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UNIVERSITE LIBRE DE BRUXELLES FACULTE DE MEDECINE

LABORATOIRE DE MEDECINE EXPERIMENTALE

Transcription factors and downstream genes modulating TNF-α + IFN-γ induced beta cell apoptosis

Jenny BARTHSON

Thèse présentée en vue de l’obtention du titre de Docteur en Sciences Biomédicales et Pharmaceutiques

Bruxelles, 2013

Members of the jury:

Dr. Muriel MOSER Dr. Rudi BEYAERT

Dr. Alain LE MOINE, President

Dr. Decio EIZIRIK, Secretary (Promoter) Dr. Marc ABRAMOWICZ

Dr. Stanislas GORIELY Dr. Bernard ROBAYE

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ACKNOLEDGEMENTS

I wish to extend my profound gratitude to the following people for their selfless contribution and support throughout the duration of this work.

My heartfelt gratitude goes to Prof. D.L Eizirik, my promoter, for his constant supervision and for being a great inspiration to me. Thank you for your perpetual energy and enthusiasm in research; for your accessibility and advice. Thank you for bringing out the best in me as concerns research and for giving me hope when all seemed lost.

Many thanks to Dr. E.N Gurzov who supervised my work and who thaught me a lot of molecular biology technics. Thanks for your support, time, intellectual contribution and motivation.

Thanks to Dr M. Cnop and Dr. M. Igoillo-Esteve for the advice, help and suggestions.

I am grateful to all the co-workers for their contribution and help.

My appreciation goes out to the jury members for taking off precious time to review this work and to be present at the defence.

I would like to thank all the members of the Laboratory of Experimental Medicine for their help and advice.

I remain indepted to my family and friends for all the support and understanding.

Special thanks to my husband, Koen Andries for his patience and endless support. Thank you, Aicha Barthson for giving me the opportunity to continue my studies and for always supporting me and Julius Barthson for always being there and encouraging me.

Thanks to all who helped me in one way or another and who are not mentioned.

Financial support for the work shown in this thesis was provided by grants from the Fonds National de la Recherche Scientifique (FNRS) Belgium, the Communauté Française de Belgique, Actions de Recherche Concertées (ARC), the European Union (projects Naimit and BetaBat, in the Framework Programme 7 of the European Community), the Juvenile Diabetes Foundation International (JDFI) and the Expert Center Grant 2008.40.001 from the Dutch Diabetes Research Foundation.

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SUMMARY

In type 1 diabetes (T1D) a combination of genetic predisposition and environmental factors triggers islet inflammation (insulitis) leading to a selective and gradual destruction of the pancreatic beta cells. Beta cells mainly die through apoptosis, triggered at least in part by pro-inflammatory cytokines such as IL-1β, TNF-α and IFN-γ. Recent findings suggest that the mitochondrial pathway of cell death is involved in this death cascade. Array analysis indicated that TNF-α+IFN-γ induces transcription factors such as NF-ĸB, STAT1, and AP-1 in beta cells. We presently aimed to examine the pathway(s) of apoptosis triggered by TNF- α+IFN-γ in beta cells.

TNF-α+IFN-γ induces beta cell apoptosis through the intrinsic pathway of cell death.

This involved activation of the BH3 only proteins DP5, PUMA and Bim. Knockdown (KD) of either DP5 or PUMA or both led to a partial protection of INS-1E cells (12-20%), while silencing Bim led to about 60% protection against cytokine-induced apoptosis. Bim is transcriptionally induced by activated STAT1. TNF-α+IFN-γ also induces downregulation of Bcl-XL, an anti-apoptotic Bcl-2 gene which inhibits Bim. Knocking down Bcl-XL alone led to increase in apoptosis, but this was prevented by the parallel KD of Bim.

The ultimate goal of our research is to protect beta cells from the autoimmune assault.

Previous data revealed that JunB inhibits ER stress and apoptosis in beta cells treated with IL- β+IFN-γ. Here, TNF-α+IFN-γ up-regulated the expression of JunB which was downstream of activated NF-ĸB. JunB KD exacerbated TNF-α+IFN-γ induced beta cell death in primary rat beta cells and INS-1E cells. The gene networks affected by JunB were studied by microarray analysis. JunB regulates 20-25% of the cytokine-modified beta cell genes, including the transcription factor ATF3 and Bcl-XL. ATF3 expression was increased in cytokine-treated human islets and in vitro silencing of JunB led to >60% reduction in ATF3 overexpression.

We confirmed direct JunB regulation of the ATF3 promoter by its binding to an ATF/CRE site. Silencing of ATF3 aggravated TNF-α+IFN-γ induced cell death in beta cells and led to the downregulation of Bcl-XL expression in INS-1E cells. Pharmacological upregulation of JunB using forskolin led to upregulation of ATF3 and consistent protection of these cells against cytokine-induced cell death, while genetic overexpression of JunB in mice increased ATF3 expression in the pancreatic islets and reversed the pro-apoptotic effects of cytokines on beta cells (±40 % protection).

As a whole, our findings indicate that TNF-α+IFN-γ triggers beta cell apoptosis by the upregulation of the pro-apoptotic protein Bim and downregulation of the Bcl-XL protein.

These deleterious effects are at least in part antagonized by JunB via activation of ATF3.

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RESUME

Dans le diabète de type 1 (DT1), la combinaison de facteurs génétiques de prédisposition et de l'environnement déclenche l'inflammation des îlots de Langerhans (insulite) conduisant à une destruction sélective et progressive des cellules bêta du pancréas.

Les cellules bêta meurent principalement d’apoptose, déclenchée au moins en partie par les cytokines pro-inflammatoires sécrétées par les cellules immunitaires comme l’IL-β, le TNF-α l’IFN-γ. De récentes découvertes suggèrent que la voie mitochondriale de la mort cellulaire jouerait un rôle dans la mort de ces cellules. L'analyse de réseaux de gène utilisant les biopuces d’ADN indique que l’association TNF-α+IFN-γ induit l’activation de facteurs de transcription tels que NF-ĸB, STAT1 et AP-1 dans la cellule bêta. Dans ce contexte, nous avons cherché à examiner les voies de l'apoptose déclenchées par le TNF-α+IFN-γ dans la cellule bêta.

En présence de TNF-α+IFN-γ les cellules bêta meurent par apoptose via la voie intrinsèque. L’activation des protéines pro-apoptotiques « BH3-seulement » dont DP5, PUMA et Bim étaient en cause de cette apoptose. Le « knockdown »1 (KD), de DP5 ou de PUMA, ou des deux en même temps conduit à une protection partielle des cellules INS-1E (12-20%), tandis que le KD de Bim conduit à environ 60% de protection contre l’apoptose induite par cette combinaison de cytokines. La transcription de Bim est induite par STAT1 activé. Parallèlement à la régulation positive de Bim, TNF-α+IFN-γ conduit à la régulation négative de la protéine Bcl-XL. Bcl-XL est une protèine anti-apoptotique de la famille de protèines Bcl-2 qui en general inhibe Bim. Réduire l’expression de Bcl-XL seul induit une augmention de l'apoptose, alors que le KD de Bim et Bcl-XL en parallèle empêche l'apoptose.

Le but ultime de notre recherche est de protéger les cellules bêta des agressions autoimmunitaires. Les données antérieures ont révélé que JunB inhibe le stress du réticulum endoplasmique et l'apoptose dans les cellules bêta traitées avec IL-β+IFN-γ. Nous avons observé que TNF-α+IFN-γ induit l'expression de JunB qui se produit en aval de NF-ĸB activé.

