen which

contribute towards thrombus formation. It was suggested that platelets of diabetic patients often

interact with sub endothelial collagen that is the major component of sub endothelial matrix

(Petrovic et al 2003).

11

The scientists have documented that the 2β1 expression upon the platelets increases chances of

adhesion of platelets to the sub endothelium (Kritzik et al 1998, Kunicki et al 2009).Therefore

they concluded that platelets adhesion to the collagen is an important step for the normal activity

of platelet, during hemostasis and also for wound repair (Kunicki et al 1997). Hence, genetic

variation in the level of 2β1 integrin on the platelet could be due to the presence of multiple

alleles of 2 gene. It was concluded that this expression might have a substantial impact on the

functions of platelet which could contribute towards the process of thrombosis or bleeding.

Kunicki et al (1997) documented polymorphism association of GP Ia gene with the variations in

the levels of 2β1 on platelets. It was observed that platelets of subjects having 807T allele often

exhibit higher levels of 2β1 while subjects having 807C allele showed lower density of 2β1

integrin. By these different experiments, Kunicki et al (1997) concluded that platelets from the

subjects having 807T allele stick considerably quickly as compared to the platelets from the

subjects with 807C allele. This concept of 2β1expression was further studied by Pavkovic et al

(2010) by determining the BglII polymorphism of the 2β1 integrin gene in Macedonian healthy

population and concluded that polymorphism of 2β1integrin gene is present in their population.

Further, this BglII polymorphism of 2β1 integrin gene has been documented by Matsubara et al

(2000) in subjects of diabetic retinopathy.

1.12.1.7. Association of Bgl II polymorphism with diabetic retinopathy: A study showed that

polymorphism of Bgl II have association with the development of retinopathy in patients of

T2DM (Kritizik et al 1998). The genotypes of BglII i.e. (+/+, +/-) have shown increased risk for

the development of retinopathy and nephropathy (Kritizik et al 1998, Kunicki et al 1997). In

many studies (Kritizik et al 1998, Kunicki et al 1997, Carisson et al 1999, Moshfegh et al 1999)

the polymorphism of Bgl II has been linked with 2β1 density of platelet, the degree of adhesion

of platelets to collagen, and also with the chances of having myocardial infarction or stroke

(Carisson et al 1999). Infect it is the very first study that demonstrated an association of Bgl II

polymorphism and the development of diabetic retinopathy. It was suggested that platelets

having Bgl II (+)- could easily interact with glycosylated collagen that may enhance the

development of retinopathy (Reviewed by Matsubara et al 2000). Therefore, it was suggested

that the patients with Bgl II (+/-, +/+) genotype may benefit from the anti-platelet therapy. Even

12

today the precise role of 2β1 integrin in the causation of diabetic retinopathy is not known, but

this study does suggest a strong association of platelets in the process of diabetic retinopathy.

Hence, it was concluded that polymorphism of subunit of 2β1 integrin of Bgl II is strongly

associated with the development of retinopathy in T2DM patients (Matsubara et al 2000).

Matsubara et al (2000) documented higher frequency of polymorphism of 2β1 integrin gene of

Bgl II (+/+) in diabetic retinopathy patients as compared to those patients who did not develop

DR. Different factors such as polymorphism of 2β1 integrin gene of Bgl II (+/+) genotype, age

at start of diabetes, total duration of diabetes, and insulin treatment were independent risk factor

for the development of DR in Caucasians (Petrovic et al 2003) with T2DM. These results are

similar with the findings of Matsubara et al (2000) who performed the study in Japanese

population with T2DMand documented strong association between genetic variations of 2β1

integrin and DR (Petrovic et al 2003) whereas Tsi et al (2001)could not detect an association of

α2β1 integrin with diabetic nephropathy inT2DM in Chinese population.

1.13. Changing concept of type 2 diabetes mellitus

Type 2 diabetes mellitus was considered to be due to insufficient amount of insulin and it was

often linked to obesity which was thought to be the reason for insulin resistance and

glucolipotoxicity (Kahn et al (2006). It has been documented that subjects of T2DM have

subclinical inflammation which can be demonstrated by acute phase proteins, the level of

cytokines, etc which are raised as compared to healthy individuals but their level is low as

compared to individuals with full blown acute infection (Kolb et al 2005) HLA genes

polymorphism have been demonstrated in subjects of T2DM (Groop et al 1986, Tuomilehto-

Wolf et al 1993). Further, polymorphism in TNF-alpha receptor (Ferandez-Real et al 2000) and

TGF-beta (Rosmond et al 2003) has also been studied. These immune disorders and

inflammation are thought to be the reasons for the diabetic complications (Mandrup-Poulsen et

al 2010).

The newly diagnosed subset of T cells called as Th17 cells has been recognized as a vital

contributor in various conditions such as infection, autoimmune diseases, inflammation and

cancers (Dong et al 2008). It has been documented that Th1 cells of CD4+T cells and

13

CD4+CD25hi Treg cells play an important role in the regulation of insulin resistance, glucose

tolerance and T2DM in both mice and humans (Winer et al 2009, Feuerer et al 2009).

The increased level of Th17 and Th1 cells while decreased level of CD4+CD25hi Treg cells have

been observed in inflammation and insulin resistance (Winer et al 2009, Feuerer et al 2009).

T2DM patients have shown predominance of pro-inflammatory subset of cells (Jagannathan et al

2011). Zeng et al (2012) documented reduced CD4+CD25hi Treg/Th17 and

CD4+CD25hiTreg/Th1 ratios in T2DM and they suggested that this decreased ratio is the reason

for the chronic low degree of activation of innate immune system and later on for the

complications of T2DM. They were of the opinion that in T2DM patients, the decreased ratio of

CD4+CD25hi Treg could be due to impaired survival capability and it was not due to the

decreased thymic output. Zeng et al (2012) further suggested that by regulating CD4+CD25hi

Treg and Th17 cells of the host, one can not only prevent the development of diabetic

complications but can also use this approach for the treatment purposes as well.

Studies on diabetic pre-retinal membranes have showed that they consist of deposition of

immunologlobulins, monocytes, components of activated complement system, two categories of

T lymphocytes i.e. suppresser and cytotoxic, fibroblasts, B lymphocytes, and lymphokines e.g.

IL-2 and IL-1 alpha (Baudouin et al 1993, Attawia et al 1999, Tang et al 1995).

1.14. Diabetic retinopathy and autoimmunity

It is suggested that some early aspects of pathogenesis of diabetic retinopathy could be due to

loss of self-tolerance (Baudouin et al 1993, Attawia et al 1999, Tang et al 1995). At the

beginning of retinopathy, anti-pericyte and anti-endothelial cell auto-antibodies are detected in

the circulation of diabetic (Attawia et al 1999) patients. It has been documented that there were

increased vitreous concentrations of IL-6 and IL-8 in the patients of diabetic retinopathy while in

the serum there were elevated levels of IL-8, TNF-alpha, and soluble IL-2 receptor (sIL-2R)

(Doganay et al 2002).

The expression of human leukocyte antigens (HLA) DR and DQ have been determined on retinal

vascular endothelial cells and on the pigmented and non-pigmented epithelial cells (Baudouin et

14

al 1993). It was suggested that aberrant expression of HLA-DR and HLA-DQ antigens on the

places where in normal circumstances do not express these antigens may lead to autoimmunity

by altering these target cell into an antigen presenting cell. This conversion process may allow

the activation of helper T lymphocytes and it subsequently result in the shape of autoimmune

reaction (Bottazzo et al 1983). All these findings suggest the involvement of autoimmune

processes during the early stages of diabetic retinopathy (Reviewed by Kastelan et al 2007).

1.15. Gender bias in autoimmunity

It has been documented that hormones from hypothalamic-pituitary gland and sex hormones may

affect the severity, occurrence, and development of autoimmune diseases (Lahita et al 1990,

Ahmed et al 1990, Arythera et al 1998, Whitacre et al 1999, Task Force on Gender MSaA

1999). The association of gender biases in susceptibility and also in the severity of autoimmune

and allergic diseases have been established (Reviewed by Shames et al 2002).

It is well known that autoimmune diseases are more common in females as compared to males

and females have about 2.7 times more chances as compared to men to develop an autoimmune

disease (Jacobson et al 1997). The severity of autoimmune disease also changes during different

stages of female life such as periods, pregnancy, or menopause, and even by the use of hormonal

contraceptives (Rosciszewska et al 1980, Zorgdrager et al 1997). Likewise to autoimmune

diseases, studies have documented similar kind of gender bias in patients of allergic disease and

asthma (Venn et al 1998, Aberg et al 1990).

It has been observed that female asthma patients are likely to have bad prognosis as compared to

male patients (Jenkins et al 1994). It was suggested that sex hormones might directly bind to the

surface receptors at lymphocytes and macrophages and hence affect their function and they may

act indirectly by acting on hormone-responsive target tissues i.e. through hypothalamic-pituitary

axis (Sthoegher et al 1988). It is also seen that females can mount more intense antibody

mediated immune response as compared to the male patients (Sthoegher et al 1988). One of the

reasons is that estrogen can enhance B cell function whereas inhibitory action has been observed

by testosterone. Therefore serum IgM levels are mostly raised in females as compared to males

(Sthoegher et al 1988).

15

Another observation that has been made is that females develop swift rejection of allografts,

generally more resistance to the mechanism of immune tolerance as compared to males (Graff et

al 1969). The females also demonstrate low incidence and regression of tumors as compared to

male counterparts (Gross et al 1941).

It has been observed that females and hypo gonadal males are likely to maintain an elevated ratio

of CD4+, CD8 T+ cells in their peripheral blood, which means that they have an increased

number of circulating CD4+ T lymphocytes in their circulation (Amadori et al 1995). Therefore,

if androgens are given, they seem to increase CD8+ cells activity. It has been documented that

hormones affect all the lymphoid tissue in the body but the most responsive organ to hormones is

thymus.

It has been observed that the production of T cells by the thymus is at its maximum level during

young age but after puberty this production of hormones is decreased and it is thought that it is

because of the sex hormones (Sobhon et al 1974, Chiodi et al 1940). Further, replacement of

androgen is likely to reverse this balance while estrogen causes an increase in mature T helper

cells. Similar kind of evidence comes during pregnancy because at this time immunological

response also differs and during the postpartum stage worsening of disease have been seen and it

may be due return of TH1 responses (Warner et al 1997). It has been observed that in susceptible

hosts the change of Th2 response in pregnancy can affect allergic diseases which may later lead

to atopic diseases (Shames et al 2002).

It has been documented that a person with the family history of diabetes, overweight (obese),

female sex, living in the urban region and the age above 40 years have high chances of

developing impaired glucose tolerance or diabetes i.e. (Zargar et al 2000). It was suggested that

more woman transmit type-II diabetes to their off springs as compared to males (Reviewed by

Gale et al 2001, Tull et al 1995). There are studies on the development of metabolic syndrome

i.e. diabetes, obesity and hypertension and it has been observed that this syndrome is accepted as

a strong risk factor for type-II diabetes mellitus and females are affected more as compared to

males (Ahmed et al 2010, Mohsin et al 2007).

16

1.16. T regulatory cells (Tregs)

1.16.1. Treg and autoimmunity: In the last a couple of years, researchers have developed a lot

of interest in T regulatory (Treg) cells that are supposed to down regulate the process of

autoimmunity (Kappler et al 1987). Treg cells are the subset of CD4+ T cells. Treg cells which

are important to maintain peripheral tolerance and they do so by the down regulation of antigen

specific immune responses (O’ Garra et al 1997). Nature has provided regulatory mechanisms at

different levels to immune system and the purpose is to minimize the chances of autoimmune

damage. Infect in the process of autoimmunity there is activation of self-reactive T cells and at

the same time there is inefficiency of other regulatory mechanisms which are supposed to control

this process. Actually CD4+Treg cells identify a specific framework region 3 of the Vβ8.2 chain

of TCR (B5 peptide, aa 76-101), whereas CD8+ Treg cells attack at the complementarity

determining region (CDR) ½ determinant. Different studies have shown that these cells secrete

TGF-β, IL-10 and IL-4 to down regulate autoimmune diseases (O’ Garra et al 1997, Delovitch et

al 1997, Nicholson et al 1996, Reviewed by Madakamutil et al 2003).

A study was performed to determine the percentage of CD4+CD25+ Treg cells in the patients of

autoimmune liver disease. This study included both the aspects of the disease i.e. at the clinical

presentation and later at the time of remission. The purpose was to determine the frequency of

Treg cells at different stages of disease and to observe the ability of CD4+CD25+ T cells to

expand and at the same time to inhibit INF-gamma production. This study suggested the possible

mechanism to develop autoimmunity against liver and they concluded that its therapy must be

directed to increase the number of Treg cells (Longhi et al 2004).

1.16.2. Types of Treg cells: The ability of the T cell that can suppress the immune response

provides them the quality of regulatory T cell. These Treg cells can be classified into natural T

reg cells and induced or adoptive Treg cells. Natural T reg cells (nTreg) are those cells which are

self-antigen specific CD4+ T cells and they express CD25 in high levels and Foxp3-gene as well.

Further, these cells also express CD62 ligand, CD103, glucocorticoid induced tumor receptor,

cytotoxic T-lymphocyte Antigen 4, CD152, neurophilin and CD45RO. It was suggested that

these nTregs cells are selected within the thymus, and they become Treg cells in the peripheral

circulation (Nandakumar et al 2009).

17

Another variety of Treg cells are called adoptive or induced T regulatory cells. They arise due to

activation of mature T cells and it happens in the absence of antigen exposure or co-stimulation

or occasionally in the presence of some inhibitory cytokines. Generally, induced Tregs consist of

type 1 regulatory T cells (Tr1) and Th3 cells. It has been observed that Tr1 cells exhibit Th1 as

well as Th2 markers e.g. CXCR3, CCR5, CCR3, CCR4 and CCR8. Upon activation these cells

exhibit CD40L, CD69, CD28, CTLA-4, IL-2R-α, IL-15Rα and HLA-DR. It is documented that

Tr1 cells have the property of producing increased quantity of IL-10, TGF-β and IL-5. Further, it

was determined that naïve CD4+ T cells develop into IL-10 producing Tr1 cells but it happens in

the existence of immunosuppressive drugs, soluble proteins and during the stages of chronic

stimulation due to allergic, infectious or tumor antigens.

1.16.3. Murine CD4+ T cells: There was a study to investigate the role of CD4+CD25+ cells

towards alloantigen and to determine their importance for the induction of tolerance. In this

experiment murine CD4+ T cells were exposed to alloantigen through CD40/CD40 ligand or by

the exposure of CD28/cytotoxic T lymphocyte which were associated with antigen-4/B7

blockade. Secondary mixed leukocyte reaction and against the alloantigen tolerance was

observed. It was concluded that CD4+CD25+ cells are needed for the development of tolerance

process against alloantigen. They claimed it to be an important application for the strategies to

create tolerance while targeting the pathways of co-stimulatory signals for the T cells (Taylor et

al 2001).

1.16.4. Regulation of Treg cells: It has been documented that Treg cells have well defined

phenotype, they produce a specific set of cytokine and they have specific mechanism of action

which include CD8+ and CD4+. It has been observed that within the domain of CD4+Treg cells,

there are T-rig cell type-I that produce IL-10, transforming growth factor-β secreting T helper

cell type-3 and a sub population of Treg cells that exert suppressive function in a very specific

contact dependent manner and in the periphery these cells express high levels of CD25 and the

fork head and winged-helix family transcription factor (Foxp3), gamma-delta T cell, and NKT

cells (Dejaco et al 2005).

18

A study was conducted to identify CD4+CD25+ T cells development and their function. Further,

they determined the diversity of both CD4+CD25+ as well as CD4+CD25- T cell populations in

the thymus and peripheral circulation. They concluded that in humans CD4+CD25+ T cells can

recognize similar kind of antigens as CD4+CD25- T cells can. It was suggested that the reduced

levels of TCR on Treg cells recommend different requirements for their activation and in this

way it may contribute towards immune system responses that in which way they have to precede

i.e. a specific response should be suppressed or it has to be augmented. They concluded that in

humans CD4+CD25+ T cells repertoire is quite diverse. However, it is clear that it is extensive

and composite just like the population of CD4+CD25- T cells (Kimberly et al 2004).

1.16.5. Foxp3: Phenotypically CD4+ Tregs are characterized by increased expression of the level

of CD25 and at the same time forkhead winged-helix family transcription factor (Foxp3) which

is a master control gene. In 2001, Foxp3 gene was first identified in Scurfy mice as the disease

causative agent. In this case due to single gene mutation on the X chromosome the animal

spontaneously develop severe autoimmunity or sever inflammation. Clinical findings in humans

with mutated FOXP3 gene encounter disease which is given the name as IPEX (immune

dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome). This disease results in

autoimmunity where various endocrine organs are involved (Sakaguchi et al 2007).

There is evidence from the studies where scientists have discovered that the expression of

FOXP3 mRNA transcripts and other protein can also be expressed in the activated non-

regulatory human T cells. Unlike older observations, this time FOXP3 induction was not

specifically associated with the suppressive activity in these activated T cells. In autoimmune

patients low levels of CD4+CD25hi T cells were determined e.g. in individuals with juvenile

idiopathic arthritis, psoriatic arthritis, HCV–associated mixed cryoglobulinaemia, autoimmune

liver disease, SLE and Kawasaki disease. Further, low levels of CD4+CD25hi T cells in the

circulation have also been correlated with an increased activity of the disease or it is associated

with the poor prognosis. They concluded that decreased percentage of Tregs in the circulation is

not a common observation in all the patients of autoimmune diseases and it also do not indicate

the real picture at the inflammation site (Dejaco et al 2005).

19

1.16.6. Surface markers for Treg cells: Till to date there is not a single specific surface marker

available in the market for the enumeration of Treg cells. Most of the time increased surface

expression of IL-2 receptor alpha chain i.e. CD25 is considered as a reliable marker for most of

the human Treg cells. It is assumed that their regulatory capacity is augmented in CD4 T cells

that express increased levels of CD25. Other surface markers for the identification of Treg cells

include CTLA-4, CD62L which is also known as L-selectin, CD134 (OX40), glucocorticoid

induced tumor necrosis factor receptor, membrane bound TGF-β, programmed cell death-ligand

1, and α4β7/α4β1 integrin. It was observed and possible explanation for the induction of Treg

cells due to pro-inflammatory cytokines from synovial fluids of patients of rheumatoid arthritis is

that IL-6 cytokine is increased at the sites of inflammation. This cytokine causes resistance of

CD4+CD25- T cells towards suppressive actions of Treg cells. Further, IL-6 producing cells have

been detected and it was observed that IL-6 abrogates suppression of human Treg cells

(Hoffmann et al 2007, Dejaco et al 2005).