Il est important de noter que l’inactivation de JunB par des agents interférants de l’ARN (siRNA) exacerbe la mort des cellules primaires bêta de rat et de cellules INS-1E induite par les cytokines. Les réseaux de gènes touchés par JunB ont été étudiés grâce a l'analyse en microréseaux. JunB règule 20-25% des gènes modifiés par des cytokines dans les cellules bêta, y compris le facteur de transcription ATF3 et Bcl-XL. L’expression d’ATF3 est augmenté dans les îlots humains traités avec les cytokines et la répression in vitro de JunB conduit à une réduction de >60% de l’expression d’ATF3. Nous avons confirmé la régulation

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ATF/CRE. La diminution d’expression d’ATF3 en presence de TNF-α+IFN-γ a aggravé la mort cellulaire induite dans les cellules bêta et a conduit à la régulation négative de l'expression de Bcl-XL dans les cellules INS-1E. L’augmentation pharmacologique de JunB dans les cellules INS-1E par l’utilisation de forskolin a conduit à la régulation positive en aval d’ATF3 et par conséquente à la protection de cellules bêta vis-a-vis de effets indésirables des cytokines. Dans cette optique, la surexpression génétique de JunB dans le modèle Ubi-JunB de souris transgénique a conduit à une surexpression d’ATF3 dans les îlots pancréatiques et a permir d’inverser les effets pro-apoptotiques de cytokines sur la cellule bêta (protection ± 40%).

Globalement, ces résultats indiquent que TNF-α+IFN-γ déclenche l'apoptose des cellules bêta par la régulation positive du gène pro-apoptotique Bim et la régulation négative du gène anti-apoptotique Bcl-XL. Ces effets indésirables sont inhibé en partie par JunB via l’activation de ATF3.

1Pas d’équivalent en français. Signifie la réduction de l’expression d’un gène via utilisation d’un siRNA (agent

interférant de l’ARN).

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LIST OF ABBREVIATIONS AND ACRONYMS

AIRg Acute insulin response to glucose AKT/PKB Protein kinase B

AP-1 Activator protein-1

APAF1 Apoptotic protease activating factor-1 APC Antigen presenting cell

AS Alternative splicing

ATF Activating transcription factor Bad Bcl-2 antagonist of cell death Bak Bcl-2 antagonist killer 1 Bax Bcl-2-associated x protein BB rats BioBreeding rats

Bcl-2 B-cell lymphoma 2

Bcl-2A1 Bcl-2-related gene A1 Bcl-2L10/Bcl-B Bcl-2-like protein 10

Bcl-XL Bcl-2-related gene long isoform

BH Bcl-2 homology domain

Bid Bcl-2-interacting domain death agonist Bik Bcl-2-interacting killer

Bim Bcl-2-interacting mediator of cell death BIRC3 Baculoviral IAP repeat-containing 3 BMF Bcl-2 modifying factor

BMI Body mass index

BNIP3 Bcl-2/adenovirus E1B 19 kDa protein-interacting protein 3 Bok Bcl-2-related ovarian killer

bZIP Basic region-leucine zipper cAMP Cyclic adenosine monophosphate

CCL CC chemokine ligand

CFLAR CASP8 and FADD-like apoptosis regulator ChIP Chromatin immunoprecipitation

CHOP C/EBP homologous protein

CTL Cytotoxic T lymphocyte

CXCL CXC chemokine ligand

DC Dendritic cell

DHA Decosahexaenoic acid

DIABLO Direct IAP-Binding protein with Low PI

DP5 Death protein 5

DPT Diabetes prevention trial

dsRNA double stranded RNA

ECSIT Evolutionarily conserved signalling intermediate in Toll pathways eIF2α Eukaryotic initiation factor 2 α

ENDIT European Nicotinamide Diabetes Intervention Trial

ER Endoplasmic reticulum

ERAD ER-associated degradation

ERK Extracellular signal-regulated kinase FACS Fluorescent activated cell sorting

FasL Fas ligand

FINDIA Finnish Intervention Trial for the Prevention of Type 1 Diabetes

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FPIR First phase insulin release

FXYD2 Sodium/potassium-transporting ATPase gamma chain GAD Glutamic acid decarboxylase

GADA Glutamic acid decarboxylase autoantibodies

GAS Gamma activated site

GDM Gestational diabetes GLP-1 Glucagon-like peptide-1 Glut2 Glucose transporter 2

GWAS Genome-Wide Association Studies

HLA Human leukocyte antigen

HSP60 Heat shock protein 60

IA-2A Insulinoma associated protein-2 autoantibodies IAA Insulin autoantibodies

ICA Islet cell autoantibodies ICAD Caspase-activated DNase ICAM Intercellular adhesion molecules IDF International Diabetes Federation IDLV Integration-deficient lentiviral vectors

IFN Interferon

IFN-γR Interferon receptor

IKK IĸB kinase

IL Interleukin

IL-1R Inteleukin 1 receptor IL-1Ra IL-1 receptor antagonist

IMS Mitochondrial intermembrane space iNOS Inducible nitric oxide synthase INS-1E Insulin secreting (rat) cell line INT-II Intranasal Insulin Trial II IRAK IL-1R-associated kinase IRE-1 Inositol requiring enzyme 1 IRF Interferon regulatory factor

Isl-1 Islet 1

IVGTT Intra-venous glucose tolerance test

JAK Janus kinase

JAM-1 Junctional adhesion molecules JDP Jun dimerization protein JNK c-Jun N-terminbal kinase

KD Knockdown

LFA-1 Leukocyte function-associated antigen-1

MafA V-maf musculoaponeurotic fibrosarcoma oncogene homolog A (avian) MAPK Mitogen-activated protein kinase

MCL-1 Myeloid cell leukemia 1

MDA-5 Melanoma differentiation associated gene 5

MDG Millenium Development Goals

MEKK MAP kinase kinase kinase

MHC Major histocompatibility complex

miRNA Micro mRNA

MKK MAP kinase kinase

MLDS Multiple low dose streptozotocin

MOMP Mitochondrial outer membrane permeabilization

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MULE MCL-1 ubiquitin ligase E3

MyD88 Myeloid differentiation primary response gene NAD Nicotinamide adenosine dinucleotide

NEMO NF-ĸB essential modulator NF-ĸB Nuclear factor-ĸB

NIK NF-ĸB-inducing kinase

NIP Nutritional Intervention to Prevent Diabetes

NK Natural killer

NO Nitric oxide

NOD mice Non-obese diabetic mice

Nova1 Neuro-oncological ventral antigen 1

NOXA Phorbol-12-myristate-13-acetate-induced protein 1 OGTT Oral glucose tolerance test

OMM Outer mitochondrial membrane Pdx1 Pancreatic and duodenal homeobox 1

PERK Protein kinase RNA-like endoplasmic reticulum kinase

pLN Pancreatic lymph nodes

Pre-POINT Primary Oral/Intranasal Insulin Trial PRR Pattern-recognition receptor

PTPN2 Tyrosine-protein phosphatase non-receptor type 2 PUMA p53 upregulated modulator of apoptosis

RHD Rel homology domain

RIG-1 Retinoic acid-inducible gene 1 Rip Receptor interacting protein

SERCA Sarco/endoplasmic reticulum Ca2+-ATPase

SHP2 SH2 domain-containing protein tyrosine phosphatase siRNA Small interfering RNA

SMAC Second mitochondria-derived activator of caspase SOCS Suppressor of cytokine signaling

SOD Superoxide dismutase

STAT1 Signal transducer and activator of transcription 1

T1D Type 1 diabetes

T2D Type 2 diabetes

TAB1 TAK1-binding protein 1

TAK1 Transforming growth factor β activated kinase 1 tBid Truncated Bcl-2-interacting domain death agonist

TCR T cell receptor

Th T helper cell

Th0 Naive T helper cell

TLR Toll-like receptor

TNF Tumor necrosis factor

TNFAIP3 TNF-alpha-induced protein 3

TNF-R TNF receptor

TRADD TNF receptor-associated death domain TRAF TNF-receptor-associated factor

TRE Phorbol 12-O-tetradecanoate-13-acetate (TPA) response element

Treg Regulatory T cell

TRIGR The Finnish Trial to Reduce IDMM in Genetically at Risk UPR Unfolded protein response

VEC Vascular endothelial cells

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VLA-4 Very late activation antigen-4

WT Wild type

XBP-1 X-box binding protein 1 ZnT8 Zinc transporter 8

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PUBLICATIONS CONSTITUTING THIS THESIS

Article I: Cytokines tumor necrosis factor-α and interferon-γ induce pancreatic β-cell apoptosis through STAT1-mediated Bim protein activation.

Jenny Barthson, Carla M. Germano, Fabrice Moore, Adriano Maida, Daniel J. Drucker, Piero Marchetti, Conny Gysemans, Chantal Mathieu, Gabriel Nuñez, Andrea Jurisicova, Decio L. Eizirik, and Esteban N. Gurzov.

J. Biol. Chem. 2011 286: 39632-39643. First Published on September 21, 2011, doi:10.

/jbc.M111.253591

Article II: Pancreatic β-cells activate a JunB/ATF3-dependent survival pathway during inflammation.

Esteban N. Gurzov, Jenny Barthson, Ihsane Marhfour, Fernanda Ortis, Najib Naamane, Mariana Igoillo-Esteve, Piero Marchetti, and Decio L. Eizirik

Oncogene. 2012 Mar 29;31(13):1723-32. doi: 10.1038/onc.2011.353.

(These papers will be quoted in the text as roman numerals).

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Table of Contents

UNIVERSITE LIBRE DE BRUXELLES ... 1

ACKNOLEDGEMENTS ... 2

SUMMARY ... 3

RESUME ... 4

LIST OF ABBREVIATIONS AND ACRONYMS ... 6

PUBLICATIONS CONSTITUTING THIS THESIS ... 10

1. INTRODUCTION ... 12

1.1 Type 1 Diabetes ... 12

1.1.1 Definition and classification of diabetes ... 12

1.1.2 Clinical manifestations ... 12

1.1.3 Burden of the disease ... 13

1.1.4 Genetics and environmental factors leading to T1D ... 13

1.1.5 Pathogenesis ... 15

1.1.6 Prediction, prevention trials and therapy ... 17

1.2 Inflammation (insulitis) in type 1 diabetes ... 22

1.2.1 Induction of insulitis and innate immune response ... 22

1.2.2 Adaptive immune response ... 23

1.2.3 Amplification, maintenance or resolution of insulitis ... 26

1.3 Inflammation and beta cell loss in type 1 diabetes ... 28

1.3.1 Inflammation and apoptosis ... 28

1.3.1.1 Apoptotic pathways ... 28

1.3.1.2 Pro-inflammatory cytokines and the intrinsic apoptotic pathway in beta cells ... 31

1.3.1.3 Bcl-2 proteins and intrinsic/mitochondrial apoptosis ... 35

1.3.1.4 Regulation of Bcl-2 proteins ... 36

1.3.2 Transcription factors downstream of inflammatory stress in beta cells ... 38

1.3.2.1 JNK ... 38

1.3.2.2 NF-κB ... 39

1.3.2.3 JAK/STAT1 ... 41

1.3.2.4 AP-1 ... 42

2. AIMS ... 44

3. RESULTS ... 45

4. DISCUSSION ... 47

4.1 Effects of pro-inflammatory cytokines on beta cell viability ... 47

4.1.1 TNF-α+IFN-γ activates the intrinsic apoptotic pathway in beta cells ... 48

4.1.2 STAT1 mediates TNF-α+IFN-γ-induced Bim activation ... 49

4.1.3 TNF-α+IFN-γ triggers beta cell death mostly via an imbalance between Bim/Bcl-XL ... 50

4.1.4 Jun-B protects beta cells against TNF-α+IFN-γ induced cell death through the upregulation of ATF3 and Bcl-XL ... 51

4.1.5 Conclusions ... 54

4.1.6 Future perspectives ... 57

Reference list………64  

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1. INTRODUCTION

1.1 Type 1 Diabetes

1.1.1 Definition and classification of diabetes

Diabetes mellitus is a group of heterogeneous metabolic disorders of multiple aetiology, characterised by chronic hyperglycaemia and disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action or both (1).

The current system of classification proposed by the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus is based on the known aetiology and the associated pathological process (1;2). The different forms include type 1 diabetes, type 2 diabetes, gestational diabetes and other specific forms.

Type 1 diabetes (T1D): This form of diabetes affects 5-10% of those with diabetes. The condition develops as a result of beta cell destruction usually leading to absolute insulin deficiency. It exists in two forms: the immune mediated (type 1a) diabetes, which occurs as a consequence of the T-cell mediated autoimmune destruction of beta cells (3) and the idiopathic (type 1b) diabetes, which has an unknown aetiology and accounts for a minority of type 1 diabetes patients (most common among individuals of African and Asian origin) (1).

Type 2 diabetes (T2D): 90-95% of diabetic patients have T2D. It is characterised by insulin resistance and relative insulin deficiency, either of which may present at the time of clinical manifestation. It is strongly but not always associated with obesity (1).

Gestational diabetes (GDM): Any degree of glucose intolerance with onset or first recognition during pregnancy. The prevalence ranges from 1-14% depending on the population studied.

GDM constitutes an increased risk of developing T2D for both mother and child (1).

Other specific types of diabetes: Includes forms of diabetes that develop as a result of genetic defects in beta cell function or insulin action, diseases of the exocrine pancreas, endocrinopathies, drugs or chemically induced diabetes, infections or other genetic syndromes (1).

1.1.2 Clinical manifestations

Individuals with diabetes have an increased risk of developing a number of serious health problems due to chronic hyperglycemia. The symptoms of acute hyperglycemia include polyuria, polydipsia, polyphagia, weight loss, blurred vision and frequent or recurrent infections. One of the most severe acute complications of hyperglycemia is diabetic ketoacidosis. Chronic complications of diabetes include slow healing wounds, sexual

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dysfunction, retinopathy, nephropathy and neuropathy leading to diabetic foot, kidney failure, blindness, cardiovascular and cerebrovascular complications (1).

1.1.3 Burden of the disease

Reports from the International Diabetes Federation (IDF) indicate that the number of people living with diabetes is expected to increase from 366 million in 2011 to 552 million by 2030. This is equivalent to three new cases every ten seconds or almost ten million cases per year. The IDF also estimates that as many as 183 million people are unaware that they have diabetes. In some of the poorest regions in the world such as in some regions in Africa, diabetes cases are expected to rise by 90% by 2030. About 78% of diabetic individuals in Africa are undiagnosed and are unaware of their diabetic status (4).

Approximately 80% of people with diabetes live in low and middle-income countries.