1.16.7. Role of co-stimulatory molecules: It has been suggested that the specific signals which

assist the Treg cells in the peripheral circulation are still not very clear but the evidence about the

involvement of co-stimulatory molecules e.g. CTLA-4, TGF- β and dendritic cells is present. It

was documented that T cells that express retroviral Foxp3 are far less suppressive as compared to

the freshly isolated CD4+CD25+Tregs121 cells and hence it is suggested that it may be not

sufficient to down regulate autoimmune process in human beings. Further, it has been suggested

that increased percentage of Treg cells also exhibit increased risk of developing cancer and it

may alter immune response during stages of acute or chronic infections. There were clinical

trials where administration of growth hormone or IL-17 cytokine increased thymic size and even

its cellularity. It has been noted that in autoimmune diseases there can be insufficient suppression

of inflammatory process or there can be transformed creation of Treg cells that are needed for the

initiation and later for the continuation of autoimmune disease (Dejaco et al 2005).

The concept of Treg cell involvement in the autoimmune diseases have been studied by various

scientists, therefore Treg cells participation in different human autoimmune diseases have been

reviewed by Buckner et al 2010. The role of Treg cells in type 1 diabetes mellitus has been

studied and proved extensively (D’Alise et al 2008, Clough et al 2008, Tang et al 2008).

20

Scientists have pointed out towards derangement of immune mechanisms in type 2 diabetes

mellitus as well (Keppler et al 1987, O’ Garra et al 1997, Madakamutil et al 2003). Zeng et al

2012 have provided some evidence about the involvement of Treg cells and Th17 cells in the

development of complications in T2DM patients but the convincing evidence about the

development of autoimmune processes in type 2 diabetes mellitus is lacking.

1.17. Cytokines

It is well documented that hyperglycemia is the main reason for the development and also for the

progression of diabetic retinopathy but still, precisely about the pathogenesis of diabetic

retinopathy the concepts are not clear. The evidence supports that it is due to chronic

inflammation. Cytokines may play physiological role in maintaining the ocular surface. The level

of two chemokines i.e. RANTES/CCL5 and stromal cell derived factor (SDF-1α) was much

raised in the patients of severe diabetic retinopathy. It is known that ICAM-1/CD54 is an

intracellular adhesion molecule which is mandatory for the adhesion of leukocytes to capillary

endothelium, and it has also been associated in the pathogenesis of diabetic retinopathy.

Monocyte chemo-attractant protein (MCP)-1/CCL2 has been found increased in diabetic

retinopathy. Several inflammatory cytokines and chemokines have been found elevated during

severe diabetic retinopathy such as RANTES/CCL5, stromal cell derived factor (SDF-

1α),epithelial neutrophils activator, interferon-induced protein-10 which is also known as

CXCL10, stromal cell derived factor-1 that is also known as CXCLl2, monocyte chemo-

attractant protein-1 which is also given the name as CCL2, macrophage inflammatory protein-1

that is known as CCL3, IL-8 also known as CXCL8, intercellular adhesion molecule-1 that is

also known as CD54, vascular cell adhesion molecule which is known as CD106, vascular

endothelial growth factor and IL-6 cytokine (Meleth et al 2005). Many researchers have

documented increased level of different cytokines in the intra-vitreous fluid of eye (Yoshimora et

al 2009, Dongancy et al 2002, Ongkosuwito et al 1998).

1.17.1. IL-6

1.17.1.1. Production and action of IL-6: IL-6 is synthesized by different cells that include

macrophages, fibroblasts, epidermal cells, vascular endothelial cells, and vascular smooth

21

muscles (Kishimoto et al 1989). It is also documented that within an eye, the causes of IL-6

consist of retinal pigmented epithelial cells, corneal epithelial cells, keratocytes, iris and ciliary

body. It is well observed that IL-6 cytokine is capable of various functions that may induce an

increase of endothelial permeability directly and at the same time it induces new vessel

formation (Cohen et al 1996, Maruo et al 1992). This cytokine can induce an increased quantity

of vascular permeability and neovascularization through the expansion of vascular endothelial

growth factor (VEGF) indirectly.IL-6 exhibits a variety of biologic activities including activation

of macrophages. In a study, it was documented that in both aqueous and vitreous, the levels of

VEGF and IL-6 are closely correlated with each other (Funatsu et al 2005). It was observed that

the levels of VEGF and IL-6 were increased in the eye as compared to their plasma levels

(Funatsu et al 2005). Funatsu et al concluded that the levels of aqueous and vitreous of VEGF

and IL-6 were associated with the severity of diabetic retinopathy (Funatsu et al 2005).

1.17.1.2. IL-6 and Eye: Significantly increased levels of IL-6 were found in the conjunctival

epithelium in the patients of Sjogren syndrome (SS) and non-SS dry eye as compared with

controls (Pflugfelder et al 1999, Chotikavanich et al 2009). The effect of desiccation on secretion

of inflammatory cytokines in corneal epithelial cells and in rat desiccation model was

investigated and it was found that desiccation induced IL-6 expression in corneal epithelial cells,

suggesting that IL-6 participates in the desiccation induced cell death. Therefore, it was expected

that neutralization of IL-6 would suppress cell death. In fact, anti-IL-6 antibody protected

corneal epithelial cell line (CEPI) from cell death induced by short term desiccation (Higuchi et

al 2011).

It has been documented that in human trabecular meshwork (HTM) cells, TGF-β1 and IL-6 are

required for the signaling pathways and these cells had increased expression of IL-6 cytokine

that is infect happening due to mechanical stress. Linton et al incubated HTM cells with TGF-β1

which showed a significant increase of protein, mRNA, the level of IL-6 and they concluded the

importance of TGF-1 in the induction of basal and stretch-induced expression of IL-6 cytokine

by the involvement of an autocrine loop between TGF- β1and IL-6 (Liton et al 2009).

22

1.17.1.3. IL-6 and diabetic retinopathy: A study was conducted in children with diabetes

mellitus type-1 to determine the relationship in early diabetic retinopathy and the IL-6cytokine.

Higher concentration of IL-6 was demonstrated in the serum of diabetic patients with retinopathy

as compared to diabetic patients without diabetic retinopathy and the level of cytokine was

associated with the severity of disease. In this study the control group showed the lowest level of

IL-6 among the studied population (Mysliwiec et al 2008).

A study was carried out to determine the possible involvement of IL-6 in the pathogenesis of

proliferative diabetic retinopathy (PDR). Mocan et al (2006) documented higher concentrations

of intra-vitreous IL-6 cytokine in PDR patients as compared with the control subjects. The serum

levels of IL-6 in the PDR subjects were decreased as compared to the lower measurable

threshold by the ELISA technique. This study could not determine association between intra-

vitreous IL-6 levels and patient age, duration of diabetes mellitus or vitreous hemorrhage, etc. It

was concluded that IL-6 may have a contribution towards the development of PDR (Mocan et al

2006). Intraocular production of IL-6 seems to be responsible for the elevated intra-vitreous

levels observed. The serum IL-6 concentrations were undetectably low in all the type 2 diabetic

patients. The author accepted that although the sample size is a limitation of this study but it

supported a previous study where elevated levels of IL-6 in the vitreous fluid of diabetic patients

were not associated with corresponding elevations in the serum IL-6 levels. At the same time, the

results of Mocan et al (2006) suggested that systemic circulation of IL-6 was not the primary

source for the elevated intra-vitreous IL-6 concentrations. It is also believed that IL-6 levels may

have been elevated secondary to acute hemorrhage (Mocan et al 2006).

1.17.1.4. IL-6 in the eye and in the serum: In a study Nakamura et al (2003) tried to determine

the reasons for the initiation of diabetic retinopathy and for this they worked on IL-6 cytokine

and advanced glycation end products. They documented higher levels of IL-6 cytokine in the

vitreous fluid of PDR patients as compared to the control group. Further they suggested the level

of IL-6 cytokine was higher in those patients of PDR who had vitreous hemorrhage (VH) as

compared to those PDR subjects who did not have VH. The level of IL-6 was much higher in the

vitreous fluid as compared with the serum and these scientists could not determine any

correlation of IL-6 levels within these two fluids. They proposed that there may be an increased

23

amount of advanced glycation end products in the vitreous fluid that causes production of IL-6

from retinal Muller cells and finally they contribute towards the development of diabetic

retinopathy. They could not determine any significant association of IL-6 levels between the

serum and vitreous fluid of the patients. It was suggested that the levels of IL-6 of vitreous fluid

could be independent from the levels of IL-6 in the serum and therefore increased levels of IL-6

in the vitreous fluid could be of intraocular in origin and that is how it signifies its presence

during PDR (Nakamura et al 2003).

A study was conducted to define the relationship between the levels of cytokines in the serum

and the different stages of DR among diabetes patients and they compared these levels with the

levels in the healthy controls. They could not determine the level of IL-6 in both the patients and

the control group because it was below the detection limits of that particular assay. They

concluded that IL-6 is not an important factor for the pathophysiology and progression of DR.

Further, they found out that IL-6 was raised in poorly controlled diabetes (Doganay et al 2002).

In a study, patients of diabetic vitreo-retinopathy were selected and among them the levels of

different cytokines were measured in their vitreous fluid and serum. Vitreous levels of IL-6 were

mush greater than in the non-inflammatory retinopathy but in the sera, concentrations of IL-6

was similar in proliferative and non-proliferative retinopathy subjects. They also documented

that IL-6 deceases with the duration of diabetes because the levels of IL-6 was low in patients

who had diabetes for more than 10 years as compared to those patients who had diabetes of less

than five year duration (Yuuki et al 2001).

1.17.1.5. IL-6 disturbs immune privilege site: A study was performed in the animal model to

define the immunosuppressive status of aqueous humor (AqH) in the mouse eyes. During the

experiment, the mouse eye was exposed to endotoxin-induced uveitis (EIU) and the aim of the

scientists was to identify the set of cytokines that are accountable for immune-modulatory

activity within EIU AqH. It was demonstrated that there is local production of IL-6 after PLS-

induced intraocular inflammation. Therefore they concluded that it is IL-6 that is a key hazard to

ocular immune privilege. Therefore, it was concluded that approaches should be developed to

24

decrease intraocular synthesis of IL-6 and in this way it may reduce the inflammation and would

restore ocular immune privilege (Ohta et al 2000).

It has been observed that most of the time there is a rejection of retinal pigment epithelium

(RPE) allografts after retinal transplantation and therefore the long term success is difficult

(Enzmann et al 2000, Algvere et al 1997, Gouras et al 1996). A study was conducted to

determine the importance of IL-6 during the rejection process and to identify the possibility to

use its levels for monitoring transplant rejection. It was shown that there is an increase in the

level of IL-6 in the vitreous fluid after the transplantation and it was low in the control group.

They supported the potential of IL-6 to act as a modulator of the immune response after such

transplantation. They also suggested that since there is a local production of IL-6 in the eye

therefore for monitoring purposes, after the transplant it will not be advisable to determine the

level of IL-6 in the serum (Enzmann et al 2000).

A study was conducted to measure the levels of cytokines in the vitreous fluid of patients

suffering from different eye diseases. They included the patients of proliferative diabetic

retinopathy (PDR), proliferative vitreo-retinopathy (PVR), vitreous hemorrhage and patients of

macular pucker. Elevated levels of IL-6 were detected in the vitreous fluid of PVR and it

correlated with disease severity but it was low / undetectable in patients with PDR. They

proposed the contribution of IL-6 in the pathogenesis of this ocular disorder (Kauffmann et al

1994).

1.17.1.6. Anti-IL-6 as treatment modality: It has been documented that an increased level of

IL-6 contributes towards different autoimmune inflammatory diseases e.g. RA and SLE

(Nishimoto et al 2006). There is a recombinant humanized anti IL-6 receptor antibody by the

name of tocilizumab, which has been proven to be of value in the usage of many diseases. It has

been used both in experimental studies and also in the clinical settings as well e.g. RA, systemic

onset juvenile idiopathic arthritis, Chron’s disease, reactive astrogliosis, and experimental spinal

cord injury (Yoshimura et al 2009).

25

1.17.1.7. Role of IL-23: In a study an experimental model, experimental autoimmune uveitis

(EAU) was used to determine the contribution of IL-6 in the initiation of refractory ocular

inflammation. It was observed that for the establishment of IL-17 producing T-helper subset

(Th17) from naïve CD4+ T cells, both the cytokines i.e. IL-6and IL-23 are needed. It was

concluded that IL-6 is accountable for the development of ocular inflammation which is at least

partially because of IL-6 dependent Th17 differentiation. Therefore in humans, to treat refractory

endogenous uveitis, IL-6 may be considered as a target. It has been found that during chronic

ocular inflammation, it isTh-17 which is blamed for. In this sequence of inflammatory reaction,

IL-6 has been recognized as an important element in the induction of Th-17 from the naïve T

cells along with the combination of TGF-β. Both the cytokines i.e. IL-6 and IL-23 have been

identified for the production of Th-17. IL-17 has been identified as a vital component in the

pathogenesis of different inflammatory and autoimmune disorders, e.g. RA (Murphy et al 2003),

chronic obstructive pulmonary disease (Curtis et al 2007), bone destruction (Sato et al 1992),

EAE (Langrish et al 2005) and experimental autoimmune uveo-retinitis (Yoshimura et al 2008,

Amadi-Obi et al 2007). Further, it has been suggested that by blocking the cytokines such as IL-

6 and IL-23 improves EAU in terms of Th-17 differentiation and its expansion (Yoshimura et al

2009).

1.17.1.8. IL-6 and Treg cells: The crucial role of IL-6 in the production of Foxp3 CD4+CD25+

regulatory cells and Th17 has been studied. It was documented that IL-2 and TGF-beta drives

immature (naïve) T cells into regulatory cells (iTregs) that have the expression of

forkhead/winged helix transcription factor (Foxp3). Further it was observed that by the

combination of IL-6 with the TGF-beta causes induction of IL-17 producing cells (Th17).

Further, IL-6 cytokine in combination with TGF-beta, which is coming from thymus-derived

natural regulatory T cells (nTregs), can also convert them to Th17 cells (Xu et al 2007). It has

been documented that IL-6 receptor expression and also IL-6 signaling is being down regulated

by the IL-2 and TGF-beta cytokine (Zheng et al 2008). It was found that activating nTregs in the

presence of IL-2 and TGF-beta down regulated expression of IL-6 receptor and its signaling,

thus enabling them to also develop resistance against conversion of Th17 (Xu et al 2007, Zheng

et al 2008). Further it was suggested that in an inflammatory condition, resistance of iTregs to

26

attain the form of Th17 recommends that they can be more effectively used as compared to

nTregs (Zheng et al 2008).

1.17.1.9. IL-6 and Th17 cells: It was found that IL-6 and TGF-beta is required for lineage

commitment of Th17and for the maintenance of this lineage IL-23 is essential. It was

demonstrated that there is constitutive expression of IL-23 receptor and RORγt (lineage specific

transcription factor for Th17) upon NKT cells and therefore they can rapidly cause IL-17

production upon ligation of its receptor and it is independent of IL-6. It was concluded that IL-

17which is secreted from NKT cells (Rachitskaya et al 2008) is not due to a particular subset of

NKT and it differs considerably from the adaptive IL-17 which is being produced by Th17 cells

(Rachitskaya et al 2008). It has been documented that innate IL-17 production by the NKT cells

is quite rapid, it is independent of IL-6, it is facilitated by the engagement of TCR and more over

it is constitutively expressed IL-23R which makes it different from the adaptive IL-17. It was

concluded that contribution of IL-17 from NKT cells is different as compare to the involvement

of pro-inflammatory IL-17 from Th17 cells. These differences have been associated with the

effector cells in different autoimmunity models (Rachitskaya et al 2008).

1.17.2. IL-17

CD4+ T cells have been divided into various subgroups which are on the basis of different

cytokines that are being produced and also upon the various functions they perform. One

population of Th cells is Th17 that is characterized by the production of IL-17 cytokine

(Harrington et al 2005). IL-17 comprised of six family members of related cytokines i.e. IL-17A,

B, C, D, E, and F (Kolls et al 2004). It is IL-17E that is also labeled as IL-25, and it has been

designated with Th2 responses and also with the immune responses against helminthes (Fallon et

al 2006, Owyang et al 2006). It is suggested that IL-17A is a pro-inflammatory cytokine which

has the capacity to induce the production of many different cytokines and chemokines e.g. IL-6,

IL-8, GM-CSF and MCP-1, and endothelial and epithelial cells. (Cooke et al 2006)

1.17.2.1. Role of IL-17:In 1995 when scientists became aware of IL-17 and they found out that

it is produced by T cells and this cytokine has wide effects on inflammation and the activation of

neutrophils (Fossiez et al 1996, Yao et al 1995). Later during 2006, while performing

27

experiments on muse model, precise source of IL-17was identified and then these cells were

labeled as Th17 cells (Miossec et al 2003). It has been documented that these Th17 cells have

major contribution in different human diseases that are related to inflammation and tissue

destruction such as rheumatoid arthritis, psoriasis, Crohn’s disease, and multiple sclerosis,

therefore it was suggested that IL-17 has got the potential to be used as treatment option

(Firestein et al 2003, Lubberts et al 2000). It was documented that constant supply of IL-17 by

virtue of over-expression of gene in a healthy knee joint induced immense damage and it was

accompanied with broad inflammatory cell migration, erosions of bones and there was

degradation of cartilage tissue (Lubberts et al 2002). It has been observed that synovium of the

rheumatoid arthritis patient can produce IL-17. Further, along with inflammation of synovium,

there is bone resorption which also associate with inflammation induced by IL-17 and it also

participates in similar diseases e.g. periodontal disease and joint prosthesis loosening (Anderson

et al 2007, Oda et al 2003).

1.17.2.2. Pro-inflammatory cytokine: IL-17 is regarded as a pro-inflammatory cytokine like

TNF-α, IL-1, IL-6, IL-8, GM-CSF and chemokines CXCL1, 2 and 8, which are the hall marks

of acute inflammatory process (Aggarwal et al 2002, Fossiez et al 1996, Jovanovic et al 1998,

Yao et al 1995). The salient feature of Th17 mediated inflammation is that it mobilizes

chemokines that are essential for the recruitment of neutrophils (Cooke et al 2006).