In 2011 diabetes caused 4.6 million deaths and at least 465 billion dollars in healthcare expenditure. Diabetes is responsible for 1 million amputations each year and increases the risk of tuberculosis (4). If the United Nations’ Millenium Development Goals (MDG) are to be met, the prevention, control, treatment and management of diabetes and its complications must be made a priority since the disease poses severe risks to families and whole nations and considerably retards development (5).

5-10% of all cases of diabetes are attributable to Type 1 diabetes (T1D), the main focus of the present thesis. An estimated 490,100 children below the age of 15 years are living with T1D. A further 77,800 children under the age of 15 developed the disease in 2011 and there is evidence that the incidence is rising rapidly with an estimated 3% increase per year, especially among the youngest children (4;6). Younger children with diabetes may be more likely than older children or adults to present with ketoacidosis at the time of diagnosis and face more years of hyperglycaemia with increased risk of complications. These combined factors place a significant burden on health systems and may increase the costs of care (4;7).

1.1.4 Genetics and environmental factors leading to T1D

More than 35 years have passed since the first genetic associations with T1D were reported (8). The inheritance of diabetes is very complex. The life time risk of developing T1D is about 1% (9) and approximately 10-15% of patients have a family history of the disease (10). Predicting with exactitude which individual will be affected by T1D is not presently possible. However, it is possible to perform tests to assess who is at a higher risk and these tests include assays for autoantibodies, genetic and metabolic assays.

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Autoimmune markers of beta cells in T1D include islet cell autoantibodies (ICA), autoantibodies to insulin (IAA), autoantibodies to glutamic acid decarboxylase (GAD/GAD65) (GADA), autoantibodies to the tyrosine phosphatises such as insulinoma associatd proteins IA-2 and IA-2β (combinedly referred to as IA-2A) and autoantibodies to the cation eflux zinc transporter ZnT8 (Slc30A8) (ZnTA) (1;3;11). One or more, usually 2-4 of these autoantibodies are present in 85–90% of individuals with T1D when fasting hyperglycemia is initially detected (1).

Genetic testing for T1D is important for the identification of population with increased risk for the disease. The first reports of genetic associations to T1D were for the human leukocyte antigen (HLA) region about 40 years ago (8). Since then, large collaborative international studies such as the Genome-Wide Association Studies (GWAS) and large case- control and family based association studies have been carried out to determine which alleles of the HLA are involved in T1D association and to search for other loci that may contribute to disease risk (8). Based on these studies, it was discovered that over 50 loci may affect the risk of T1D with the HLA association being strongest by far with linkage to the DQA and DQB genes and influenced by the DRB genes. These HLA-DR/DQ alleles can either predispose or protect against the disease (1). After HLA, the most significant T1D genetic associations come from polymorphisms in the insulin gene promoter region and in the PTPN22 and IL- 2RA loci, with the last two genes modulating basic pathways of T cell activation, function and regulation (12). Candidate genes for T1D may act both at the immune system and pancreatic islet-cell levels (13)

Genetic susceptibility to T1D does not seem to be the only criteria necessary in the development of the disease. A series of evidence supports a critical role of environmental factors. Available data show that: <10% of individuals with high susceptibility to T1D diabetes actually progress to clinical disease; <40% of monozygotic twins are pairwise concordant for T1D; there is a more than 10-fold difference in the disease incidence among caucasians living in Europe; there has been a several-fold increase in the incidence over the last 50 years, and migration studies indicate that the disease incidence has increased in population groups who have moved from a low-incidence to a high-incidence region (9;14).

Environmental factors are not only triggers but may also potentiate/accelerate beta cell destruction (Fig 1). The proposed environmental factors that may participate in the development and potentiation of T1D include: viral infections (enteroviruses, mumps, measles, rotaviruses, Epstein-Bar virus, cytomegalovirus, coxsackie A and B virus and

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of breastfeeding, cereals, insulin in milk, nitrates, nitrites, inadequate consumption of cod liver oil, vitamin C); climatic influences (cold climate, lack of sunshine and vitamin D); rapid growth or weight gain; puberty; pregnancy; psychological stress; toxins and drugs (e;g alloxan and streptozotocin); vaccination; hygiene and perinatal and neonatal risk factors (older maternal age at birth, excessive weight gain in pregnancy, early neonatal illnesses and mother-child blood group incompatibility-ABO and Rh, caesarean section deliveries, birth weight and birth order) (9;15-21). In population studies no common environmental factor has been conclusively identified. The mechanism by which some of these factors may contribute to the aetiology and pathogenesis of T1D are under investigation. However, we should keep in mind that progression to clinical T1D typically requires the combination of genetic disease susceptibility, diabetogenic triggers (which might be one or several environmental factors) and a high exposure to putative driving antigen(s).

Fig 1: Hypothetical stages in the development of type 1 diabetes beginning with genetic susceptibility and ending with complete beta cell destruction. Figure also illustrates different stages of insulitis, evolution of metabolic disorder and different levels of prevention. Adapted from (22-24)

1.1.5 Pathogenesis

Clinical T1D presents as beta cell failure with the requirement of daily insulin treatment. The precise sequence of immunological, genetical and physiological events that regulate disease initiation and progression remains to be clarified. In the preclinical phase most subjects are asymptomatic and euglycemic over many months or years. Most of the knowledge gained on the pathophysiological development of diabetes has been obtained

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through the use of the non-obese diabetic (NOD) mouse (25;26) and the BioBreeding (BB) rat (27). Studies in these animal models indicate that the disease occurs as a consequence of breakdown in immune regulation and triggering of an innate and then adaptive immune response (28). Macrophages and dendritic cells are the first cells to infiltrate the pancreas at the early stages and this may be followed by peri-insulitis during which potential pathogenic T cells surround the islets. Further islet damage leads to the release of self-antigens, epitope spreading and amplification by islet mononuclear cell infiltrates present at the time of disease onset (3). At this time, autoantibodies can be detected in blood samples from patients. The level of insulitis and beta cell destruction is probably dependent on the balance between pathogenic and regulatory T cells (21). Failure to resolve insulitis will lead to progressive beta cell destruction culminating in overt clinical diabetes (Fig 1). Of note, a study on baboons administered with increasing doses of streptozotocin revealed that while in vivo measures of beta cell function approached zero in some cases, there was still approximately 40-50% of the beta cell mass detectable histologically (29) suggesting that loss of functioning cells in T1D may be due in part to the inhibitory action of cytokines and other mediators released from inflammatory cells in the islets (30).

Intra-venous glucose tolerance tests (IVGTT) and more frequently oral glucose tolerance tests (OGTT) are usually carried out to determine functioning beta cell mass. The former determines the acute insulin response to an intravenous injection of glucose (AIRg) while the latter measures the body’s ability to clear orally ingested glucose over a 2 hour period (29;31). Although glucose tolerance can remain normal until near the onset of clinical type 1 diabetes, measurement of pancreatic beta cell function by measurement of the AIRg (IVGTT) usually shows substantial reduction in insulin secretion (32) (Fig 1). However, impaired OGTT frequently precedes the onset of overt diabetes and it is thus recommended to carry out both tests in order to maximise sensitivity (31;33). Interestingly, the Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) (34) has recently shown that determination of C-peptide and glucose indexes from OGTT, along with age and BMI, are useful in the identification of individuals who are highly likely to progress to T1D within 2 years (35).

Most of these individuals who were in a state of “preclinical T1D” still had appreciably high levels of C-peptide indicating residual beta cell function which may still be rescued.