1.17.2.3. Th1 vs Th17: The contribution of Th17 cells in inducing autoimmune pathology is also

being acknowledged in those conditions which were blamed for Th1 mediated (Amadi-Obi et al

2007). In a study it is shown that two human inflammatory diseases i.e. uveitis and scleritis have

great contribution of Th17 cells and their findings were confirmed in EAU; a model for uveitis

(Amadi-obi et al 2007). It has been observed that IL-2 causes expansion of Th17 cells while they

are inhibited by INF-γ (Amadi-obi et al 2007). It was observed that the number of Th17 cells

was increased in the infections of eye i.e. active uveitis and scleritis and the number of Th17

cells were decreased after treatment (Amadi-obi et al 2007). It was documented that IL-17 is

elevated during EAU, uveitis and scleritis, and at the same time IL-17 cytokine induced

expression of TNF-α on retinal cells, that suggested the mechanism of Th17 to cause pathology

in the ocular region (Amadi-obi et al 2007).

28

1.17.2.4. IL-17 in human diseases and in animal models: Increased levels of IL-17 have been

detected in rheumatoid synovitis, multiple sclerosis, psoriasis and systemic lupus erythematous

(Firestein et al 2003). TGF-β plus IL-6 are essential for the development of Th17 cells from the

naïve CD4+ T cells. It was observed that for this differentiation, there should be nonexistence of

INF-γ (Veldhoen et al 2006, Park et al 2005, Harrington et al 2005). Further it was suggested

that IL-23 is needed for IL-17 production and it actually promotes Th17 cell expansion (Duerr et

al 2006). Later some of the studies pointed out that by particularly targeting IL-23 one can be

reduce the symptoms of inflammation (Lock et al 2002).Two experimentally induced

autoimmune conditions i.e. collagen induced arthritis (CIA) and experimental induced

encephalomyelitis (EAE) and many other conditions are infect facilitated by Th17 cells (Cua et

al 2003, Murphy et al 2003). Different in vivo experimental studied have pointed out that by the

neutralization of IL-17 through specific antibody one can prevent the initiation of EAE. Further

it was observed that the deficiency of IL-23 protected against EAE and CIA disease (Cua et al

2003, Murphy et al 2003).

Using the model of experimental autoimmunity uveitis (EAU), it was shown that Th1 and Th17

cells have the ability to cause tissue damage that depends on the methods used to initiate the

disease (Cua et al 2003, Murphy et al 2003). It was observed that by giving antibodies against

IL-17 one can inhibit EAU disease that can develop after immunization with retinal antigen

intra-retinal binding protein (IRBP) and it can also reverse an established disease. It was

concluded that Th17 is not the only reason for the tissue damage in MS or EAE (Cua et al 2003,

Murphy et al 2003).

It has been observed that IL-1, IL-6 and IL-23 facilitate differentiation of Th17 in humans and

there is no need for the TGFβ-1 (Acosta-Rodriguez et al 2007). It has been documented that

Th17 cells are vital for the immunity to check fungi and extracellular bacteria and they can also

be blamed for the pathogenesis of autoimmune diseases. Therefore, it was suggested that by

specifically attacking Th17 cells, beneficial effects in inflammatory and autoimmune diseases

can be achieved (Chen et al 2008, Lubberts et al 2007).

29

1.17.2.5. Concepts about IL-17 formation: It was observed that IL-6 with TGF-beta can induce

Th17 cell generation from the naïve T cells while TNF-alpha and IL-1beta is not required

(Kimura et al 2007). At the same this reaction inhibits TGF-beta induced Foxp3 expression

(Kimura et al 2007). It was also found out that IL-6 and TNF-beta can sustain activation of

signal transducer and activation of transcription (Stat)3, but they cannot express Stat1 (Kimura et

al 2007). Either IL-27 or INF-γ can suppress Th17 induction by TGF-beta along with IL-6 and

they can also express preserve Stat1 activation (Kimura et al2007).

It was observed that Th17 cells with specificity for self-antigens can be pathogenic because they

cause initiation of sever autoimmunity and inflammation (Bettelli et al 2007). Further, it was

documented that TGF-beta along with IL-6 and transcription factors STAT3 and RORγt are

needed for the initial stages of Th17 cells and for the later stabilization of Th17 cells,IL-23 is

required (Veldhoen et al 2006). A new player (IL-21) which is produced by Th17 cells

contribute substantially in the multiplication of Th17 cells (Bettelli et al 2007). Another study

documented that the differentiation of Th17 cells in mice, needs TGF-β and IL-6 and the

transcription factor RORγt (Acosta-Rodriguez et al 2007). In human beings naïve CD4+ T cells,

RORγt expression and Th17 formation is induced by IL-1β while it is potentiated by IL-6 but

this lineage of cells is depressed in the presence of TGF-β and IL-12 (Duerr et al 2006). Acosta-

Rodriguez et al concluded some basic dissimilarity in the ingredients for the differentiation of

Th17 cells in human and mice (Acosta-Rodriguez et al 2007).

It was observed that IL-6 can endorse the growth of Th17 by stimulating T cells gp130-STAT3

pathway and in this way it has smallest effect on the development of Treg (Acosta-Rodriguez et

al 2007). Acosta-Rodriguez et al concluded that by blocking IL-6-gp130-STAT3 pathway ofCD4

T cells, can be a reasonable option to check unsolicited Th17-mediated responses that also

include autoimmune diseases (Nishihara et al 2007).

1.17.2.6. Role of IL-6 in IL-17 production: In an experiment upon IL-6 deficient (Il6-/-) mice it

was observed that these animals cannot establish Th17 production and the repertoire in their

circulation consisted of Foxp3 Treg cells. Upon removing the Treg cells, there was re-

appearance of Th17 cells in these (Il6-/-) mice, which suggested some other routes for the

30

production of Th17 cell in vivo. They showed that IL-21 along with TGF-beta induced Th17

cells in naïve IL6-/- T cells but IL-21-receptor deficient T cells are unable to generate Th17

response (Korn et al 2007).

TGF cytokine is critical for initiation ofTh17 development and it also up-regulates IL-23R

expression, and in this way it shows responsiveness to IL-23. It is INF and IL-4 that antagonizes

the action of TGF on naïve T cells, therefore it indicates the process for the divergence of Th1,

Th2 and Th17 lineage (Mangan et al 2006).

IL-23 causes the expansion of Th17 cells that leads to production of IL-17, IL-6 and TNF-α

(Veldhoen et al 2006). Now the scientists believe that Th17 cells discovery is a mile stone in

making better understanding of inflammatory processes (Cooke et al 2006). It has been

documented that there is an increased production of IL-23 and IL-17 in the pathogenesis of

several autoimmune diseases, including multiple sclerosis and rheumatoid arthritis (Joseph et al

2011). Further they suggested that inflammation by virtue of IL-23/IL-17 and understanding

about related molecules can become a therapeutic agent for autoimmune diseases (Wong et al

2008).

1.17.2.7. IL-27: IL-27 is constitutively present in the retina of eye and it is up-regulated by INF-

γ while it obstructs propagation of Th17 cells (Amadi-Obi et al 2007). It suggested that it is INF-

γ that may alleviate uveitis by antagonizing Th17 by the production of IL-27 in the target tissue.

It is believed that IL-23 and IL-27 also inhibited secretion of IL-2 to the almost at the same

degree but this effect is more noticeable for IL-27 (Amadi-Obi et al 2007). IL-27 prevents the

IL-2 production, suppresses Th1 expansion and Th17 cells and also impedes IL-23 induced IL-

17 expression through the activated CD4 T cells (Owaki et al (2005). It was documented that

increase in activated Th17 cells was stopped by primary retina cells, through IL-27 which was

endogenously produced. It has been observed that there is a reciprocal antagonism between Th1

cells and Th17, which becomes the reason for the production of mutual T-cell developmental

pathways by IL-27 and IL-23. It is now known that Th17 cells are involved in the pathogenesis

of immune-mediated diseases (Amadi-Obi et al 2007) and studies have documented that specific

31

targeting of IL-23 may result in the improvement of several inflammatory conditions (Cooke et

al 2006).

1.17.2.8. IL-23: The establishment of IL-23-IL-17 cytokine network in different mechanisms of

pathogenesis lead the scientists to further investigate these cytokines for CD4 T effector lineage

i.e. Th17. It has been documented that Th17 cells play role in the control of certain pathogens,

analogous to the specialized functions of Th1 and Th2 cells to deal with intracellular pathogens

and also parasitic infections (Harrington et al 2006). IL-23 enhanced production of human Th-17

cells and at the time it is a powerful inducer of other pro-inflammatory cytokines (Chen et al

2007).

It is well documented that rheumatoid arthritis and multiple sclerosis are basically IL-17

mediated autoimmune diseases (Cooke et al 2006). It is believed that in future manipulation of

IL-17/23 axis of inflammation could be used as therapeutic targets for various diseases

(Furuzawa et al 2007).It is believed that IL-23 in not a differentiation factor for the production of

Th17 cells from naïve T cells (Veldhoen et al 2006). A dichotomy was observed in the initiation

of pathogenic Th17 cells that could induce autoimmunity and Foxp3 Treg cells that can check

autoimmune tissue injury (Bettelli et al 2006).

1.17.2.9. IL-21 is a major element in the production of IL-17 secreting CD4T cells and also for

the establishment of experimental autoimmune encephalomyelitis. The results of in vitro studies

have suggested that IL-21 can guide Th17 responses along with TGF-β (Spolski et al 2007). At

the same time one study has challenged the perception that IL-21 is important in producing Th17

mediated immunity and disease (Korn et al 2007). They also suggested that IL-21 signaling

inhibits, rather than exacerbates Th17 mediated EAE (Coquet et al 2008).

RORγt induces transcription of the genes encoding IL-17. Th17 cells are constitutively expressed

all over the intestinal lamina propria, also express RORγt and they are not present in the mice

which are deficient for RORγt or IL-6 (Amadi-Obi et al 2007). RORγt is a main element for the

immune homeostasis and therefore it can be used as a therapeutic option in inflammatory

diseases (Ivaylo et al 2006).

32

It was observed that EAE is ameliorated by the suppression of T-bet and it is basically through

stopping initiation of auto reactive Th1 cells and also by inhibiting pathogenic Th17 cells via the

regulation of IL-23R (Gocke et al 2007).

A small molecule present in herbal medicine is known as ursolic acid (UA) and its contribution

to suppress IL-17 production by selectively antagonizing the function of RORγt was studied. It

was found that this molecule specifically and quite efficiently stops the function of RORγt, that

lead to immensely decrease in IL-17 expression in developing and already differentiated Th17

cells. Therefore, UA was suggested as a reasonable option for treating Th17-mediated

inflammatory diseases and cancer (Tao et al 2011).

T-betis an important element for the production of INF-γ producing CD4 Th1 lymphocytes and

the suppression of T-bet can ameliorate EAE because in this way it stops initiation of auto

reactive Th1 cells and it also checks pathogenic Th17 cells through IL-23R regulation (Gocke et

al 2007).

1.17.2.10. Plasticity of Th17: It has been observed that by providing appropriate stimuli such as

IL-12, Th17 lineage can be converted into Th1-type cells (Zheng et al 2008). In early days it was

believed that IL-23 is an essential factor for expanding and maintaining Th17 cell responses but

studies have documented that IL-23 can facilitate aberration from Th17 to Th1 phenotype (Cua

et al 2006, Veldhoen et al 2006). It has been established that variations of the IL-23R gene can

effect IL-22 secretion (Weaver et al 2006). Nevertheless the findings of a study upon two

antibodies for neutralizing IL-23/p40 subunit were not promising. Further, a study performed

later for blocking IL-17A was also not effective in CD (Fujino et al 2003). It is assumed that

tissue damaging immune response in IBD is due to some other cytokines and they are not Th17

related (Fujino et al 2003). They speculated that at the same time neutralization of at least two or

more of these molecules e.g. IFN-gamma and IL-17A could assist the patients to deal with the

active phases of IBD (Annunziato et al 2007, Monteleone et al 2011).There is a contradiction in

the production of Th17 cells that leads to autoimmunity and Treg cells that check autoimmune

tissue injury (Fujino et al 2003).

33

It has been demonstrated in an in vitro study that in inflammatory conditions at the single cell

level FoxP3 cells can be stimulated to secrete IL-17 (Ivanov et al 2006). They suggested a

different mechanism through which inflammation can stimulate Tregs cells to secrete IL-17, and

hence reducing suppression and at the same time promoting an inflammatory milieu. They

documented flexibility of a subset of Tregs in the circulation, which are influenced by

environmental factors to exhibit dual Treg and Th17 function (Baecher-Allan et al 2009).

A study was performed to determine the contribution of cytokines that were labeled to promote

murine Th17 cells on naïve human CD4 T cells. It was found that IL-23 stimulates production of

human Th17 cells and it is the key inducer of other pro-inflammatory cytokines. These results

are significant in the pathogenesis of human autoimmunity as compared to animal models (Duerr

et al 2006). It has been observed that for CD4 T cells in human, IL-23 is an exceptionally

effective inducer of IL-22, INF-γ, and other cytokines that participate in autoimmune diseases.

The action of IL-23 is of interest, but at this point of time this cytokine seems to have diverse

effects on human CD4 T cells (Chen et al 2007).

1.17.2.11. Difference of IL-17 in humans and animals: It has been documented that the

features that guide the expression of IL-17 in human CD4 T cells are different from mice. It was

observed that IL-6 and IL-21 could not initiate IL-17 expression in both naïve and effector T

cells, and infect TGF-beta checked expression of IL-17 (Evans et al 2009). They concluded that

Th17 cells of human and mouse need different factors during differentiation. They suggested that

human Th17 cells seem to regulate innate immunity in epithelial cells as well (Wilson et al

2007).

1.17.2.12. γδ T cells and Th17: The involvement of γδ T cells and Th17 cells in a mouse model

of pulmonary inflammation and fibrosis induced by silica particles was studied. They reported an

accumulation of IL-17A and IL-22 producing T cells in experimental silicosis. They

demonstrated that the early lung inflammation had numerous neutrophils and acute tissue injury

require the production of IL-17A by γδ T lymphocytes and Th17 cells. They suggested that Th17

cells producing IL-17A are required for acute alveolitis during experimental silicosis. However,

IL-17A and IL-22 are dispensable for chronic inflammation and are not essential modulators of

34

fibroblast functions, uncontrolled tissue repair, and lung fibrosis induced by silica particles (Re-

Sandra et al 2010).

1.17.2.13. Invariant natural killer T cells: A study was conducted by using a model of

experimental autoimmune uveitis (EAU) immunized with an uveitogenic regimen of the retinal

antigen and the aim was to explore the role of invariant natural killer T (iNKT) cells in the

directive of autoimmunity to retina. It was found that once iNKT cells are activated, they protect

the animal from EAU by involving innate production of INF-γ and dampening of Th1 and Th17

effector responses. It was suggested that protective effect of iNKT cells in EAU seems to require

INF-γ and is associated with reduced adaptive INF-γ and IL-17 responses. They demonstrated

that iNKT cells can actively participate in regulating the autoimmune response to

immunologically privileged retinal antigens. The mechanism involves the induction of innate

INF-γ production through ligation of the invariant TCR and leads to inhibited development of

adaptive Th1 and Th17 responses that represent pathogenic effector mechanisms in uveitis

(Grajewski-Rafael et al 2008).

1.17.2.14. IL-17 and diseases: A study was performed on skin biopsies of psoriasis patients and

high level of IL-17, IL-23 and IL-22expression was observed. The cytokines such as IL-23, IL17

and IL-12 had been identified as over expressed in the lesions of CD. In the patients of multiple

sclerosis, brain biopsies showed high level of gene expression for IL-17 (Firestein et al 2003).

High levels of IgE have been identified in patients of hyper IgE syndrome which is a primary

immunodeficiency (Minegishi et al 2007). These patients documented various kinds of mutations

in the Stat3 gene and there were defects in Th17 cells (Ma et al 2008). As it is believed that IL-

23 is involved in the production of IL-17, therefore stopping IL-23 could be a way to manipulate

Th17 pathway. Kobayashi et al concluded the use of monoclonal antibody against p40 that is

similar to IL-12 and IL-23, which is effective for psoriasis and Crohn’s disease (Kobayashi et al

2008).

Studies in experimental models of inflammatory bowel diseases (IBD) indicated that T cell

derived cytokines are fundamental mediators of the tissue damage. In the beginning, CD and

ulcerative colitis (UC) were thought as the two perfect examples of Th1 and Th2 associated

35

diseases respectively but at the moment it is clear that CD and UC related inflammation has

increased production of cytokines by the Th17 cells (Fujino et al 2002).

In the gut Th17 cells change their cytokines production according to the stimuli they received

and they can convert into Th1 producing cells (Ivanov et al 2006). Genome-wide association

studies in IBD and on candidate genes had showed that polymorphisms of Th17-related genes,

such as Stat3 or IL-23R, often associate with IBD (Franke et al 2010, Anderson et al 2011, Glas

et al 2009). Therefore it supports the contribution of Th17 pathway in the pathogenesis IBD.

In humans, it is documented that presence of T cell clones in the intestines of IBD patients can

induce IL-17 and INF-gamma and hence it is labeled as Th1/Th17cells (Ivanov et al 2006).

Further, such dual producer cells have also been identified in EAE lesions in mice. These cells

express Th17-inducing transcription factor (ROR-γt) and Th1-stimulating transcription factor (T-

bet) (Ivanov et al 2006).

At the moment it is believed that Th1 and Th17 cells are capable of inducing autoimmunity

(Steinman et al 2008).Some of the Th17 cells present in the gut of CD patient yield both IL-17

and INF-γ (Th17/Th1) (Annunziato et al 2007). Self-reactive Th cells co-express IL-17 and IL-

22 but IL-22 seems unlikely to be involved in autoimmune pathogenesis of CNS in vivo

(Kreymborg et al 2007).

Th17 cells have been associated in the pathogenesis of several autoimmune diseases, e.g.

multiple sclerosis and rheumatoid arthritis (Chen et al 2006, Kotake et al 1999). It was

concluded that IL-17 is dispensable, at least in large part, in the pathogenesis of autoimmune

diabetes (Joseph et al 2011). Nakae et al suggested that IL-17 is essential in the development of

(CIA) through activating auto antigen specific cellular and humoral immune responses. (Nakae

et al 2003)

1.17.2.15. IL-17 and type-1 diabetes: In a study on children with type-1 diabetes (TID), the

Th17 immunity in the peripheral blood T cells was studied. They documented increased level of

IL-17 and expression of IL-17, IL-22 and retinoic acid-related orphan receptor C isoform 2.

36

Foxp3 transcripts have been observed upon T cell activation in vitro. They showed that IL-17

had harmful effects on human islet cells in vitro; it potentiated both inflammatory and pro-

apoptotic responses. Their results highlighted the contribution of IL-17 immunity in the

pathogenesis of human TID which also indicated towards probable option as treatment

(Honkanenat et al 2010). The mutual relationship between regulatory T cells and Th17 cells

suggested options to revert the function of regulatory T cells in autoimmune diseases (Miossec et

al 2009).

Serum levels of IL-17, IL-22 and INF-γ were found significantly elevated in comparison to

normal controls in the patients of psoriasis. The levels of IL-17 and IL-22 were significantly

correlated with the severity of disease while INF- γ level was not. It was suggested that psoriasis

is a condition which might have a mixture of Th1 and Th17 involvement. (Almakhzangy et al

2009).

1.17.2.16. Prognostic value of IL-17:A study was conducted to investigate the predictive value

of tumor-infiltrating IL-17 cells in human esophageal squamous cell carcinoma (OSCC).

Increased levels of tumor infiltrating IL-17 lymphocytes were linked with better survival. It was

suggested that tumor infiltrating IL-17 producing cells in OSCC may provide shielding effect in

the tumor microenvironment and this marker can be opted as a predictive tool for OSCC patients

(Lv et al 2011).

In a study on liver disease, various aspects of IL-17 and Th17 cells were looked at. It has been

observed in various liver diseases that in humans and mice Th17 cells and Th17 related

cytokines are present. Precisely pathogenic involvement of Th17 cells to liver inflammation may

differ and it depends upon the disease e.g. infectious and autoimmune disorder (Hammerich et al

2011).

Bahcet disease (BD) is a chronic, systemic, relapsing inflammatory disease that mainly featured

as recurrent uveitis, oral aphthae, genital ulcers and skin lesions. The involvement of IL-17 CD4

T cells in BD was studied and it was observed that rIL-23 stimulate creation of IL-17 by CD4 T

cells in BD patients. It was suggested that in active uveitis in BD patients, IL-23/IL-17 pathway

37

is involved. The increased levels of IL-17 were thought to be the reason for intraocular

inflammation of BD patients (Chi et al 2011).

ANCA-associated vasculitis (AAV) patients showed increased serum level of IL-17, IL-23 and

percentage of auto-antigen specific Th-17 cells and surprisingly the level remained increased in a

number of patients during convalescent stage. There was no difference in the level of INF-γ

between patients and control group. They concluded that Th17 and more precisely IL-23 are key

intermediaries of sever disease in AAV (Nogueira et al 2010).

1.17.2.17. IL-17 Foxp3 Treg cells: It has been observed that human thymus do not contain IL-

17 producing Treg cells which suggested that IL-17 Foxp3 Treg cells are produced in the

peripheral circulation (Voo et al 2009).IL-17 Treg cells are thought to contribute in antimicrobial

defense and it checks autoimmunity and inflammation (Voo et al 2009). Therefore, Treg cells

might participate towards antimicrobial innate immunity by producing IL-17. It was claimed that

these cells restrict inflammation and autoimmunity at the same time (Voo et al 2009).

It is demonstrated that IL-17 is generated simultaneously with INF-γ by the T cells that infiltrate

coronary artery cells and in this way cytokines act synergistically to build pro-inflammatory

responses in vascular smooth muscle cells (Eid at al 2009). IL-17 is a vital component of T cell

mediated skin response and they may have systemic or antagonist effects on INF-γ and TNF-α-

stimulated keratinocyte activation (Albanesi et al 1999).

1.17.2.18. Variation in the therapeutic effect of targeting IL-17: It has been documented that

there are major variances in the development of Th17 cells and also it is important that how they

function in autoimmune diseases in humans and experimental animals. It has been suggested that

there are differences in the therapeutic effects of attacking IL-17 related molecules in human

autoimmune diseases (Yamada et al 2010). It is believed that understanding differentiation

pathways of IL-17 and Th17 has improved the understanding of immunologists about chronic

tissue inflammation, in particularly where Th1 cells were thought as the reason for pathology.

The closeness of Treg and Th17 differentiation pathway is of special interest for future research

because now we can hypothesize that Th17 immune response could be more influentially

38

changed into Treg or tolerogenic reactions than Th2 or Th1 pathways. It is believed that the

knowledge about Th17 has added difficulty towards immune regulation, but simultaneously it

has assisted in explaining various themes in T cell differentiation (Schmidt-Webber et al 2007).

1.17.2.19. IL-17 and other cytokines manipulation: It has been observed that in RA patients,

TNF-α inhibitors can control the disease by limiting TNF-α, and by repairing defective

regulatory T cell functions (Nadkarni et al 2007). Suppression of IL-17 can affect acute defense

mechanisms by the involvement of neutrophils. In mouse mode, suppression of IL-17 was

associated with enhanced mortality due to bacterial lung infections (Dublin et al 2006). Further,

suppression of IL-23 pathway was also associated with the abnormalities in the cell mediated

immunity that included more severity of mycobacterial infections in the mouse (Chung et al

2003). They concluded that by combined suppression of TNF and IL-17, could assist to target

two different cell types, monocytes and T cells (Miossec et al 2009).

It has been observed that by blocking important cytokines in vivo specificallyIL-6 could result in

a drift from Th17 to the regulatory phenotype and in this way, it may persuade latency of

autoimmune disease or stop transplant rejection (Afzali et al 2007). Researchers have

documented the role of various cytokines as a treatment modality. At the same time they also

suggested the side effects of this anti-cytokine treatment such as the use of anti-TNF-alpha can

expose the patients to mycobacterium tuberculosis infection (Feldmann et al 2000, Dinarello et

al 2003)

1.17.2.20. Protective side of IL-17: Protective aspect of the IL-17 has been documented in a

study of mycobacterium tuberculosis, where IL-17 was needed to recruit CD4+ T cells; which

are basically required to produce INF-gamma to protect the lung (Khader et al 2007). Similarly,

an asthma model documented that neutralization of IL-17 enhances infiltration of eosinophil

during the effector phase of the disease, while providing recombinant IL-17 decreases airway

hyperactivity and decreases the number of eosinophil and lymphocytes in the bronchial lavage

(Steinman et al 2008, Schnyder-Candrian et al 2006). The protective side of IL-17 has also been

documented by Tato et al (2006) stating that IL-17 along with IL-25 is important for the

resistance against Klebsiella pneumonia and mycobacterium tuberculosis (Tato et al 2006).

39

It was documented that IL-17 and IL-23 affect the production of antimicrobial proteins in the

mucosal epithelium (Duerr et al 2006, Yen et al 2006). It was observed that TGF-β1 and IL-6 are

essential for the growth of Th17 cells from naïve precursors; IL-23 also seems to contribute in

IL-17 production in the mucosal tissues in response to different infectious stimuli. As compared

to Th1 cells, IL-23 and IL-17 documented a little participation in manipulating host defense

against intracellular bacteria such as mycobacterium tuberculosis, which suggested an important

contribution of Th17 lineage in host defense against extracellular pathogens (Aujla et al 2007).

In another study distinct as well as specific IL-17 and IL-23 producing CD4+ T cell subsets were

documented and it was suggested that these contribute towards human anti-mycobacterial

immune response (Scriba et al 2008).

It is believed that along with a healthy diet, discovering the predisposing genes for diabetes and

clarification of their interactions with the dietary products would hopefully reduce the incidence

of T2DM and would improve the outcome of the disease (Dedoussis et al 2006).

The role of IL-6 has been studied in different human diseases and in the development of diabetic

retinopathy (Funatsu et al 2005) but most of scientists concentrated on the determination of intra-

vitreous level of this cytokine. Although scientists did try to measure the level of IL-6 in the

serum of diabetic patients but generally they could not measure its level in the serum (Mocan et

al 2006). IL-6 has been linked with the IL-17 (Rachitskaya et al 2008) and it has been studied in

different diseases e.g. in the development of autoimmune diseases (Annunziato et al 2007). IL-

17 has also been investigated in type 1 diabetes mellitus and increased secretion and expression

of IL-17 and IL-22 in the peripheral blood T cells was documented. At the same time there are

alterations in the Treg cells which are linked with the up regulation of IL-17 cytokine. Further it

was observed that IL-17 had detrimental effects on human islet cells (Honkanenat et al 2010). In

a study it was demonstrated that IL-17+FOXP3+ Treg cells are not produced in thymus but they

are produced in the peripheral circulation. IL-17 producing Treg cells are vital for the body

defense against microbial infections and that it helps against inflammation and autoimmunity.

(Voo et al 2009).

40

2. Hypothesis

Genetic and auto-immune mechanisms are associated with type-2 diabetic retinopathy.

3. AIMS AND OBJECTIVES

The objectives of this study were to

determine Bgl II polymorphism of α2β1integrin gene as a risk factor for the development

of diabetic retinopathy

determine the levels of interleukins (IL-6 and IL-17) and

enumerate CD4+CD25+ cells (T regulatory cells) to determine their role in diabetic

retinopathy

41

4. MATERIALS AND METHODS

4.1. Study design: Analytical-observational cross-sectional study

4.2. Setting: Department of Immunology, University of Health Sciences, Lahore

4.3. Duration: The study was started in May 2009 after the approval of synopsis by the

Advanced Study and Research Board of the University.

4.4. Sample size: n=203 was selected by using the following formula

(Sample Size determination in health studies version 2.0.21 WHO)

= for 95% confidence level P = Anticipated population proportion d = Margin of error = 5% n = Sample Size Z = 1.96, p = 0.157, 1-p = 0.843 and d = 0.05

4.5. Sample size: 203subjects. They were divided into groups as follows

Diabetic retinopathy 143 subjects

Diabetic without retinopathy 30 subjects

Normal healthy control 30 subjects

4.6. Sampling technique: Simple random sampling technique for sample allocation

4.7. Sample selection:

4.7.1. Inclusion criteria

The subjects for this study were recruited in three categories i.e. healthy individuals without

diabetes (Group-I), subjects having diabetes type II without retinopathy (Group-II), and type II

diabetes patients with retinopathy from either sex between 20 – 75 years of age. Group-I subjects

were clinically healthy volunteers and they were not receiving any medication for other reasons.

42

The assessment of eye complications among the patients was made by the consultant

ophthalmologist. Group-II and Group-III subjects were receiving the treatment from their

physicians for their diabetes while Group-III subjects were receiving medications for the

management of diabetes and in addition to that they were receiving laser treatment and /or local

eye drops and/or oral medication for their eye complications. All the diabetic subjects were

recruited from the public hospitals and non-governmental organization out-patient clinics. The

socioeconomic status and level of education of these diabetic subjects was low.

4.7.2. Exclusion criteria

Subjects with a history of infection in the last two weeks and suffering from chronic infections

like TB, autoimmune disorders, etc. were excluded. In addition patients with impaired renal

functions were also excluded.

4.8. Genotyping of BglII Polymorphism

Genomic DNA was isolated from leukocytes using DNA isolation and purification kit

(Fermentas, Canada). For genotyping of Bglll polymorphism, a 600 bp DNA fragment that

contained Bglll was amplified by PCR with a Thermal cycler (BioRad). Sequences of primers are

given in Table 1. PCR conditions of 34 cycles were: the first two cycles were at 94ºC for 1 min,

and 69ºC for 1 min and 72ºC for 1 min; the second two cycles were at94ºC for 1 min, 67ºC for 1

min and 72ºC for 1 min, the remaining 30 cycles were at 94ºC for 1 min, 65ºC for 1 min and

72ºC for 1 min. Amplified DNA was digested with BglII at 37ºC for 3 hours. Resulting product

was electrophoresed on 2% agarose gel. The PCR product containing BglII (+) was cut in to

fragments of 200 bp and 400 bp whereas those containing Bglll (-) were not cut.

4.9. Analysis of cytokines

Concentrations of interleukin 6 and interleukin 17 were determined by ELISA technique.

4.10. Analysis of T regulatory cells

CD4+CD25+ Tregs were enumerated by flowcytometry using CD4 and CD25 monoclonal

antibodies from BD.

43

4.11. Blood Sample collection

Venous blood, 2-3 ml in EDTA tube (purple top) for flowcytometery and for PCR and 2 ml of

blood in plain tube (red top) or gel vial (yellow top) for cytokines by ELISA technique was

collected. Soon after the collection of blood, the sample was transported in an ice pack to the

Department of Immunology, UHS Lahore where processing of the specimen was started within

one hour of sample collection for flowcytometery.

4.12. DNA EXTRACTION

4.12.1. Protocol

Three (3) ml of whole blood was collected in EDTA tube, mixed properly and stored at -20C for

24 hours. The aliquots were thawed and labeled for DNA extraction. 500ul of whole blood was

dispensed in each aliquot, and then added 700ul of TE buffer and it was mixed properly. It was

centrifuged at 13500rpm for 10 minutes. The supernatant was discarded; the pallet at the bottom

of aliquots was dissolved. Then added 700ul of TE buffer in it and it was centrifuged again at

13500rpm for 10 minutes. The supernatant was discarded, and pallet at the bottom of aliquots

was dissolved. Then added 700ul of TE buffer in it and it was centrifuged again at 13500rpm for

10 minutes. These washing steps were repeated for 3-4 times. After removal of supernatant it

was mixed with 375ul, 3 molar sodium acetate and 25ul of 10% SDS and 10ul of proteinase-K.

All the ingredients were mixed well and incubated for overnight in a shaking water bath at 37C.

During the washing steps the pellet was dissolved after every 15 minutes for 5 to 6 times. After

overnight incubation it was mixed properly and added 4% isoamylalcoholat a 1:3 ratios i.e. 2

part of the mixture in the tube and 1 part of isoamyl alcohol. Isoamylalcohol mixture was

prepared in chloroform. Then it was mixed well and centrifuged at 13500rpm for 10 minutes.

After centrifugation two layers were formed, supernatant was collected and lower layer was

discarded. In the supernatant, an equal amount of absolute ethanol which was ice cold was

added. The solution was mixed well and DNA contents (precipitation) appeared like a small

cotton ball /thread. The mixture was left at room temperature for 10 minutes for good

precipitation of proteins, and then it was centrifuged at 13500rpm for 10 minutes. The

supernatant was discarded and the DNA was washed with 500ul of 70% ice cold ethanol. It was

centrifuged at 13500rpm for 10 minutes. During precipitation and washing steps, the DNA

threads were observed and at the end after removal of supernatant, DNA threads were settled at

44

the bottom of aliquots. Supernatant was discarded and the remaining contents of the tube were

washed with 70% ice cold ethanol once more. Once again discarded the supernatant completely

and observed the DNA threads attached/settled at the bottom of the tube. The aliquots were kept

in the incubator at 370C till it dried, then added 50ul of TE buffer, mixed and incubated the

mixture at 67 0C for 30-60 minutes. Then the samples were electrophoresed. (TE buffer, absolute

ethanol, 70% ethanol and isoamylalcohol were stored at4C).

4.12.2. dNTPs

PCR Grade highly pure dNTPs set were used. We made a 10mM dNTPs solution by adding 5µl

of dATP, dCTP, TTP and dGTC (each 100mM) to 30µl sterile double distilled water. Finally for

PCR 2µl of 10 mM dNTP mix containing 2.5mM each dNTP were used in 25µl PCR reaction

(final conc. 200 µM)

4.12.3. TE buffer

In 1 ml of 1 M TrisHCl and 200ul of 0.5 M EDTA was mixed. Its volume was made up to 100ml

with double distilled water. From this, 10 ml 1M TrisHCl was mixed with 2ml 0.5M EDTA and

its volume was made up to 1 liter and its pH was adjusted to 8.

4.12.4. Primers

The stock solution for both the primers was prepared; for Forward primer, which was 383ug

reconstituted in 574ul of low TE buffer to get concentration of 0.67ug/ul and 100 uM was added

in the primer vial. For Reverse primer which was 351ug reconstituted in 522ul of low TE buffer

to get concentration of 0.67ug/ul and 100 uM in the primer vial and stock solution for both the

primers was stored at -20C. From this stock solution, working solution of 1:10 dilution was

prepared to make 10uM or 10pMol i.e. 50ul of stock and 450ul of distilled water. For both the

primers 1:10 dilution was prepared and it was stored at -20C.

Mastermix was tapped and centrifuged for short spin. Dispensed 25ul of it in each reaction tube,

tapped and short spin in micro centrifuge, then PCR was run.

45

4.13. Electrophoresis

Three (3) ul of PCR product was mixed with 3ul of Bromophenol Blue dye. The mixture was

dispensed into the wells for electrophoresis. Voltage of 10-12V was applied for 30 minutes. PCR

product was electrophoresed for 1 hour. The results were observed under the UV light in gel

documentation system.

4.14. DNA Recipe

DNA 1ul, DNTPs 2ul, FP 1ul, RP 1ul, Taq 0.2ul, Buffer (NH4)2 SO4 2.5ul, MgCl2 3ul, dH2O

14.3ul

4.15. Polymerase Chain Reaction (PCR)

The setting for the run of mixture for PCR was 95C 4 min, 94C 30 Sec, 59C 30 Sec, 72C 1

min, 72C 10 min, 40C and the number of cycles were 35.

4.16. Restriction Fragment Length Polymorphism (RFLP)

For restriction fragment length polymorphism (RFLP) 0.2ul of Bgl II was added to 2ul of buffer

and it was mixed with 7.8ul of sterile water. Each PCR reaction product was incubated at 37C

for overnight (14-16 hours) and then the gel electrophoresis was performed by mixing 5ul of

RFLP product with dye and buffer.

After PCR, DNA product 20ul, Hind III (enzyme) 0.2ul, buffer 2ul, nuclease free water 7.8ul

which was 30ul in total was incubated for 2 hours at 37 C and then this mixture was

electrophoresed.