Thus, genetic markers for type 1 diabetes are present from birth, immune markers are detectable after the onset of the autoimmune process, and metabolic markers can be detected with sensitive tests once enough beta cell damage has occurred, but before the onset of symptomatic hyperglycemia (36). This long latent period is a reflection of the large number of

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functioning beta cells that must be lost before hyperglycaemia occurs. Fig 1 summarises in a simplified way the hypothetical events that may lead to the onset and progression of diabetes and how the disease may progress.

1.1.6 Prediction, prevention trials and therapy

As discussed above, the risk of developing T1D can be estimated by using genetic, autoantibody and metabolic markers. At present, screening for individuals at risk of T1D is recommended only as part of prospective studies on the natural history of the disease or for selection of individuals for participation in prevention studies.

Genetic markers are helpful in assessing the risk of type 1 diabetes in close relatives of a T1D patient. The risk in these relatives is about 6% in offsprings and 5% in siblings (versus 0.4 % in subjects with no family history) (37) . The risk increases from 2-50% in first degree relatives depending on the relationship and the genetic similarity with the proband. For example, the risk in siblings decreases from 33% in identical twins (37) to 12.9 to 4.5 to 1.8

%, respectively, if the siblings share two, one, or no haplotypes (38) .

The major susceptibility genes for type 1 diabetes are in the HLA region on chromosome 6p (38). Over 90% of patients with T1D carry the DR4, DQB*0302 and/or DR3, DQB*0201. Thus, if the proband is heterozygous for DR3 and DR4 (the highest risk combination), the incidence of type 1 diabetes in a sibling who shares these two haplotypes increases to 19 %. On the other hand, the absence of the above alleles makes type 1 diabetes very unlikely, especially if the subject carries a protective allele such as DQB*0301, *0602 (39), DRB*0403, or *0406 (40). Table 1 shows the combined effect of susceptibility or protective alleles and the presence or absence of a first-degree relative with T1D.

HLA genotyping at birth may identify individuals at high risk of developing type 1 diabetes before the occurrence of clear signs of islet autoimmunity. In general, the additional measurement of two HLA-DQ high-risk haplotypes does not increase the predictive value of combined autoantibody assays. However, in relatives positive or negative for conventional islet autoantibodies, the presence of two HLA-DQ high-risk haplotypes can differentiate between rapid and slow progressors (41;42).

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Table 1: Importance of genetic markers in susceptibility to T1D

Genetic Marker No T1D relative First degree relative with T1D

DQB*0302/*0201 1 in 25 1 in 4

DQB*0302/*0302 1 in 60 1 in 10

DQB*0302/*0602 1 in 1500 Unknown

DQB*0302/Other 1 in 60 1 in 10

DQB*0201/*0201 1 in 350 1 in 10

DQB*0201/Other 1 in 400 1 in 20

Other 1 in 5000 1 in 40

Adapted from (43)

As mentioned above, several clinically useful serum autoantibodies can be detected during the preclinical period of T1D, including ICA, IAA, GADA, IA-2, IA-2β and autoantibodies to ZnT8. These autoantibodies can be present in any combination in humans (1;3;11).

In several prospective family studies in which unaffected first-degree relatives of type 1 diabetic probands were followed, the presence of ICA or IA-2 was associated with an increased risk of diabetes, particularly if the titers were high or were present in combination with IAA or GADA antibodies (44-46). The risk of T1D is relatively low with IAA alone, but is higher with the presence of multiple autoantibodies against islet antigens (insulin, GADA, IA-2 and ICA) (41;44). In T1D relatives as well in the general population, the risk of developing disease increases with the number of positive autoantibodies. T1D relatives with two or more antibodies have a 39% and 68% risk of developing T1D within 3 and 5 years respectively; relatives positive for three autoantibodies have an estimated >90% risk of developing T1D within 5 years (45). For diabetes prediction, a combination of GADA and IA-2 for primary screening, followed by ICA and IAA testing, has been proposed (47).

Antibodies to GADA are predictive of progression to hyperglycemia even in the absence of ICA or IAA (45). As with IAA, however, the risk is higher in subjects who are also ICA- positive (45). Children with the earliest evidence of autoimmunity (from 6 months to 3 years of age) are at greatest risk for and progress more quickly to the development of T1D (48-51).

Periodic testing for islet autoantibodies appears to help assess the risk of diabetes in children of parents with T1D.

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In addition to identifying subjects at risk for T1D, the presence of ICA and GADA antibodies can also identify late-onset T1D in adults thought to have T2D. In a study of 97 Swedish diabetic patients who were initially considered to have type 2 or unclassifiable diabetes, 70 became insulin-dependent after six years of follow-up. Among these 70 patients, 60 % were positive for either ICA or GADA at diagnosis, compared with only 2 % of the 27 patients who remained responsive to oral therapy (52).

ZnT8 is also a T1D autoantigen (11). 60 to 80 % of patients with newly diagnosed T1D have ZnT8 autoantibodies. Importantly, 26 % of T1D subjects negative for the other known autoantigenes (insulin, GADA, IA-2 and ICA) have ZnT8 autoantibodies. Combined measurement of ZnT8A, GADA, IA2A, and IAA raises autoimmunity detection rates to 98%

at disease onset, increasing sensitivity (11). Another study examined the added value of measuring both IA-2β and ZnT8A for prediction of impending diabetes in relatives of T1D patients. It confirmed the association of IA-2, IA-2β and ZnT8A with rapid disease progression and demonstrated that IA-2 and ZnT8A represent the most sensitive combination of two markers to identify relatives with a high progression rate (53).

Although glucose tolerance may remain normal until close to the onset of hyperglycemia (32), the acute insulin response to several secretagogues (glucose, arginine, glucagon and isoproterenol) decreases progressively during the preclinical period (54). The most useful and widely performed test is the acute (or "first phase") insulin response to glucose (AIRg or FPIR) during an intravenous glucose tolerance test (IVGTT); in this test the rise in serum insulin above baseline is measured during the first 10 minutes after an intravenous glucose challenge; the response correlates with the functioning beta cell mass (29;31). In first-degree relatives of patients with type 1 diabetes, for example, FPIR below the first percentile of normal is a strong predictor of T1D (44).

Predicting the risk of T1D is presently based on a stepwise decision tree (55). Using this appproach, genetic risk is usually the first to be applied in the form of family history and HLA DR-DQ genotyping. Autoantibodies are then measured in those individuals who are considered to have sufficient genetic risk to warrant additional testing. Finally, beta cell function is measured in islet autoantibody–positive individuals using an IVGTT and/or OGTT. BMI and age can also serve in combination with these factors to refine the predictive value (34).

Currently, there is no prevention or cure for T1D probably because of the still limited understanding of the pathogenesis and natural history of the disease. Moreover, we lack clear

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biological markers for the different phases of the disease. In spite of these short-comings, intervention trials have aimed at targeting the different phases of the disease involving primary, secondary or tertiary prevention strategies (56;57) discussed below.

Primary prevention should intervene before the development of autoimmunity. It aims at avoiding the initiation of the disease process in individuals with a genetic risk by avoiding or neutralizing potential environmental triggers (56;57). The targeted population is young children with the high risk genotypes and pregnant women expecting high risk babies based on family history. This is presently difficult to achieve as the external etiological factors have remained elusive and might be operative at an early (perhaps prenatal) stage. Added to this, the existing genetic screening tools have low predictive value (58). Dietary modifications (e.g cow’s milk hypothesis in TRIGR and FINDIA, gluten free diet in BABYDIET, decosahexaenoic acid (DHA) in TrialNet NIP and vitamin D supplementation) and antigen specific vaccines (e.g insulin in Pre-POINT) are being investigated (58-60). (Fig 1, Table 2).

Secondary prevention targets the initiated autoimmune process in the preclinical phase in both relatives of T1D patients and subjects in the general population. The goal is to prevent or delay the clinical onset of T1D. The strategies are based on pharmacological or nutritional interventions. The identification of prospective patients in the preclinical stage using immune, genetic and hormonal markers is crucial. Detecting and monitoring the subclinical disease process and the development of methods to slow down, arrest or reverse the evolution of the disease are the main goals. Insulin (oral insulin administration in DPT and TrialNET, oral and intranasal insulin administration in INT II) (61) and nicotinamide (in the ENDIT) (62) have been tested unfortunately without success. (Fig 1, Table 2).

Tertiary prevention is implemented after clinical onset. It aims at preserving or restoring beta cell mass and function in order to prevent chronic complications caused mainly by hyperglycaemia (63). Immune-based therapeutic interventions have specifically targeted the preservation of residual beta cell mass and include the use of antigen specific HSP60 and GAD65 peptides and non-antigen specific anti CD3 and CD20 monoclonal antibodies.

Therapeutic interventions targeting the restoration or regeneration of beta cell mass include approaches such as transplantation of pancreatic islets, use of pharmacological agents (GLP-1 receptor agonists), stem cell and gene therapy (64). (Fig 1, Table 2).

To date, no primary or secondary interventions have shown any real benefits but some tertiary interventions of antigen-specific or non-specific immune therapies indicated that modulation of islet specific autoimmunity in humans and delay of insulin secretion loss in the short term after the onset of disease may be achievable. Due to the complex nature of the

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disease, it is conceivable that a designed approach of combined immune-based therapies that target suppression of beta cell specific autoreactivity with maintenance of immune tolerance, coupled with direct prevention of beta cell loss and/or beta cell regeneration will be required to cause remission/reversal of disease in a durable fashion (65). Table 2 summarises the different stages of prevention for T1D.

Table 2: Primary, secondary and tertiary attempts at prevention or cure of type 1 diabetes Prevention

phase Disease

phase Objectives of

intervention Targeted

subjects Markers Examples of trials Primary Pre-disease

Genetic risk stage

Avoid or neutralize environmental triggers

Infants and pregnant women

Genetic TRIGR (59) NIP (56) BABYDIET(66) Pre-POINT (67) FINDIA (68)

Secondary Sub-clinical disease Immune aggression and ongoing beta cell destruction

Prevent, arrest or delay beta cell destruction

Relatives of type 1 diabetes patients and general population

Immune Hormonal

ENDIT (62) DPT (61;69) INT-II (56)

Tertiary Clinical disease Clinical onset Impending chronic complications

Preserve and/or restore residual beta cell mass/function Restore or increase beta cell mass through transplantation

Type 1 diabetic patients

Metabolic Anti-CD3 (70-72) Anti-CD20 (73) GAD (74;75) HSP60 (76) Islet transplantation (77)

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1.2 Inflammation (insulitis) in type 1 diabetes

1.2.1 Induction of insulitis and innate immune response

While it is widely accepted that genetic susceptibility is the main prerequisite for developing T1D, the penetrance of a susceptible phenotype is determined by environmental factors. Among the environmental factors being studied for their influence on the development of T1D, virus infections have figured prominently in epidemiological studies (78-80). There are indirect and direct evidence for viral infection of the pancreas in T1D. An example of indirect evidence is the hyper-expression of HLA Class I and IFN-α within islets of recently diagnosed diabetic children (81). These markers are absent in normal islets and are referred to as the “viral signature” since they are typically present after a viral infection (82).

The islet-specific MHC class I expression would render the beta cells suitable targets to CD8 T cells that are known to be an integral part of insulitic lesions. An example of direct evidence of viral participation in T1D are the immunohistochemical traces of enteroviral protein in three out of six pancreatic islets from recent-onset T1D patients (83), a finding extended by a larger study (84).

Though the possible contribution of a virus infection to trigger islet autoimmunity (step 1 of the disease) still needs to be clarified, the expression of toll-like receptor 3 (TLR3) is upregulated in beta cells by double stranded RNA (dsRNA) (85;86) a by-product of viral replication. TLRs and retinoic acid-inducible gene-like (RIG-like) receptors such as RIG-I, melanoma differentiation associated gene (MDA-5) are pattern-recognition receptors (PRRs) that are involved in the innate immune system. TLR3 and TLR4 are highly expressed in mouse and human pancreatic islets (85;87;88). Exposure of human islets to coxsackievirus B5 or to inflammatory cytokines such as IFN-α or IFN-γ and IL-1β leads to the upregulation of expression of TLR3, RIG-I and MDA-5 (89;90), while INS-1E cells and primary rat beta cells increase expression of MDA-5 in the presence of dsRNA (91). Intracellular and extracellular dsRNA (mainly derived from damaged or dying cells) can both bind to TLR3 while intracellular dsRNA may use alternative routes such as activation of MDA-5. Downstream of these activated PRRs are complex molecular responses such as induction of ER stress and activation of the transcription factors nuclear factor-ĸB (NF-ĸB) and interferon regulatory factor-3 (IRF-3) (28;92;93). This activation leads to the production of type 1 interferons such as IFN-α or IFN-β resulting in the paracrine activation of the transcription factor signal transducer and activator of transcription 1 (STAT1) and subsequent overexpression of MHC class-I antigens. This culminates in further release of a wide variety of cytokines and

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chemokines (86;89;94;95). The release of such chemotactic molecules and cytokines will lead to the attraction and activation of local immune cells such as macrophages, natural killer (NK) cells and dendritic cells, which secrete pro-inflammatory cytokines such as IL-1β and TNF-α.

These proinflammatory cytokines may lead to the increased expression of miRNAs such as miRNA-29 a/b/c which leads to impaired insulin release and beta cell apoptosis (96).

Regulators of alternative splicing (AS) are also modulated by cytokines such as neuro- oncological ventral antigen 1 (Nova1) which affect gene expression (13;97). It is probable that local inflammation together with intra- and extracellular viral defences contain most of the viral infections, thus restoring normal homeostasis in the islet (28). In some genetically susceptible individuals, however, these attempts to eradicate the viral infection can trigger an exaggerated inflammatory response leading to progressive inflammation with recruitment of the adaptive immune system and prolonged beta cell destruction (28).

Endogenous ligands may also start the inflammatory process by binding to PRRs (98).

For instance, apoptotic mouse beta cells undergoing secondary necrosis may activate T cell immunity through a TLR2-initiated signaling pathway. Interestingly, two mouse models with TLR2 deletion did not develop autoimmune diabetes after beta cell injury. This was due to impaired activation of T cells by antigen presenting cells (99). There is also indication that TLR4 may participate in the development of diabetes as islets isolated from TLR4 deficient mice are protected from allograft rejection when transplanted into another mouse strain (100).

Although TLR2 and TLR4 may participate in the development of T1D as indicated above, their involvement may involve complex interactions between the genetic background, enteric bacteria and the innate immune response (101).