Table 1: Sequences of primers for the amplification of loci

Primer 1

(Nucleotide number 2789-2812)

5′-GATTTAACTTTCCCGACT-3′

Primer 2

(Nucleotide number 3346-3369)

5′-CATAGGTTTTTGGGGAACAGGTGG-3′

46

4.17 Cytokine Determination

IL-6 and IL-17 were determined using commercial (commercially available) ELISA kits

(KOMA BIOTECH INC, KOREA).

4.17.1. Kit Contents

1. Pre-coated 96 well ELISA micro plates (Two) coated with purified high affinity Rabbit

anti-Human IL-6 and IL-17.

2. Detection antibody 2.75ug (lyophilized) which is purified high affinity Rabbit anti-

Human IL-6 and IL-17 (one vial each).

3. Standard Protein (lyophilized) containing recombinant human interleukin (100 ng) one

vial each for IL-6 and IL-17.

4. Color Development Enzyme (lyophilized) containing avidin-HRP (horse radish

peroxidase) conjugate (one vial each).

5. Assay diluent containing 0.1% bovine serum albumin (BSA) in phosphate buffered saline

(PBS) 50 ml each for IL-6 and IL-17 (ready to use).

6. Color development reagent ‘A’ containing tetramethylebenzidine (TMB) solution.

7. Color development reagent ‘B’ containing hydrogen peroxide (H2O2) solution.

8. PBS powder in pouch for one liter (two pouches one each for IL-6 and IL-17).

9. Tween 20 (50% ready to use) two vials one each for IL-6 and IL-17.

10. Stop Solution containing 2M H2SO4 (ready to use).

11. Plate sealer

4.17.2. Reconstitution and Reagents Preparation

Reconstitution and reagents preparation was done on the day of analysis as follows:

1. Standard proteins (100ng)

(a). Reconstitution was done in 0.1 ml (100ul) sterile water for a concentration of 1.0

ug/ml.

(b). Standards were prepared by adding Assay Diluent (0.1% BSA in PBS) at 1:2 serial

dilutions as follows:

47

Step Dilution Method Standard conc.

Step A 2ul of Standard + 1ml of Assay Diluent 2000 pg/ml

Step B 0.5ml of Step A + 0.5ml of Assay Diluent 1000 pg/ml

Step C 0.5ml of Step B + 0.5ml of Assay Diluent 500pg/ml

Step D 0.5ml of Step C + 0.5ml of Assay Diluent 250pg/ml

Step E 0.5ml of Step D + 0.5ml of Assay Diluent 125 pg/ml

Step F 0.5ml of Step E + 0.5ml of Assay Diluent 62.5 pg/ml

Step G 0.5ml of Step F + 0.5ml of Assay Diluent 31.25 pg/ml

2. Detection antibody: 2.75ug (1 vial) of biotinylated high-affinity purified anti-Human IL-6

and IL-17.

(a). Reconstitution was done in 0.275ml sterile water for a concentration of 10ug/ml.

(b). Reconstituted detection antibody was diluted with assay diluent (0.1% BSA in PBS)

to a concentration of 0.25ug/ml (1:40 dilution)

3. Color Development Enzyme (avidin-HRP conjugate)

(a). Reconstituted in 60ul of sterile water.

(b). Reconstituted color development enzyme was diluted with assay diluent (0.1% BSA

in PBS) in 1:200 dilution.

4. Washing solution: PBS powder (1 pouch) was resolved to sterile water and made 1-liter

and then 1ml of Tween-20 (50%) was added to this solution.

5. Color Development Solution was prepared by mixing 1 volume of color development

reagent ‘A’ with 2 volumes of color development reagent ‘B’ (1:2) prior to use.

4.17.3. ELISA Protocol

Two hundred (200) ul of washing solution (1 liter PBS + 1 ml Tween20) was added to each well.

Wells were aspirated to eliminate the liquid and plates were washed three times using 300ul of

washing solution (1 liter PBS + 1 ml Tween20) per well. After the last wash, plates were

inverted to remove the residual solution and the plates were blotted on the paper towel. 100ul of

standard or sample was added to each well in duplicate except one well (blank). Plates were

covered with the plate sealer provided and they were incubated at room temperature for 2 hours.

48

Wells were aspirated to remove the liquid and each plate was washed again for 4 times with

washing solution (1 liter PBS + 1 ml Tween20) as it was done before.100ul of diluted detection

antibody (0.25ug/ml of biotinylated high-affinity purified anti-Human IL-6 or IL-17) was added

to each well. Plates were covered with the plate sealer provided and incubated at room

temperature for 2 hours. Plates were aspirated and washed 4 times with washing solution (1 liter

PBS + 1 ml Tween20) again in the same manner. 100ul of diluted color development enzyme

(1/200 diluted avidin-HRP conjugate) was added in each well. Plates were covered with the plate

sealer provided and incubated for 30 minutes at room temperature. Plates were aspirated and

washed 4 times again as before. 100ul of color development solution (1 vol. of color

development reagent ‘A’ + 2 vol. of color development reagent ‘B’) was added to each well and

incubated at room temperature for proper color development (15-25 minutes). The reaction was

stopped using 100ul of stop solution (2M H2SO4) to each well. The plates were read at 450nm

wavelength using microtiter plate reader (Bio-Rad, USA).

4.17.4. Calculation of results

The average from the duplicate readings of each standard, control and sample was obtained.

Reading of blank was subtracted from each averaged value. Standard curve was made by

reducing the data by using ELISA reader’s computer software (Micro plate Manager Version

2.2).

4.17.5. Cross reactivity

Manufacturer claimed that for IL-6, at 50ng/ml antigens (recombinant protein) such as CNTF,

CT, G-CSF, sIL-6R, IL-11, IL-12, Leptin and OSM did not exhibit cross reactivity. Similarly for

IL-17, at 50ng/ml antigens (recombinant protein) such as INF-γ, IL-8, IL-10, IL-12, IL-16, Il-

17B, IL-17D, IL-17E and IL-17F did not exhibit cross reactivity.

4.18. Flowcytometry

4.18.1. Immunostaining procedure

Samples were prepared by using lyse-wash method on whole blood. For each sample one

hundred (100) ul of anti-coagulated blood (about 1 million cells) of each subject was added into

49

2 Falcon propylene tubes (12 x 75 mm BD Falcon tubes). 20ul of each of FITC (Fluorescein

isothiocyanate) labeled anti-CD4, PE (Phycoerythrin) labeled anti-CD25, and PerCP (Peridinin-

chlorophyll-protein) labeled anti-CD45 monoclonal antibodies were added to one tube and 20ul

of isotype control to the other. All these antibodies and isotype were bought from Becton

Dickinson (BD). Antibodies were vortex before adding them to blood. The tubes were vortex and

incubated in dark at room temperature for 15 minutes. 2ml of BD FACSLyse (containing <15%

formaldehyde and <50% diethylene glycol, diluted 1:10 in deionized water immediately before

use) was added to each tube. The tubes were re-incubated in dark for 12 minutes. The tubes were

centrifuged at 250g/3200 rpm for 10 minutes and supernatant was discarded. The pellet was re-

suspended and the cells were washed twice by adding 2ml of sheath fluid, it was mixed and

centrifuged. The supernatant was discarded. The cells were re-suspended in 0.5ml of sheath fluid

with 2% paraformaldehyde and the data was acquired on flow cytometer (FACS Calibur BD

USA) within 24 hours.

4.18.2. Flowcytometry / Immunophenotyping

FACS Calibur 4-color analyzer (BD USA) was used to analyze the cells. The instrument was

calibrated and fluorescent signal compensation was performed by using CellQuest Pro software

(BD) and Calibrite beads (BD) before the samples were analyzed. The data was acquired by

using these settings (Figure 1).

CD4+ cells (FITC tagged MoA against CD4), CD25+ cells (PE tagged with MoA against CD25)

and CD45+ cells (PerCP tagged with MoA against CD45) was determined using excitation by a

15mW, 488nM, argon-ion blue laser.

50

Fig.1. Calibration and fluorescence signal compensation using Cell Quest Pro software (BD) and

Calibrite Beads. R1 (First row Left; a) indicates gate for lymphocytes. Quadrants in (b) and (c)

indicate thresholds values of double negative, single positive, and double positive cells for FITC,

PE and PerCP labeled antibodies respectively. Fluorescence intensity for FITC, PE and PerCP

dyes are represented in d, e and f (Second row) respectively.

51

Figure 2: Electronic adjustment and fluorescence signal compensation of cytometer using Cell Quest Pro software

4.19. Data Acquisition:

First of all, templates were designed for the two parameter dot-plot that represented forward

angle light scatter-side scatter (FALS-SSC), and CD45-SSC.The first dot-plot was used as an

indicator of acceptable sample preparation (Figure 2) while the second was used to identify the

lymphocyte population by avoiding contamination from different cells. In this way the

lymphocytes having CD45 brightest population but with the lowest side scatter, in the

CD45-SSC dot-plot were gated and the data for CD4+CD25+ T cells was acquired (Figure 3).

52

Figure 3: FALS-SSC two parameter dot-plot showing three populations of WBCs. Top right cluster of cells indicate polymorphs, middle cluster indicates monocytes, the red cluster indicates lymphocytes which were circumscribed and gated as R1with some degree of mixing with debris (bottom; left).

Figure 4: CD45-SSC two parameter dot-plot was drawn to separate lymphocytes from debris, these were circumscribed and 2nd gate (R2) was applied.

53

4.20. Sample analysis

T cells (CD4+CD25+) were analyzed by using the two parameters dot-plot where on X-axis it

was log FITC fluorescence (CD4) and on Y-axis it was log PE fluorescence (CD25). Cell Quest

Pro software was used. Unlike mouse, humans CD4+CD25+ T cells are not clearly discernible

from CD4+CD25- T cells. Instead, they appear as a homogenous population (Figure 4).

Figure 5: CD4-CD25 two parameter dot-plot showing that CD4+CD25+ (right column; upper portion) T cell population is not discernible from CD4+CD25- T cells (lower right). Instead these cells form a continuous population. Lower left quadrant shows double negative cells (CD4-CD25-) and in the upper left quadrant CD25+cells are present.

Therefore the following strategy was adopted. CD25 (PE) one parameter histogram was overlaid

on that for control and the boundary for the fluorescence channel was selected above which not

more than 1% of control cells were detected (Figure 5). This is how the channel was set and

below this limit all the stained cells were considered negative.

54

Figure 6: Determination of criteria for the CD25 positive cells. One parameter histograms for

isotype control (blue outline) and CD25-stained cells (red) were overlaid and the fluorescence

channel was designated such that not more than 1% of the control cells were detected above this

limit. This channel (represented as M1) was selected as a limit before that all the stained cells

were considered negative.

For determination of criteria for CD4+ cells, a different strategy was adopted as there was a clear

demarcation between negative and positive populations. The cutoff for negative and positive

populations was set at the nadir of the first peak (Figure 6). This channel was selected as a limit

below which all stained cells were considered negative.

55

Figure 7: Determination of criteria for CD4 negative and CD4 positive cells. On one parameter

histogram for CD4 stained cells, a fluorescence channel boundary was selected at the nadir of the

first peak and all cells above this channel (M1) were considered positive. Blue out-line

represents isotype control, first green peak (left) represents non-specific staining.

56

Top left; shows the dot-plot of selection of CD45 cells. Top-right shows the dot-plot of CD45 isotype control. Second row left; selection of top 2% population of CD4+CD25+ population. Second row right; isotype control of CD4CD25 cells. Third row: strategy to determine percentage of top 2% of CD4+CD25+ population.

Fig 8: Histograms showing gating strategy using isotype control and Statistics of histogram

57

Top left; shows the dot-plot of selection of CD45 cells. Top-right shows the dot-plot of CD45 isotype control. Second row left; selection of top 2% population of CD4+CD25+ population. Second row right; strategy to determine percentage of top 2% of CD4+CD25+ population


58


Top left; shows the dot-plot of selection of CD45 cells. Top-right shows the dot-plot of CD4+CD25+ isotype control. Second row left; selection of top 2% population of CD4+CD25+ population. Second row right; strategy to determine percentage of top 2% of CD4+CD25+ population.

59


Top left; shows the dot-plot of selection of CD45 cells. Top-right shows the dot-plot of CD4+CD25+ isotype control. Second row left; selection of top 2% population of CD4+CD25+ population. Second row right; strategy to determine percentage of top 2% of CD4+CD25+ population

60



61



62



63

Using these strategies, quadrants for CD4 and CD25 positive cells were defined and their

percentages were determined and then percentage of Treg cells was calculated.

4.21. Markers used for Immunophenotyping

Fluorescein isothiocyanate (FITC) tagged with MoAagainst CD4, Phycoerythrin (PE) tagged

with MoA against CD25, Peridinin-chlorophyll-protein (PerCP) tagged with MoA against CD45

were used as monoclonal antibodies.

4.22. Gating strategy to identify CD4dimCD25bright T cells

It was obtained by the protocol adopted by Hoffman et al 2000. Briefly the proposed gate from

CD4+CD25+ was defined as CD4dimCD25bright; a region that was suggested to contain

predominantly FOXP3+ T cells. Hoffman et al documented that the top 2% of the CD4+CD25+

(CD4dimCD25bright) population was FOXP3+ and had regulatory properties. An algorithm was

constructed to obtain a metric proportional to the number of FOXP3 expressing T cells on the

basis of CD4 and CD25 expression; it is the number of CD4dimCD25bright T cells in the region

that had a CD4 MFI (mean fluorescence intensity) of ≤0.9 of the MFI of CD25+CD4+ T cells.

To identify the region properly, two rectangular regions were placed on the CD25CD4 dot-plot

of CD4+ lymphocytes and they were wide enough to include the range of CD4 expression; one

region i.e. CD4+CD25+ contained all the CD25+ cells above the isotype control, and the other

region i.e. CD4dimCD252% contained the 2% cells that expressed most of the CD25. If the MFI

for CD4 of CD4dimCD252%was equal or more than CD4+CD25+, the sample might have recently

been activated, and could not be evaluated, therefore it was not considered. If the MFI for the

CD4 of CD4dimCD252% was less than the CD4 MFI of the CD4+CD25+ region, the gate of the

CD4dimCD252% was moved toward the axis until the MFI for CD4 of this region was 0.9 x the

CD4 MFI of the CD+CD25+ region. The region set by this procedure was termed

CD4dimCD25bbright.

64

4.23. REAGENTPREPARATION

4.23.1. DNA EXTRACTION

4.23.1.1. Reagents Required

1. TrisHCl (1 M) pH 8: Dissolved 15.8g of TrisHCl in distilled water and volume

was raised up to 100ml and pH was adjusted at 8 with 5M NaOH

2. 0.5 Molar EDTA: Dissolved 14.61g EDTA in distilled water and volume was

raised up to 100ml

3. TE Buffer: Took 10 ml of 1M TrisHCl + 2ml 0.5M EDTA and volume was raised

up to 1 liter with double distilled water and pH was adjusted at 8 with 5M NaOH (stored at

4C)

4. Sodium Acetate (3 M): Dissolved 24.6g of sodium acetate in distilled water and

raised its volume up to 100ml

5. SDS 10%: Dissolved 10g of sodium dodecyl sulphate in distilled water and raised

its volume up to 100ml

6. 70% Alcohol (Absolute Alcohol 100ml store at 4C ). Took 70ml of absolute alcohol

and raised its volume up to 100ml (stored at 4C).

7. Proteinase K: Dissolved 25 mg of proteinase K into 2.5ml double distilled water

(stored at -20C)

8. Isoamylalcohol: Took 4ml of isoamylalcohol and raised its volume up to 100ml

with chloroform (store at 4C)

4.23.1.2. dNTPs

10mM dNTPs solution by adding 5µ1 of dATP, dCTP, TTP and dGTC (each 100mM) to

30µl sterile double distilled water.

4.23.1.3. Working solution of dNTPs for PCR

Finally for PCR 2µ1 of 10 mM dNTP mix containing 2.5mM each dNTP were used in 25µ1 PCR reaction (final conc. 200 µM)

65

4.23.1.4. TE buffer

1 molar TrisHcl

0.5 Molar EDTA (14.61 g / 100ml)

Initial Final

1000mM (C1) 10mM (C2)

Required volume (V1) 100 ml (V2)

C1V1=C2V2

V1=C2V2/C1

V1=10 x100/1000

V1= 1ml of Tris

C1V1=C2V2

V1=C2V2/C1

V1=1x100/500

V1=0.02ml of EDTA

In 1 ml of 1 M TrisHCl, 200ul of 0.5 M EDTA was added. Its volume was raised up to 100ml

with double distilled water.

10 ml 1M TrisHCl + 2ml 0.5M EDTA, raised the volume up to 1 liter. Adjusted its pH 8.

4.23.1.5. Preparation of Master Mix for Primers

1X 9X Concentration for each Reaction

DNA 1ul 9ul 10ng

10X PCR Buffer 2.5ul 22.5ul

25mMMgCl2 1.5ul 13.5ul 1.5mM

10mMdNTPs 2ul 18ul 200uM

10uM PF 1ul 9ul 0.4uM

10uM PR 1ul 9ul 0.4uM

Taq 0.1ul 0.9ul 1 unit

DDH2O 15.9 143.1ul

Total Volume 225ul

66

4.24. ELISA IL-6 and IL-17

For the detection of human IL-6 and IL-17 diagnostic kits (KOMA BIOTECH INC,

KOREA)were used. The assays were performed according to the instructions of manufacturer.

For both assays reagents were prepared as follows

a. For IL-6 and IL-17 standard: 110ng (1 vial) of recombinant human IL-6 and IL-17 was

reconstituted in 0.11ml sterile water for a concentration of 1.0ug/ml

b. Detection antibody: 2.75ug (1 vial) of biotinylated antigen-affinity purified anti-Human

IL-6 and IL-17 was reconstituted in 0.275ml sterile water for a concentration of 10ug/ml

c. Washing solution: PBS powder (1 pouch) was resolved to sterile water and made 1-liter

and then 01ml Tween-20 (50%) was added to this solution

d. Standards were prepared by adding ‘Assay Diluent’ at 1:2 serial dilutions as follows

Step Dilution Method Standard conc.

Step A 2ul of Standard + 1ml of Assay Diluent 2000 pg/ml

Step B 0.5ml of Step A + 0.5ml of Assay Diluent 1000 pg/ml

Step C 0.5ml of Step B + 0.5ml of Assay Diluent 500pg/ml

Step D 0.5ml of Step C + 0.5ml of Assay Diluent 250pg/ml

Step E 0.5ml of Step D + 0.5ml of Assay Diluent 125 pg/ml

Step F 0.5ml of Step E + 0.5ml of Assay Diluent 62.5 pg/ml

Step G 0.5ml of Step F + 0.5ml of Assay Diluent 31.25 pg/ml

Table 2. Showing different standards and their concentrations used for the determination

of IL-6 and IL-17 cytokines in ELISA technique

e. Detection antibody: reconstituted detection antibody was diluted in assay diluent to a

concentration of 0.25ug/ml (1:40 dilution)

f. Color development enzyme: Streptavidin-HRP conjugate was diluted as 1:200 in assay

diluent

g. Color development solution: 1 volume of color development reagent A and 2 volume of

reagent B was mixed prior to use

67

100 1000

Conc. (pg/ ml)

-0.1

0

0.1Abs

orba

nce

(OD

)

S4

S1

S5

S2

S6

S3

S7

Fig. 15. IL-6 ELISA Standard Curve Report. X-axis represents different standard conc. and Y-

axis represents absorbance values. (S1= 2000 pg/ml, S2= 1000, S3= 500, S4= 250, S5= 125,

S6= 62.5 and S7= 31.25 pg/ml)

4.24.1. Statistical Analysis of IL-6

Regression type: Linear

Transformation: Linear (Conc) – Linear (Absorbance)

Axis transmission: Linear [X] – Linear [Y]

Standard Curve Abs: 0.0977 x Log 10 [Conc] = 0.234

Correlation Coefficient (R value) = 0.961

68

0 500 1000 1500 2000

Conc. (pg/ ml)

0

0.1

0.2

0.3

Abs

orba

nce

(OD

)

S1

S5

S2

S6

S3

S7

S4

Fig. 16. IL-17 ELISA Standard Curve Report. X-axis represents different standard conc. and Y-

axis represents absorbance values. (S1= 2000 pg/ml, S2= 1000, S3= 500, S4= 250, S5= 125,

S6= 62.5 pg/ml and S7= 31.25 pg/ml)

4.24.2. Statistical Analysis of IL-17

Regression type: Linear

Transformation: Linear (Conc) – Linear (Absorbance)

Axis transmission: Linear [X] – Linear [Y]

Standard Curve Abs: 0.000769 x Log10 [Conc] = 0.00452

Correlation Coefficient (R value) = 0.999

69

4.25. Data Analysis

Data was entered and analysed using SPSS 17.0. Mean + SD, frequencies and percentages were

used for qualitative variables. One way ANOVA was used to observe group mean differences.

Post Hoc Tukey test was applied to observe which group means differs from the others. Pearson

correlation test was used to observe correlation between quantitative variables. Pearson Chi-

Square test was applied to observe associations between qualitative variables. A p-value of ≤

0.05 was considered statistically significant.

70

5. Results

5.1. Demographic data of the subjects

The demographic data of the studied population is shown in Table-3. In the Group-I i.e. the

healthy subjects, included 21 (70%) males and 09 (30%) females. In the Group-II i.e. diabetic

patients who did not develop diabetic retinopathy, included 5 (16.66%) males and 25 (83.33%)

females. In the Group-III i.e. diabetic patients who had diabetic retinopathy consisted of 51

(33.55%) males and 101 (66.44%) females.

The mean SD of age was 34.66 8.78 (range 24-64) years in Group-I, 49.4 9.94 (range 27-

75) years in Group-II and 50.88 8.90 (range 20-70) years in Group-III of the studied

population.

For Group-II subjects, the range of the percentage of HbA1c was between 5.9% – 12.6% and it

was 5.2% – 15.4% in Group-III subjects.

Regarding the duration of diabetes, Group-II had 25 (11.79%) subjects whose duration of

diabetes was between 5–10 years and there were 5 (2.35%) subjects who had diabetes for more

than 10 years (2.35%). In Group-III, there were 84 (39.2%) subjects who had duration of

diabetes between 5–10 years and there were 68 (32.07%) subjects who had diabetes for more

than 10 years (Table-3).

71

Table 3: Demographic data of the subjects

Variables/Parameters Group-I

Healthy

subjects

(30)

Group-II

Diabetes without

retinopathy

(30)

Group-III

Diabetes with

retinopathy

(152)

Male n (%) 21(70) 05 (16.66) 51 (33.55)

Female n (%) 09 (30) 25 (83.33) 101 (66.44)

Age (yrs) range

mean SD

24-64

34.66 8.78

27 – 75

49.46 9.94

20-70

50.88 8.90

HbA1c (percentage) NA* 5.9 – 12.6 5.2 – 15.4

Duration of diabetes

(range)

5 – 10 years n (%) NA* 25 (11.79) 84 (39.62)

More than 10 years

(%)

NA* 05 (2.35) 68 (32.07)

*NA= not applicable

72

5.2. Different continuous variables

The mean SD of percentage of HbA1c was 8.54 2.06 (range 5.90-12.60%) in Group-II and

8.83 2.35 (range 5.20-15.40%) in Group-III. On comparison of HbA1c between the two groups

there was no significant difference

The mean SD of duration of disease was 7.76 4.14 (range 5-20) years in Group-II and 10.51

5.24 (range 2-26) years in Group-III.

5.3. Comparison of different variables among the groups

For comparison of gender distributions, ANOVA test was applied and it was observed that there

was a statistically significant difference among the three groups (p-value=0.0029).Then to

determine the differences within the groups, Post Hoch Tucky Test was applied for comparison

of gender distribution. Higher percentage of females were detected in Group-II (83%) and

Group-III (66%) compared to Group-I (30%) (p-value<0.0001in each). On comparison of gender

distribution between Group-II and Group-III, there was no significant difference.

The mean SD of age of the subjects was 34.66 8.78 (range 24-64) years in Group-I, 49.4

9.94 (range 27-75) years in Group-II and 50.88 8.90 (range 20-70) years in Group-III of the

studied population. On comparison of age of the subjects, there was significant difference among

the three groups(p-value<0.0001). On comparison of age of the subjects, higher age of the

subjects was found in Group-II (49.46 ± 9.94 yrs) and in Group-III (50.88 ± 8.90 yrs) compared

to Group-I (34.66 ± 8.78 yrs) (p-value<0.0001in each) while there was no significant difference

in the age of the subject between Group-II and group-III.

In Group-II, the mean duration of diabetes was 7.76 4.14 (range 5–20) years and 10.51 5.24

(range 2–26) years in Group-III. On comparison of duration of diabetes, longer duration of

disease was found in Group-III (10yrs) compared to Group-II (7yrs) (p-value = 0.0073).

73

Table 4.Comparisons of different variables in different groups

Variable Group-I (n=30)

Group-II (n=30)

Group-III (n=152)

p-value

Gender Male (n, %)

Female (n, %)

21 (70) 9 (30)

5 (16.6)

25 (83.33)

51 (33.55)

101 (66.44)

0.0029*1

<0.0001*2 <0.0001*3 0.0868 4

Age (yrs) min max Mean ± SD

24.0 64.034.66 ± 8.78

27.0 75.049.46 ± 9.94

20.0 75.0 50.88 ± 8.90

<0.0001*1 <0.0001*2 <0.001*3 0.4365 4

Duration (yrs) min max Mean ± SD

NA# 5.0 20.07.76 ± 4.14

2.0 26.0 10.51 ± 5.24

0.0073*4

HbA1C (bands) min max Mean ± SD

NA# 5.90 12.608.54 ± 2.06

5.20 15.40 8.83 ± 2.35

0.60444

*Statistically significant # NA=not applicable 1Comparison among three groups 2 Comparison between group-I and group-II 3 Comparison between group-I and group-III 4 Comparison between group-II and group-III

74

5.4. Frequency of BglII Polymorphism in Group-I, Group-II and Group-III by PCR/RFLP

The frequency of Bgl II polymorphism i.e. disease associated homozygous positive (++), disease

associated heterozygous positive (+-) and non-disease associated homozygous negative (--) for

the allele of α2β1integrin gene was determined in all the studied population.

75

Fig 17. Showing ladder and BglII polymorphism of different subjects

Sample # 1, 3 are negative for Bgl II polymorphism

Sample # 2, 4, and 5 are heterozygous for Bgl II polymorphism

600bp

400bp

200bp

76

Fig 18. Showing BglII polymorphism of different subjects

Sample # 1, 5, 7, 8, and 10 are negative for Bgl II polymorphism

Sample # 2, 3, 4, 11, and 12 are heterozygous for Bgl II polymorphism

Sample # 6, and 9 are homozygous for Bgl II polymorphism

400

200

+/+ ‐/‐ +/‐ +/‐ ‐/‐ +/+ ‐/‐ ‐/‐+/‐ +/‐ +/‐

1 2 3 4 5 6 7 8 9 10 11 12

77

Fig 19. Showing ladder and Bgl-II polymorphism of different subjects

Sample # 1, 2, 3, 4, 6, 7, 10, 11, 12, 16, 25, 31, 35, 37, 38, and 40 are negative for Bgl II

polymorphism

Sample # 5, 8, 9, 13, 14, 15, 17, 18, 19, 20, 21, 23, 24, 26, 27, 28, 29, 32, 33, 34, 41, and 42 are

heterozygous for Bgl II polymorphism

Sample # 30, 36, and 39 are homozygous for Bgl II polymorphism

‐/‐‐

‐/‐

‐/‐

‐/‐

+/‐

‐/‐

‐/‐

+/‐

+/‐

‐/‐

‐/‐

+/‐

‐/‐

+/‐

+/‐

‐/‐

+/‐

+/‐

+/‐

+/‐

‐/‐

+/‐

+/‐

+/‐

‐/‐

+/‐

+/‐

+/‐

+/‐

+/+

‐/‐

+/‐

+/‐

+/‐

‐/‐

+/+

‐/‐

‐/‐

+/+

‐/‐

+/‐

+/‐

600400 200

200

400 600

1 2 3 4 5 6 7 8 9 10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

dder

78

Fig 20. Showing ladder and Bgl-II polymorphism of different subjects

Sample # 4, 7, 8, 10, 13, 14, (upper row) and 1, and 4 (lower row) are negative for Bgl II

polymorphism

Sample # 1, 2, 3, 5, 6, 9, 10, 11, 12, 15, 16, 17, 18 (upper row) and 2, and 5 (lower row) are

heterozygous for Bgl II polymorphism

79

In Group-I, none of the subjects had ++ polymorphism, there were 21 (70%) subjects with + -

polymorphism and 9 (30%) subjects had - - polymorphism. In Group-II, there were 4 (13.3%)

subjects who had ++ polymorphism, 16 (53.3%) subjects had + - polymorphism and 10 (33.33%)

subjects had - - polymorphism. In Group-III, 29 (19.1%) subjects had ++ polymorphism, 67

(44.7%) subjects had + - polymorphism and 56 (36.18%) subjects had - - polymorphism.

In total, 33 (15.6%) subjects had + + polymorphism, 104 (49.05%) had + - polymorphism and 75

(34.90%) had - - polymorphism.

On comparison of Bgl I polymorphism between Group-I and Group-III, higher percentage of ++

polymorphism was found in Group-III (19%) compared to Group-I (0%) (p-value=0.003). While

comparing Bgl II polymorphism among the three groups, between Group-I and Group-II and

between Group-II and Group-III, there was no significant difference (Table 7).

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Table 5. Frequency of Bgl-II Polymorphism in Group-I, Group-II and Group-III by PCR

Group Bgl-II Polymorphism Total

p-value ++

n (%) + -

N (%) - -

n (%)

Group I (Healthy subjects)

0 (0.00) 21 (70.0) 9 (30.0) 30 0.3971 0.0962 0.003*3 0.6044

Group II (Diabetic without

retinopathy)

4 (13.3) 16 (53.3) 10 (33.33) 30

Group III (Diabetic with retinopathy)

29 (19.1) 67 (44.7) 56 (36.18) 152

Total 33 (15.6) 104 (49.05) 75 (34.90) 212

The groups were compared using Chi-square test. There was statistically significant difference

between Group-I and Group-III (p-value = 0.003).

* Statistically significant 1 comparing group-I, group-II and group-III 2 comparing group-I and group-II 3 comparing group-I and group-III 4 comparing group-II and group-III

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5.5. Cytokines Assessment

The mean SD of level of IL-6 was 1331.98 306.41 (range 728.66-1680.58) pg/ml in Group-I,

1341.78 294.74 (range 750.95-1666.73) pg/ml in Group-II, and 718.66 614.02 (range 10.00-

2000.0) in Group-III.

The highest level of IL-6 was found in Group-II, followed by Group-I and then Group-III. For

the comparison of IL-6 levels among the three groups, ANOVA test was applied and it was

observed that there was a statistically significant difference (p-value<0.0001). Then to determine

the differences of level of IL-6 within the groups, Post Hoch Tucky Test was applied. Higher

level of IL-6 was found in Group-I (1331pg/ml±306) and in Group-II (1341pg/ml±294)

compared to Group-III (718pg/ml±614) (p-value<0.0001 in each). On comparison of IL-6

between Group-I and Group-II, there was no significant difference in the level of IL-6.

The mean SD of level of IL-17 was 718.05 756.55 (range 44.37-2000) pg/ml in Group-I,

415.01 483.40 (range 85.67-1743.64) pg/ml in Group-II, and 375.95 468.19 (range 38.47-

2000) pg/ml in Group-III.

The highest level of IL-17 was detected in Group-I, followed by Group-II and then Group-III.

On comparison of IL-17 levels, significant difference was found in the level of IL-17 among the

three groups (p-value=0.0026) and higher level of IL-17 was found in Group-I (718pg/ml±756)

compared to Group-III (375pg/ml±468)(p-value=0.0014). On comparison of level of IL-17

between Group-I and Group-II and between Group-II and Group-III, there was no statistically

significant difference (Table 6).

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Table 6. Comparison of variables (Cytokines) in different groups


Group-II (n=30)

Group-III (n=152)

p-value

IL-6 (pg/ml) min max Mean ± SD

728.66 1680.58 1331.98 ± 306.41

750.95 1666.731341.78 ± 294.74

10.00 20000 718.66 ± 614.02

<0.0001*1

<0.4255 2 <0.0001*3 <0.0001*4

IL-17 (pg/ml) min max Mean ± SD

44.37 2000718.05 ± 756.55

85.67 1743.64415.01 ± 483.40

38.47 2000 375.95 ± 468.19

0.0026*1

0.1456 2 0.0014*3 0.67914

*Statistically significant 1 Comparison among three groups 2 Comparison between group-I and group-II 3 Comparison between group-I and group-III 4 Comparison between group-II and group-III

83

5.6. Data of Assessment of Cells by Flow cytometer

The mean SD of percentage of CD4+CD25+cells was 14.53 4.84 (range 7.08-25.64) in Group-

I, 14.68 6.21 (range 1.60-27.55) in Group-II and 16.47 6.56 (range 2.14-31.54) in Group-III.

On comparison there was no statistically significant difference among the three groups.

From the CD4+CD25+ cells, the percentage of T-reg cells was calculated. The meanSD of

percentage of T-reg cells was 2.910.4 (range 2.28-4.40) in Group-I, 3.070.43 (range 2.36-

4.02) in Group-II and 2.880.38 (range 2.23-4.72) in Group-III.

On comparison of Treg cells, higher percentage of Treg cells was found in Group-II (3.07%)

compared to Group-III (2.88%) (p-value=0.0150). There was no significant difference in the

percentage of Treg cells among the three groups, between Group-I and Group-II and between

Group-I and Group-III (Table 7).

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Table 7. Comparison of CD4CD25 T cells and Treg cells (by Flow cytometer) among different

groups


Group-II (n=30)

Group-III (n=152)

p-value

CD4CD25 (%) min max

Mean ± SD

7.08 25.64

14.53

1.60 27.55

14.68

2.14 31.54

16.47

0.06751

0.8374 2 0.1272 3 0.1705 4

T-regs (%) min max Mean ± SD

2.28 - 4.40 2.91 ± 0.04

2.36 - 4.02 3.07 ± 0.43

2.23 - 4.72 2.88 ± 0.38

0.24341

0.5383 2 0.6643 3 0.0150*4

*Statistically significant 1 Comparison among three groups 2 Comparison between group-I and group-II 3 Comparison between group-I and group-III 4 Comparison between group-II and group-III

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5.7. Logistic Regression Model for Group-II and Group-III

Logistic regression model was applied to determine the associations among various variables

(Table-8).

There was statistically significant difference in the percentages of T-reg cells and the level of IL-

6 (p-values=0.039, 0.009) respectively. On comparison of the number of CD4+CD25+cells p-

value was 0.05 while for rest of the parameters there was no statistically significant difference.

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Table 8. Logistic Regression Model for Group-II and Group-III

Variable Degree of

Freedom (DF)

Estimate Standard Error

Chi-Square p-value

Age 1 0.0004 0.0008 0.21 0.644 Duration 1 0.0019 0.0015 1.62 0.203 HbA1C 1 0.0006 0.0034 0.04 0.847

CD4CD25 1 0.0022 0.0011 3.59 0.058 T-regs 1 -0.0419 0.0204 4.24 0.039* IL-6 1 -0.0000 0.0000 6.74 0.009* IL-17 1 0.0000 0.0000 0.87 0.350

Frequency of Bgl-II polymorphism

1 -0.0011 0.0106 0.01 0.9199

*Statistically significant

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5.8. Logistic Regression Model for Group-I and Group-III

Age, percentages of CD4+CD25+cells, and the level of IL-6 (p-values <0.0001, 0.0044, 0.0054)

respectively were significant predictors between Group-I and Group-III. The rest of the variables

were not statistically significant (Table 9).

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Table 9. Logistic Regression Model for Group-I and Group-III

Variable Degree of

Freedom (DF)Estimate Chi-

Square Standard

Error p-value

Age 1 0.0174 42.93 0.0027 <0.0001*CD4CD25 1 0.0099 8.12 0.0035 0.0044*

T-regs 1 0.0383 0.40 0.0603 0.5249 IL-6 1 -0.0001 7.74 0.0000 0.0054* IL-17 1 -0.0001 2.84 0.0000 0.0921

Frequency of Bgl-II polymorphism

1 -0.0011 0.12 0.0112 0.7333

*Statistically significant

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6. Discussion

The present study was carried out on 212 subjects that included healthy, diabetic without

retinopathy and diabetic with retinopathy subjects. The study included both male and female

subjects but the percentage of female diabetic patients was higher as compared to male diabetic

patients. On comparison between gender distribution there was statistically significant difference

among the groups, between Group-I and Group-II, and between Group-I and Group-III (p-

value=0.0029, <0.0001, <0.0001) respectively but there was no statistically significant difference

between Group-II and Group-III (p-value=0.0868). The possible explanation for this non-

significant value for gender distribution is that in both the groups percentage of female patients

was more as compared to male patients.