1.2.2 Adaptive immune response

Virus infections or other “danger signals” such as components of dying cells may elicit an innate immune response through the generation of exogenous or endogenous ligands for the PRRs on the beta cell surface as described above. This will lead to intracellular responses such as cytokine and chemokine production, accumulation of unfolded proteins, decrease of beta cell function and ER stress resulting in increased beta cell death and local inflammation (28). The dying beta cells probably release immunostimulatory ‘danger’ signals, physiologically aimed at eliminating the initial harmful factor. This may lead to transition to adaptive immune response through the enrolment of antigen presenting cells (APCs) and the establishment of a pro-inflammatory local environment (IFN, IL-1β, and chemokines) to attract other immune cells (28). Priming of naïve CD4+ T cells in the pancreatic lymph nodes

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(pLN) by islet antigens presented by APCs would be the first event in initiating islet autoimmunity (3;21). Islet antigen presentation in pLN has been demonstrated in mouse models (102;103) and evidence of such antigen recognition has been shown in T cells from draining pancreatic lymph nodes in T1D subjects (104;105). Beta cell apoptosis has been suggested to be a required step for T-cell activation (106) but the detailed mechanisms involved in human disease remain unclear. It is conceivable that during the early stages of insulitis, initiation of a full fledged adaptive immune response will either lead to protracted autoimmune response due to defective resolution (such as in an individual with genetic disposition) or may resolve and maintain islet integrity (28). Expanded T cells from pancreatic lymph nodes of type 1 diabetic subjects were shown to recognize an insulin epitope (104;107) and expansion of Th17 cells and functional defects in T reg cells have been shown to be key events occurring in the pancreatic lymph nodes of T1D patients (105).

In the NOD mouse (108) and BB rat (109), dendritic cells (DCs) are the first cells to infiltrate the islets. Similar observations have been made in humans with T1D (110). Of note, DCs may cross-present peptides derived from apoptotic cells directly onto MHC class I molecules, without processing these in the cytosol (111). Thus, APCs such as DCs may take up antigens from dying beta cells during local inflammation and present them to naïve T cells in the pLN and thus prime them to initiate an adaptive immune response. This has not been fully demonstrated in humans; but the expression of beta cell autoantigens such as proinsulin, GAD, and IA-2 has been detected in human peripheral DCs (112) and T cells from pancreatic lymph nodes of T1D subjects (104).

In the pLN, the APCs loaded with beta cell antigens present them to naïve CD4+ T cells. The primed CD4+ T cells proliferate and differentiate into several subsets, such as type 1 CD4+ T cells (Th1), IL-17-producing CD4+ T cells (Th17), and Treg cells. These primed CD4+ T cells help to sustain CD8+ T cell responses and to activate B cells into plasma cells.

In order to expand into pro-inflammatory subtypes (Th1 and Th17), CD4+ T need a supporting cytokine milieu made up of IL-6 and IL-23 (for Th17 cells (113)) and IL-12 (for Th1) (114). Th1 cells secrete IFN-γ and TNF-α (115). Th17 are potent inducers of tissue inflammation and autoimmunity (116) and they play a role in islet destruction, as is reported for the NOD mouse (117) and have been shown recently to be involved in human T1D (118).

Activation and differentiation of naïve CD8+ T cells to antigen-specific cytotoxic T cells (CTLs) is dependent on “cross-priming”, i.e the cognate recognition of the same antigen by the CD8+ and the CD4+ T cells on the same APC (119). Interaction between the CD40 on an

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activation of the CD8+ T cells (120) and increases the local production of pro-inflammatory cytokines such as TNF-α and IL-12 (121). Cognate interaction between B cells and activated CD4+ T cells will initiate the B cell differentiation into plasma cells which secrete immunoglobulins (122).

Primed beta-cell-specific effector T cells home to the pancreas reaching the beta cells.

The molecular basis for this directed migration (homing) of autoreactive T cells to the islets and for endothelial transmigration is not completely understood. It has been proposed that T cells can display a specific tissue tropism through a distinct ‘homing receptor pattern’

acquired at the site of priming (123). Upon second contact with a target antigen in the islet, CTLs are retained inside the islet tissue and initiate insulitis (124). In the islets, beta cell specific CTLs may recognize antigens expressed on beta cells in association with MHC class I molecules (114). These primed immune cells homing to the pancreas produce a variety of chemokines that direct leukocyte migration and activation during the transition to adaptive immunity (28). Increased islet levels of CXCL10 (or IP-10), CCL2 (or MCP-1), CCL20, and IL-15 mRNA and/or proteins are detectable in the NOD mice during the pre-diabetic stage (28;125-128). In NOD and BB rats, activated macrophages are the first to infiltrate the islets and their depletion or inactivation prevents diabetes development (129). Chemotactic mediators such as CXCL10 and CCL2 attract macrophages and probably contribute to their early recruitment in the islets of NOD mice as mentioned above. The early infiltrate in NOD mice have also been shown to consist of activated CTLs which are probably under the chemottractant effects of IL-1 (130), CXCL10 and CCL2 (131). Interestingly, high basal levels of CCL2 produced by human islets are prognostic of poor clinical outcome following islet transplantation in T1D patients (132).

In the NOD mice, Th1 cells express the CCR5 receptor and its ligands CCL3, CXCL10, as well as CXCL1 (or Groα), CCL2, CCL7 and CCL12 (133;134). Of note, Th1 cell derived chemokines (CCL3, CCL4 and CXCL10) levels are increased in the serum of recently diagnosed T1D patients (135-137). Beta cells themselves produce homing ligands.

Isolated rat beta cells exposed to IL-1β+IFN-γ or to dsRNA or human islets exposed to IL- 1β+IFN-γ upregulate expression of CCL2, CXCL10, CCL20, CX3CL1 and IL-15 and secrete several of these chemokines and cytokines into the culture medium (28;89;95). The expression of chemokines in beta cells is mainly regulated by the transcription factors STAT1 (138) and NF-ĸB (139).

During inflammation, islet endothelium increases the expression of surface adhesion molecules that facilitate vascular permeability and the recruitment of effector cells. T cells

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adhere and migrate to the islet through the interactions of T cell surface molecules (integrins) such as leukocyte function-associated antigen-1 (LFA-1) and very late activation antigen-4 (VLA-4) with their counter ligands on vascular endothelial cells (VEC), such as intercellular adhesion molecules (ICAM) and junctional adhesion molecules (JAM-1); these molecules play a major role in the homing of diabetogenic T cells to the pancreas in the NOD mouse (114). This hyper-expression of adhesion molecules is documented in new-onset diabetes pancreas but may not completely explain the observed enrichment of infiltrating autoantigen- specific T cells to the islet (114).

1.2.3 Amplification, maintenance or resolution of insulitis

During insulitis, beta cells are not passive by-standers. There’s a “dialogue” between the immune cells and the target beta cells during which activated macrophages, NK cells and T cells produce cytokines such as IL-1β, IFN-γ and TNF-α which induce beta cells to release chemokines and stimulatory cytokines (28). As the islet invasion progresses, these chemokines released by beta cells and invading immune cells recruit more chemokine- attracted macrophages and T cells which contribute to the recruitment of more immune cells that also release multiple chemokines and pro-inflammatory cytokines. These inflammatory signals create an overall immuno-reactive environment that modifies DC phenotype (140), shifts CD4+ T cells towards a “Th1- and Th17-like” responses which promote the expansion of CTLs, and shelters the immune cells from peripheral tolerance (3;141;142). If this vicious circle is not interrupted, insulitis will be amplified and maintained by the continuous recruitment of activated immune cells. This will lead to accumulation of immune cells and their cytotoxic mediators in the islets that may act synergistically to destroy the beta cells (28). In the later stages, the destructive process may be worsened in the course of beta cell failure as the hyperglycemic environment may locally enhance GAD and insulin epitope presentation (143-145).