The percentage of male and female included in this study is in agreement with the study of

Akram et al (2011), who determined the prevalence of peripheral arterial disease in type-II

diabetes mellitus. In their study, among 830 patients, males were 49% while females included in

the study were 51%. Similarly regarding the percentage of patients studied in this work there is

an agreement with the study reported by Chhutto et al (2009) where among 350 patients there

were 35.1% males and 64.9% were females. In the study of Ahmadani et al (2008) the

percentage of female patients was 56.3% while for male patients it was 43.7%, which is also

very close to the percentage of subjects in the current study. The current study is also in

agreement with the study of Jamal-u-Din et al (2006), who included a total of 192 patients that

consisted of 43.5% males and 56.5% females. They determined the prevalence of diabetic

retinopathy among individuals screened positive for diabetes in five community-based eye

camps in northern Karachi, Pakistan. The current study is similar to the study conducted by Tam

et al 2008, because they included females (59.6%) and males (40.4) whereas the current study

had females (63.67%) and males (36.32%). They determined incidence and progression of

diabetic retinopathy in Hong Kong Chinese with type 2 diabetes mellitus. Although the

prevalence of diabetes has been reported more in men as compared to females, however impaired

glucose tolerance was higher among females as compared to males (Qidwai et al 2010, Shera et

al 2007).

90

Similarly, the findings of Khan et al (2007) are different from ours study as they documented the

mean prevalence of diabetes mellitus as 1.77% and the higher prevalence of diabetes in males

(1.01%) than females (0.76%) in Mirpur and Kotli districts of Azad Jammu and Kashmir,

Pakistan whereas in the current study there were more females as compared to males. Regarding

the median age of the subjects the study of Zhang et al (2010) is in partial agreement with the

current study because they included 1006 subjects of 40 years of age as the current study

included. They documented prevalence of diabetic retinopathy in the United Sates during 2005-

2008 that consisted of 504 males and 502 females. In the literature, there are different reports

about gender distribution of diabetes prevalence, but majority of the studies documented that

diabetes is more prevalent in females as compare to males and the current study is in agreement

with them because there were more females as compare to males in this study.

In the current study, highest meanSD of age was detected in Group-III (508.90yrs), followed

by Group-II (499.94yrs) and then Group-I (348.78yrs). On comparison among the three

groups, there was significant difference in the age (p-value<0.0001). Higher meanSD of age

was observed in Group-II (499.94yrs) as compared to Group-I (348.78yrs) (p-value<0.0001)

and higher meanSD of age was observed in Group-III (508.90yrs) as compared to Group-I

(348.78yrs) (p-value<0.0001). There was no significant difference between the meanSD of

age of Group-II and Group-III. The possible explanation for no difference in the meanSD of

age range could be that both the groups had diabetic patients and diabetic retinopathy could be

due to certain other factors e.g. genetics and environmental factors that need to be investigated in

future studies.

Regarding the age distribution our study is in close agreement with the study of Chhutto et al

(2009), in which the age range for the diabetic patients was between 15 - 65 years. The study of

Ahmadani et al (2008) is also in agreement with our study because they set the lower age of 18

years for the diabetic patients and the mean age of the diabetic patients was 49.9 10.8. The

current study is in agreement with the study of Shaw et al (2010) because they selected the

subjects between 20 - 80 years for global estimate of the prevalence of diabetes for 2010 and

2030 and the subjects of the current study were also between 20 - 75 years of age. Similarly,

Yang et al (2010) and Wild et al (2004) also set the lower age of the subjects as 20 years to

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determine the prevalence of diabetes among men and women in China and global prevalence of

diabetes respectively and it is the same in the current study. Similarly the current study is close to

the study conducted by Tam et al 2008, because they included diabetic subjects between 20 - 77

years of age. They determined incidence and progression of diabetic retinopathy in Hong Kong

Chinese with type 2 diabetes mellitus. However the study of Akram et al (2011) is not in

agreement with the current study because they set the lower limit of age as 40 years for the

diabetic patients while for the maximum age they did not set the age limit. The patients included

in the study by Zhang et al (2010) were between 58.9 - 62.9 years.

Although the exact reason for the development of diabetic retinopathy is not known as described

previously that age factor does not play a role between the diabetic patients, however it can be

concluded that age of the subjects play a role in the development of diabetes and later on along

with the genetic and environmental factors, diabetic complications such as retinopathy may

develop (Anonymous et al 2000, Silverman et al 1995).

On comparison of percentage of HbA1c between the Group-II and Group-III subjects, there was

no significant difference. In the literature, there are different opinions about relevance of HbA1c

with diabetic complications. Ahmadani et al (2008) is in agreement with the current study, as

they determined the percentage of HbA1c among the hypertensive patients with type-2 diabetes

with macro albuminuria, micro albuminuria and normal subjects and they observed the level of

HbA1c as 9.32 2.14%. In this study there was no significant difference in the percentage of

HbA1c. Similarly the current study is in agreement with the study of Tam et al (2008) who

determined the incidence and progression of diabetic retinopathy in Hong Kong Chinese with

type 2 diabetes mellitus and they documented the percentage of HbA1c as 8.1 1.5% while the

current study determined the percentage of HbA1c as 8.54% 2.06 and 8.83% 2.35 in the

Group-II and Group-III respectively.

The percent of HbA1c among the patients studied by Zhang et al (2010) was between 6.8% and

8.1% and it is not in agreement with the current study because they determined statistically

significant difference in the percentage of HbA1c among the diabetic patients with retinopathy

and those without retinopathy. Although the findings of the current study are not similar to the

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study of Yang et al (2010) who determined the prevalence of diabetes among men and women in

China and they inferred significant difference (p-value=0.01) in the level of glucose between

male and female subjects but the current study should not be compared with that because they

estimated the mean fasting glucose level as 95.6 mg/dl and 94.1 mg/dl in male and female

patients respectively.

In the current study almost similar level of HbA1c in both the diabetic groups reflects poor

diabetes control on part of the subjects. The reason for this non-significant value for the

percentage of HbA1c, in the current study, could be that both the groups had diabetic patients.

All the diabetic patients included in this study, had their disease for a period of more than 5-

years, and they were recruited from the public hospital/non-governmental organizations.

Majority of these patients were from the low socio-economic background and their education

level was not very high. Education and socioeconomic status has already been associated with

the increased prevalence of diabetes (Seeman et al 2008, Yan et al 2006), therefore the probable

reasons for the inefficient control of diabetes in the current study could be their low education

level and poor socioeconomic background.

Regarding the duration of diabetes, the results of the current study is in agreement with the study

of Ahmadani et al (2008). They included diabetic patients who had diabetes for 9.32 6.87 years

duration, which is similar to the duration of diabetes in the current study. They conducted a study

to determine the prevalence of micro-albuminuria in hypertensive patients with type-2 diabetes

in Pakistan. Similarly, the current study is in agreement with the study reported by Zhang et al

(2010). They also included the diabetic patients having diabetes between 6.5 years to 16.5 years

which is not different from the period of diabetes in the current study. They conducted this study

to document the prevalence of diabetic retinopathy in the United States from 2005 to 2008.

The current study is not in agreement with the study of Jamal-u-Din et al (2006), because they

included the subjects with newly diagnosed diabetes and diabetes of up to 15 years. They

determined prevalence of diabetic retinopathy among individuals screened positive for diabetes

in five community-based eye camps in northern Karachi Pakistan. Similarly the current study is

in partial agreement with the study conducted by Tam et al(2008), because they included

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subjects having diabetes for the duration of 8.8 6.1 years while in the current study the duration

of diabetes was 7.76 4.14 in Group-II and 10.51 5.24 years in Group-III. Tam et al (2008)

determined incidence and progression of diabetic retinopathy in Hong Kong Chinese with type 2

diabetes mellitus.

Regarding the selection of the diabetic subjects for the current study i.e. the duration of their

disease is generally in agreement with the majority of studies in the literature which explains that

the duration of disease plays a role in development of diabetic retinopathy. The possible

explanation for the significance of duration of diabetes could be that along with other factors,

length of disease could play a role in the development of diabetic retinopathy.

In the current study, on comparison of Bgl-II polymorphism i.e. homozygous disease associated

(++), heterozygous disease associated (+-) and homozygous for not disease associated (- -), it

was found that there was difference in Group-I and Group-III. In Group-I the Bgl-II

polymorphism was 0 (+ +), 70% (+ -), and 30% (- -) whereas in Group-III this polymorphism

was 15% (+ +), 49% (+ -), and 34% (- -) (p-value=0.003). On comparison among the three

groups there was no difference and similarly there was no difference between Group-I and

Group-II and between Group-II and Group-III.

There are studies in the literature whose findings are in agreement with the current study such as

Matsubara et al (2000) claimed to be the first one to demonstrate an association between the

BglII polymorphism of subunit of 2β1 integrin and diabetic retinopathy among patients with

type 2 diabetes mellitus in Japanese population. Matsubara et al (2000) documented that Bgl II

(+/+, +/-) genotypes increased the risk of retinopathy and nephropathy. The researcher also

suggested that patients with the BglII (+/-, +/+) genotype might benefit more from anti-platelet

therapies. (Matsubara et al 2000).

Similarly, Pavkovic et al (2010) studied polymorphism in GP Ia gene and suggested that it is

associated with variations in platelet 2β1 expression levels. Platelets from individuals with

807T allele express higher levels of 2β1 whereas individuals with 807C exhibit a lower density

of 2β1 integrin. High levels of GP Ia/IIa only depend on the presence of the 807T allele and

94

heterozygous individuals express almost similar number of GP Ia copies as individuals

homozygous for 807T. Platelets derived from 807T donors adhere significantly faster than

platelets from 807C donors.

In the current study BglII polymorphism has been observed between the normal healthy control

group and the diabetic retinopathy subjects. Therefore along with other factor, BglII

polymorphism could have been one of the factors responsible for the development of diabetic

retinopathy. Petrovic et al (2003) determined a significantly higher frequency of the Bgl II (+/+)

genotype of the gene polymorphism of the 2β1 integrin gene in patients with diabetic

retinopathy as compared to patients without diabetic retinopathy. The Bgl II (+/+) genotype of

the gene polymorphism of 2β1 integrin gene, age at the onset of diabetes, duration of diabetes,

and insulin therapy were independent risk factor for diabetic retinopathy in Caucasians with

type-2 diabetes. Tsai et al (2001) on the other hand tried to find out an association between Bgl II

genotype polymorphism in diabetic nephropathy in the Chinese population of type-2 diabetes but

he could not succeed. Since in the current study, on comparison of BglII polymorphism in

Group-I and Group-III has been observed, therefore this study suggests that the BglII

polymorphism may have contributed towards the development of diabetic retinopathy in the

studied population.

In the current study the polymorphism of BglII was determined by PCR/RFLP (Polymerase

chain reaction/Restriction fragment length polymorphism). This technique has been

recommended as the method of choice by Stevens et al (1999) who mapped Bgl II polymorphism

to intron C and developed a PCR-RFLP method to genotype individuals. The researcher

suggested PCR/RFLP based assay for the BglII polymorphism for high throughput typing in

association studies.

On comparison of IL-6, highest level of IL-6 was observed in Group-II, followed by Group-I and

then Group-III, there was significant difference among the three groups (p-value<0.0001). The

higher level of IL-6 was observed in Group-I (1331pg/ml) and in Group-II (1341pg/ml compared

to Group-III (718pg/ml) (p-value<0.0001 in each). It showed that the levels of IL-6 were high in

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the control group and in diabetic patients who did not have retinopathy compared to diabetic

patients with retinopathy.

Most of the studies that have been performed to evaluate the role of IL-6 in the development of

ophthalmic complications are performed to determination the level of IL-6 in the vitreous fluid

and majority of them have emphasized the involvement of this cytokine in the development of

eye complications. Mysliwec et al (2008) determined the level of IL-6 in the diabetic

retinopathy patients. They included 202 children with diabetes mellitus type-I and grouped them

into two. They observed higher levels of vitreous IL-6 in Group-I and they were able to establish

a relationship of level of IL-6 with the retinopathy. Unlike Mysliwec et al (2008), the current

study determined the level of IL-6 in the serum, and could not determine high levels of IL-6 in

the diabetic patients of retinopathy. Mocan et al (2006) performed a study to elucidate the

possible role of IL-6 in the pathogenesis of proliferative diabetic retinopathy. They documented

significantly higher vitreous level of IL-6 in patients with proliferative diabetic retinopathy

compared to control group however the serum level of IL-6 was below the lower detection limit

in both patients and controls. They suggested that IL-6 may have a role in the pathogenesis of

retinal neo-vascularization. Its intra-vitreous levels appear to be independent of both serum IL-6

levels and the clinical and metabolic parameters of the study. The findings of the current study

indicate that although IL-6 being an inflammatory cytokine could be blamed for different stages

of diabetic retinopathy but in the subjects with fully developed diabetic retinopathy the level of

IL-6 could be decreased, if they are getting treatment for the diabetes and for their eye

manifestations.

The relationship between advanced glycation end products (AGEs) and IL-6 in the development

of diabetic retinopathy was studied by Nakamura et al (2003). They included 62-patients of

proliferative diabetic retinopathy and 50-non diabetic controls. They documented significantly

higher level of IL-6 in the vitreous of patients with proliferative diabetic retinopathy (PDR) as

compared with the controls. Level of IL-6 was higher in the vitreous as compared to serum level

and there was no correlation between these two levels of IL-6. They suggested that increased

formation of AGEs in the vitreous may be involved in the development of diabetic retinopathy

by inducing IL-6 from retinal Muller cells. Although they showed the involvement of IL-6 in

96

diabetic retinopathy but again it was on the basis of IL-6 level in the vitreous fluid which is

different from the current study because we determined the level of IL-6 in the serum.

A further study measured concentration of cytokines including IL-6 in vitreous and serum from

47 patients with PDR and 21 patients with vitreous non-inflammatory retinopathy patients

(Yuuki et al 2001). They suggested higher IL-6 concentration in vitreous fluid of proliferative

diabetic retinopathy patients as compared to non-inflammatory retinopathy patients. In the serum

there was no difference in the levels of IL-6 between proliferative diabetic retinopathy and non-

inflammatory patients. Unlike their findings, in my study, we were able to determine the level of

IL-6 in the serum of patients of diabetic retinopathy, diabetic patients without retinopathy and

normal healthy controls. The probable reason could be subclinical infection in healthy

individuals and in diabetic without retinopathy whereas diabetic subjects with retinopathy were

being more aggressively treated and therefore, the level of IL-6 was low in this group of subjects.

A mouse experimental autoimmune uveitis (EAU) model was created in which researcher

investigated the role of IL-6 in the formation of refractory ocular inflammation (Yoshimura et al

2009). They found significantly increased level of IL-6 in the vitreous of refractory/chronic

uveitis as compared to control group. They concluded that IL-6 is responsible for causing ocular

inflammation, and it is at least partially due to IL-6 dependent Th17 differentiation. They

suggested IL-6 involvement in the ophthalmic complications whereas in the current study

different level of IL-6 has been observed in the serum of different groups of the study. The serum

level of IL-6 may not be the true reflection of eye complications such as diabetic retinopathy and

the level of IL-6 may be different in the vitreous fluid compared to serum level.

The role of IL-6 in proliferative vitreo-retinopathy (PVR) as compared to retinal detachment

patients was documented by Limb et al 1991. Norose et al 1994 suggested participation of IL-6

as an inflammatory mediator in Vogt-Koyanagi-Harada (VKH) disease. Ongkosuwito et al 1998

documented higher level of IL-6 in the ocular fluid samples from patients with uveitis. Most of

the researchers have documented the higher levels of IL-6 in the vitreous fluid of various eye

diseases whereas in the current study the determination of IL-6 has been performed in the serum

of the diabetic patients and normal healthy controls.

97

The first study regarding the role of IL-6 as an inflammatory mediator in uveitis documented

higher levels of intraocular IL-6 in the patients of uveitis but the serum level of IL-6 was not

different in patient and control groups (Murray et al1990). It is dissimilar from the findings of

the current study because here different levels of IL-6 were detected in the serum of three

groups, which could not be detected by Murray et al. Dongancy et al 2002 determined the level

of certain cytokines including IL-6 with stages of diabetic retinopathy. In their study the level of

IL-6 was below the detection limit in both the diabetic patients and controls. They further

claimed that IL-6 was raised in poorly controlled diabetic patients. It is again unlike with the

findings of the current study because various levels of IL-6 in diabetic patients, diabetic patients

with retinopathy and healthy controls were detected but the level of IL-6 was low in diabetic

retinopathy patients as compared to diabetic without retinopathy and control group. The lowest

level of IL-6 in diabetic with retinopathy subjects as compared to the other two groups could be

due to the treatment which these patients were receiving as they were being treated with

laser/local eye drops along with their regular medications for the control of diabetes.

IL-6 levels decline after normalization of plasma glucose (Esposito et al 2002). Ohta et al 2000

determined the immunosuppressive status of aqueous humor (AqH) from mouse eyes affected

with endotoxin induced uveitis (EIU) and identified the relevant cytokines responsible for

immune modulatory activity with EIU. They documented that lipopolysaccharide (LPS) induced

intraocular inflammation is associated with local production of IL-6. The researcher suggested

that suppression of intraocular synthesis of IL-6 may reduce inflammation and restore ocular

immune privilege. In the current study patients of diabetic retinopathy were getting treatment for

their eye complications that could have been the reason for their low IL-6 level.

The role of IL-6 was investigated by the rejection process in sub retinal space and the use of IL-6

monitoring for a possible early sign of rejection after transplantation of allogeneic retinal

pigment epithelial (RPE) cells (Enzmann et al 2000). Unlike the current study, Enzmann et al

(2000) conclude that the difference in the level of serum IL-6 was not statistically different

between control and experimental models but this difference was significant in the intra-vitreous

fluid. Similarly, Kauffmann et al (1994) measured the level of IL-6 and other cytokines in the

vitreous of patients of proliferative vitreo-retinopathy (PVR), PDR, vitreous hemorrhage, and

98

macular pucker. The researchers found highest level of IL-6 in the vitreous of PVR patients and

it was correlated with the disease activity. In the PDR group the level of IL-6 was either below

the detection limit or was low as compared to PVR group. Rosenbaum et al (1998) used IL-6

deficient mice to test the hypothesis that IL-6 contributes to the development of endotoxin

induced uveitis and found out that IL-6 was not the sole agent to induce uveitis in mice. They

suggested that IL-6 was not necessary for the development of uveitis subsequent to intra-vitreous

injection of endotoxin in mice.

Most of the researchers have concluded the involvement of IL-6 in various eye diseases and they

were able to detect IL-6 in the vitreous fluid of the eye but they did not detect IL-6 in the serum

whereas the current study focused on the determination of IL-6 in the serum of different groups.

In the current study various levels of IL-6 were detected in different groups and the level of IL-6

was decreased in the diabetic retinopathy subjects as compared to the two other groups. The

probable explanation for the low IL-6 levels in Group-II and Group-III compared to Group-I,

could be that Group-II and Group-III were receiving treatment for their diabetes as compared to

Group-I and Esposito et al (2002) have documented that level of IL-6 decreases after

normalization of serum glucose. Further, since all the patients of Group-III were receiving the

treatment for their eye complications i.e., either they were getting laser treatment for the eye or

some were on medications while some were on both kind of treatment. Therefore one of the

possibilities for the low level of IL-6 in the serum of diabetic retinopathy patients could be due to

their treatment of eye complications which are likely to reduce the inflammation in general and

of the eye in particular because Ohta et al (2000) also documented that suppression of IL-6 can

reduce inflammation as well.

Further, the protective aspect of the IL-6 genotype polymorphism has been highlighted in

retinopathy and nephropathy of type 1 diabetes mellitus patients. The researchers documented -

174GG IL-6 polymorphism as protected from late diabetic complications (Mysliwska et al 2009,

Hermann et al 2005). The same polymorphism of IL-6 has also been studied by other researchers

and they have the similar observation. They found elevated level of serum IL-6 and its

association with the raised insulin levels at fasting and after meals (Andreozzi et al 2006). The

protective aspect of Il-6 was confirmed in pre-diabetic condition by using transgenic non-obese

99

diabetic mouse (NOD). The NOD mouse over express human IL-6 cytokine and these animals

has decreased fasting levels of glucose with the delayed onset of disease i.e. diabetes. At the

same time these animals can survive for the longer time as compared to those animals who do

not over express IL-6 gene (DiCosmo et al 1994).

Another reason for the raised IL-6 in the control group could be that although detailed history of

infection in the last two weeks were obtained from all the studied population but the reason for

high level of IL-6 in the control group could be any sub-acute infection. The high level of IL-6 in

the Group-II could be due to diabetes because Dongancy et al (2002) documented high level of

IL-6 in poorly controlled subjects or this high of IL-6 could be due to the initial stages diabetic

complications. Further, high level of inflammatory markers has been suggested in the healthy

individuals who are prone to get diabetes in later part of their lives (Shoelson et al 2006).

In the current study, highest level of IL-17 cytokine was detected in Group-I (718756pg/ml),

followed by Group-II (415483pg/ml), and Group-III (375468pg/ml). In the literature, some of

the studies are in agreement with the findings of current study such as Steinman et

al(2008)highlighted protective aspect of IL-17 in mycobacterial infection and documented that

IL-17 is required to recruit protective INF-g producing CD4+ T cells into the lung. Further, in an

asthma model, neutralizing IL-17 increased infiltration of eosinophil during the effector phase of

disease. Likewise, Joseph et al (2011) concluded in his study that IL-17 is dispensable at least in

large part in the pathogenesis of autoimmune diabetes. Re et al (2010) suggested, although Th17

cells producing IL-17A are required for acute alveolitis during experimental silicosis, IL-17A

and IL-22 are dispensable for chronic inflammation and are not essential modulators of fibroblast

functions, uncontrolled tissue repair and pulmonary fibrosis. Ye et al (2001) demonstrated that

IL-17 is produced locally in lung tissue as part of the normal host response to a bacterial

challenge with Kalebsella pneumonia. Lv et al (2011) investigated prognostic value of

measuring tumor-infiltrating IL-17 producing cell levels in human esophageal squamous cell

carcinoma (ESCC) and documented higher densities of these calls are associated with better

prognosis. Although the current study also documented high level of IL-17 in healthy control

group compared to diabetic patients with retinopathy and probably this IL-17 is there to provide

protection against the ophthalmic complications but the comparison of above mentioned studies

100

with the current study should not be made because none of the above mentioned studies were

performed in diabetic patients.

It was also suggested that IL-17 may constitute an early initiator of the T cell dependent

inflammatory reaction (Fossiez et al 1996). Guangfu et al (2003) concluded that in vitroIL-17

may play a role in the initiation and development of lupus nephritis through induction of IL-6

over-expression and autoantibody overproduction in peripheral blood mononuclear cells. It is in

agreement with the results of the current study because in Group-II the level of IL-17 was more

compared to Group-III patients which suggest that the level of IL-17 decreased after the

development of diabetic retinopathy.

The results of the current study are not in agreement with some studies such as Zeng et al (2012)

documented increased level of IL-17 in type 2 diabetic patients compared to healthy controls.

Honkane et al (2010) showed an in vitro increased secretion of IL-17 upon T cell activation of

peripheral blood of type-1 diabetic patients. Grajewski et al (2008) explored the role of iNK cells

in the regulation of autoimmunity to retina. They suggested activation of iNK cells ameliorates

experimental ocular autoimmunity by involving innate INF-γ production and dampening

adaptive Th1 and Th17 responses. Monteleone et al (2011) documented enhanced production of

IL-17 in Crohn’s disease (CD) and ulcerative colitis (UC). They speculated simultaneously

neutralization of INF- and IL-17A could help manage the active phases of IBD. Fujino et al

(2003) also concluded increased expression of IL-17 in IBD patients. Hammerich et al (2011)

suggested Th17 cells and related cytokines in various liver diseases. Chi et al (2011) documented

significantly higher levels of IL-17 in active Behcet disease (BD) compared to inactive disease

and normal controls. Nogueira et al (2010) reported significantly elevated levels of IL-17A and

IL-23 in acute ANCA-associated vasculitis.

Similarly, Eid et al (2009) reported that IL-17 is produced concomitantly with INF- by coronary

artery infiltrating T cells and these cytokines act synergistically to induce pro-inflammatory

responses in vascular smooth muscle cells. Almakhzangy et al (2009) documented high levels of

IL-17 and IL-22 in patients of psoriasis. Pene et al (2008) demonstrated high quantity of CD4+ T

cells that produced increased level of IL-17in the inflamed tissue of psoriasis, Crohn’s disease,

101

rheumatoid arthritis, and allergic asthma. Zhao et al (2009) showed elevated levels of IL-17 in

SLE patients compared to normal controls. Wong et al (2008) documented elevated levels of IL-

17 and IL-23 in SLE patients compared to healthy controls. Kotake et al (1999) determined

significantly increased levels of IL-17 in rheumatoid arthritis patients compared to osteoarthritis

patients. Nakae et al (2003) suggested the role of IL-17 in the development of autoimmune

arthritis by T cell activation.

Although the results of the above mentioned studies are different from the current study but

findings of the current study suggest that high level of IL-17 in the control group compared to

diabetic patients with retinopathy could be a protective aspect of IL-17 or low level of IL-17 in

the diabetic patients with retinopathy could be attributed to the effect of medications which these

subjects were having or it could be a combination of both. Although the history of the

medication was not obtained from these patients but there is a possibility that these patients

might be having anti-inflammatory drugs for their eye complications. Therefore, in the light of

the current study, the possibility of negative association of IL-17 with the development of

diabetic retinopathy may also be considered.

In the current study, on comparison of CD4+CD25+cells there was no significant difference.

Studies are available on the frequency of CD4+CD25+ cells whose results are close to the

findings of the current study such as Sun et al (2010) is in partial agreement with the current

study but they used mice model and determined the contribution of CD4+CD25+ T cells to the

regression phase of experimental autoimmune uveoretinitis (EAU). They documented the level

of CD4+CD25+ T cells between 12.7% and 20.7%. Liu et al (2008), investigated the level of

CD4+CD25+ T cells in primary Sjogren syndrome and correlated their level with the

inflammation and they found their level between 7.85 2.62% in the patient group and 11.68

3.78% in the healthy controls. Brusko et al (2005) studied the functional defects and the

influence of age on the frequency of CD4+CD25+ T cells in type-1 diabetes. They documented

their level from 9.67% to 20.75% in the patient group and from 13.49% to 24.57% in the control

group.

102

Similarly, Baecher-Allan et al (2001) studied CD4+CD25high regulatory T cells in human

peripheral blood and suggested the level of CD4+CD25+ cells up to 16%. Fai Ng et al (2001)

documented human CD4+CD25+ cells as a naturally occurring population of regulatory T cells

and suggested their level as 15% to 20% in the peripheral circulation. Dieckmann et al (2001)

studied ex-vivo isolation and characterization of CD4+CD25+ T cells from the blood and

suggested their level between 2.8% to 17.2%. Levings et al (2001) documented that human

CD4+CD25+ T regulatory cells suppress naïve and memory T cell proliferation and this

population can be expanded in vitro without loss of function. They suggested the level of

CD4+CD25+ T cells from 9.8% to 18.1%. All these above mentioned studies detected

CD4+CD25+T cells in the same range as have been observed in the current study but these

studies cannot be compared with the current work because none of them have been performed in

type-II diabetes patients.

There are a number of studies which suggested the range of CD4+CD25+ cells that is different

from the current study. The study reported by Radstake et al (2009) is not in full agreement with

the current study because they found an increased frequency and compromised function of T

cells in systemic sclerosis and they determined the level of CD4+CD25+ T cells as 12.4% 1.0%.

Abdulahad et al (2007) do not agree with the current study because they studied the functional

defect of circulating regulatory CD4+T cells in patients with Wegener’s granulomatosis in

remission and compared it with healthy control group. They documented the level of

CD4+CD25+T cells in Wegner’s granulomatosis and healthy control as 13.29% and 13.68%

respectively. Yeh et al (2006) documented that regular Tai Chi Chuan exercise enhances

functional mobility and number of CD4+CD25+ T cells because before the exercise the level of

CD4+CD25+ cells was 12.5% while their level was 13.6% after this exercise. Game et al (2003)

studied the role of CD4+CD25+ T cells in the patients of renal transplant and they documented

the level of these cells as 7.76% in the patient group and 9.10% in the healthy control group.

Sullivan et al (2002) studied CD4+CD25+T cell production in healthy humans and in patients

with thymic hypoplasia and suggested comparatively higher number of these cells in healthy

controls as compared to the patient group. The level of these cells was between 6% and 15% in

both the groups. Smyth et al (2007) determined CD4 T regulatory cells in chronic obstructed

pulmonary disease (COPD) patients and documented their median level as 0%, 28.8% and 23.1%

in healthy individuals, smokers and COPD patients respectively.

103

The findings of the above mentioned studies suggested that in humans, in different diseases there

is variation in the percentage of CD4+CD25+ T cells. The variation observed in the percentage of

CD4+CD25+ T cells in the current study, is almost similar to the percentage observed by various

researchers in different diseases. In the current study, on comparison of total CD4+CD25+ cells

among different groups, there was no significant difference. The reason for not finding any

significant relationship of CD4+CD25+cells in any group could be that CD4+CD25+ T cells may

not be involved directly in the development of diabetic retinopathy in type-II diabetes.

In the current study, it was also observed that on comparison of Treg cells; that were calculated

from the total population of CD4+CD25+ cells, higher percentage of Treg cells was determined in

Group-II (3.07%) compared to Group-III (2.88%) (p-value=0.0150) but there was no significant

difference of Treg cells among the groups, between Group-I and Group-II, and between Group-I

and Group-III. Therefore, in the current study direct involvement of Treg cells in the

development of diabetic retinopathy cannot be documented.

There are various studies on Treg cells which are in agreement with the current study such as

that Radstake et al (2009) documented an increased frequency and compromised function of

Treg cells in systemic sclerosis and they determined the level of Treg cells as 2.9% 0.5%. Liu

et al (2008) determined the level of CD4+CD25+brightT cells in patients of primary Sjogren

syndrome and suggested their level between 2.79 1.06% in the patient group and 3.84 1.42%

in the healthy controls. Chen et al (2007) documented that CD4+CD25+ Foxp3 regulatory T cells

suppress mycobacterium tuberculosis immunity in patients with active disease. They suggested

their level as 3%, 1.5% and 1.6% in pulmonary tuberculosis, healthy individuals and pulmonary

tuberculosis patients after treatment respectively. Brusko et al (2005) studied the functional

defects and the influence of age on the frequency of CD4+CD25+ Treg cells in type-1 diabetes.

They documented the level of Treg cells around 1.5% in both patient and control group which is

similar to the findings of the current study.

The level of CD4CD25 Treg cells in the patients of renal transplant and healthy control was

reported (Game et al 2003). They observed their level as 7.76% and 9.10% in the patients and

healthy controls respectively but they could not find a significant difference in the level of Treg

104

cells. Baecher-Allan et al (2001) studied CD4+CD25high regulatory T cells in human peripheral

blood and suggested their level as 1 - 2%. Levings et al (2001) documented that human

CD4+CD25+ T regulatory cells suppress naïve and memory T cell proliferation and reported the

level of CD4+CD25+ T reg cells as 1.6 - 4.4%. Guyot-Revol et al (2006) suggested that

regulatory T cells are expanded in blood and disease sites in patients with tuberculosis and

documented the mean level of Treg cells as 1.17% and 2.51% for the healthy subjects and

tuberculosis patients respectively.

In the literature, there are various studies performed on the Treg cells but the data of Treg cells in

diabetes type-II is very limited. Sun et al (2010) who observed significantly increased frequency

of CD4+CD25+ Treg cells in association with the development and regression of experimental

autoimmune uveoretinitis. They documented the level of CD4+CD25+ Foxp3 cells between 6.47

- 13.25%. Hoffmann et al (2007) determined CD4+CD25bright T cells frequencies in asthmatics

and controls and they documented similar frequencies in both. In the normal control group their

level was between 9.41% (7.44% - 12.85) and 10.17% (7.06 – 12.94) in asthmatics. Abdulahad

et al (2007) studied the functional defect of circulating regulatory CD4+ T cells in patients with

Wegener’s granulomatosis in remission. They documented Treg cells as 5.9% 0.5% and 6.8%

0.5% in untreated and treated Wegener’s granulomatosis patients respectively. Loghi et al

(2004) studied the impairment of CD4+CD25+ Treg cells in autoimmune liver disease and

suggested their level as 3.3 0.4 in the patient group while 6.8 0.7 in the control group. They

concluded decreased Treg cell number in autoimmunity against liver. Dieckmann et al (2001)

studied characterization of CD4+CD25+ T cells with regulatory properties and suggested their

level between 2.8% and 17.2% with a mean of about 6%.

The results of the above mentioned studies suggested that in different diseases the percentage of

Treg cells can vary but the above mentioned studies cannot be compared with the findings of the

current study because none of the above mentioned studies were performed on diabetes type-II

patients. Further, the possible explanation for not finding the significant difference in the

percentage of Treg cells could be that Treg cells are involved in the autoimmune process of type-

I diabetes (D’Alise et al 2008, Clough et al 2008, Tang et al 2008) and since in the current study,

105

only patients of type-II diabetes were included, therefore no significant association of type-II

diabetes with Treg cells was found.

106

7. Conclusion

It has been observed in this study that age and gender of the subjects, duration of diabetes and

BglII polymorphism may contribute in the development of type-II diabetic retinopathy. The

serum levels of IL-6 andIL-17 are found negatively associated while level of CD4+CD25+T cells

and percentage of Treg cells are not associated with the development of type-II diabetic

retinopathy.

107

8. Suggestions

1. It has been observed in this study that age and gender of the subjects, duration of diabetes and

BglII polymorphism may contribute in the development of diabetic retinopathy.

2. The differences which has been observed in the levels of IL-6 and IL-17 cytokine, level of

CD4+CD25+ T cells and percentage of Treg cells could have been the result of disease

manifestations.

3. Although, high levels of IL-6 in the intra vitreous fluid has been documented in diabetic

retinopathy subjects but studies should be carried on for the determination of IL-17 in the intra

vitreous fluid as well.

4. There should be functional assays of T lymphocytes and in particular CD4+CD25+ cells to

evaluate their actual role in the diabetic retinopathy.

5. The use of more reliable markers for enumeration of Treg cells such as Foxp3 or CD127

should be performed.

108

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136

Appendix A

CONSENT FORM

Introduction:

Aim of this project is to analyze one of those genes that determine susceptibility to diabetic

retinopathy, enumerate T regulatory cells and to determine the concentration of cytokines (IL-6

and IL-17).

Procedure:

In this study we would draw 10 ml blood by aseptic technique

Possible risks:

No risk

Possible benefits:

It will help in understanding the etiology of diabetic retinopathy.

Financial benefit:

There is no financial benefit for your participation in this research.

Confidentiality:

The information provided by you will be kept secret.

Available sources of information:

You may ask any question from principal investigator; Dr. Nadeem Afzal, Department of

Immunology, University of Health Sciences,Lahore.

Authorization:

I have read and understand this consent form, and I volunteer to participate in this research study.

I am not waiving any of my legal rights by signing this form. My signature below indicates my

consent.

Name of participant: Date:

Signature/thumb impression: Date:

Signature of principal investigator: Date:

137

Appendix B

DATA FORM

Patient ID: ___________

Name: ___________ Age: ________________

Sex: _____________ Occupation: ____________

Contact Address: _________________________________________________________

Land line number: _____________ Cell phone number: ____________________

Duration of diabetes: ________________________________

Insulin therapy: ____________________________________

Age at the onset of diabetes: _____________________________

Smoking status: ____________________________________

History of hypertension: _____________________________

Blood pressure (mmHg): _____________________________

HbA1c (%): ____________________________________________________________

Diagnosis:

______________________________________________________________________________

______________________________________________________________________________

____________________________________________________________

the role of genetics and immune mechanisms in the

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