In some individuals who develop mild insulitis, the inflammation may be resolved and beta cell function regained. For example, in individuals in which CD4+ T cell expansion and differentiation is under the influence of IL-4, IL-5, and IL-25, these cytokines might lead to a decrease in inflammation (114). Resolution of inflammation is also evidenced by the observation that some autoimmune positive individuals with impaired beta cell function seem to regain normal beta cell function when followed prospectively (146) and that most individuals who are islet autoantibody (mostly one autoantibody) positive do not show histological signs of insulitis in post-mortem examination (147).

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Fig 2 provides a hypothesis for the events that may occur during insulitis/inflammation in T1D, the initiation and the recruitment of the innate and adaptive immune responses.

Fig 2: Schematic view of hypothetical immuno-pathogenesis of beta cell destruction: Binding of endogenous or exogenous ligands to the PRRs (TLR, RIG-I, MDA5) results in the activation of transcription factors such as STAT1 and NF-ĸB which induce the release of chemokines and cytokines thus recruiting and activating immune cells. These immune cells home to the pancrease and produce cytokines such as IL-1β, TNF-α and IFN-γ which increase activation of key transcription factors, activate miRNAs such as miRNA-29 a/b/c and upregulate AS regulators such as neuro-oncological ventral antigen 1 (Nova1). Downstream of these modified pathways is the upregulation of MHC molecules resulting in increased presentation of modified antigens, increase in ER stress, downregulation of beta cell function (e.g insulin release) increased cytokine and chemokine production and increased beta cell apoptosis. The dying beta cells may act as “danger signals” thus attracting more immune cells. Signals from dying beta cells are presented by antigen presenting cells (APCs) such as dendritic cells (DCs). DCs migrate to the pancreatic lymph node (pLN) where they present peptides to naive T helper cells leading to their activation and proliferation into type 1 (Th1) helper cells, IL-17-producing helper cells (Th17), regulatory T (Treg) cells, cytotoxic T cells (CTL), B and plasma cells (PC), and thus activation of different immune cell subsets by cytokines. The activated autoreactive immune cells then migrate from pLNs to the islets.

There is also cross talk with the periphery through production of autoantibodies by the plasma cells and by the circulation of primed T cells which can be detected in the peripheral blood.

Once in the islet, these immune cells destroy beta cells through cytokine- and perforin/granzyme-mediated mechanisms. If this inflammatory environment is maintained/amplified by recruitment and activation of more immune cells, the vicious cycle

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will result in selective and progressive destruction of beta cells eventually leading to clinical onset of T1D. This figure was adapted from refs (28;96;114;148).

1.3 Inflammation and beta cell loss in type 1 diabetes 1.3.1 Inflammation and apoptosis

T1D develops as a result of selective and progressive destruction of pancreatic beta cells. As described above, the pancreatic beta cells are destroyed by infiltrated autoreactive immune cells. Beta cell injury in the course of insulitis is caused by both exposure to soluble mediators such as cytokines, nitric oxide (NO) and other reactive oxygen species, and direct cell-to-cell contact with activated immune cells (130). There is increasing evidence that apoptosis is the main mode of beta cell death in T1D (28;129;130;149).

1.3.1.1 Apoptotic pathways

Fas and its ligand, FasL, are proteins belonging to the TNF family which play a major role in apoptosis induction (150). Binding of Fas by FasL results in apoptosis through the activation of the caspase 8 and the downstream caspase 3 (extrinsic pathway of apoptosis), leading to DNA fragmentation and cell death (151). In line with this, activated CD4+ and CD8+ T-cells express FasL, which after binding to the Fas receptor on beta cells causes beta cell apoptosis. In NOD mice, FasL-induced beta cell death was shown to be caspase dependent as Fas induced cell death was abrogated by the caspase inhibitor, z-VAD-fmk (152) or by suppression of caspase expression in beta cells (153).

The main cellular source of FasL are the immune cells but beta cells themselves can express FasL (154). In vitro studies have shown that cytokines, such as interleukin IL-1β upregulate Fas expression on beta cells in an NO-dependent fashion (155). Analysis of human biopsies from T1D patients showed Fas expression only on beta cells of islets with insulitis, suggesting that infiltrating immune cells induce Fas expression in these cells (156). In line with this, in vitro studies revealed that only beta cells previously treated with cytokines die when exposed to FasL (154;157) and that diabetogenic CD4+ T cells specifically kill cytokine-treated beta cells expressing Fas (158).

Though Fas has been postulated to play an important role in the beta cell demise in T1D, experiments aimed to evaluate the role of Fas/FasL pathway in vivo yielded controversial results. Several studies have reported a significant protection from insulitis and/or diabetes in mice lacking Fas (159;160) or FasL (161) or treated with anti-FasL antibody (162;163) indicating a role for Fas/FasL pathway in the development of diabetes. On

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the other hand, other studies have shown that the Fas/FasL pathway is not the major effector in T-cell-mediated beta cell death (164;165). Moreover, Fas deficient islets transplanted into diabetic mice are only minimally protected from the destructive immune attack (166;167) and Fas deletion in perforin-deficient NOD mice did not reduce the incidence of diabetes when compared to the wild type (WT) control NOD mice (167).

In conclusion, the Fas/FasL pathway was initially considered as the most important death effector of beta cells in T1D. However the experiments described above cast doubt on such a hypothesis. Other pathways probably play a more important role such as the combinations or synergism between IFN-γ and TNF-α or IL-1β (28;129).

Another way by which CTLs can induce apoptosis is via the secretion of perforin (114;168). Perforin is a transmembrane molecule which forms pores through which granzyme B granules (serine protease secreted by CTLs) are delivered into the target cell. Granzyme B activates the BH3 only protein Bid, leading to cell death (168). Activation of Bid stimulates caspase 8 which can lead to cleavage of caspase 3 which then cleaves the inhibitor of caspase- activated DNase (ICAD) and other key proteins, leading to cell death. Activated ICAD translocates to the nucleus where it fragments DNA contributing to cell death (169).

Granzyme B activation of Bid can also lead to cell death in a caspase-independent way. Here, activated Bid targets the outer mitochondrial membrane triggering cytochrome c release and subsequent apoptosis via caspases 9 and 3 activation (intrinsic or mitochondrial pathway of cell death) (169). Studies performed with CTLs from T cell receptor (TCR) transgenic mice have highlighted the role of perforin-mediated cytotoxicity in in vitro beta cell destruction.

For example, the perforin inhibitor concanamycin A was able to block perforin-mediated death of human pancreatic islet cells by CTLs in vitro (170) and reduced incidence and delayed onset of diabetes was observed in perforin-deficient NOD mice (171). Beta cell destruction by perforin may be involved in more advanced stages of the beta cell loss (114).

Cytokines play a major role in the development of T1D through direct cytotoxicity or indirectly by modulating the activation, homing and effector functions of inflammatory cells as discussed above. This role was confirmed by the demonstration that suppression of cytokine signaling within beta cells (172) or use of cytokine blockers (173;174) prevents mice from developing diabetes despite the presence of insulitis. More specifically, the use of antibodies/or soluble cytokine receptors against IFN-γ, TNF-α and IL-1β inhibited the development of autoimmune diabetes in NOD mice or BB rats (175-177). Another evidence for the role played by pro-inflammatory cytokines in the development of T1D is the finding that transgenic mice expressing IFN-γ in beta cells develop severe insulitis leading to beta cell

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