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Regulatory T Cells and Mechanisms of Immune Regulation in Type 1 Diabetes

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Regulatory T Cells and Mechanisms of Immune Regulation in Type 1 Diabetes
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BRUSKO, TODD MICHAEL
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2008

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Blood ( jstor )
Cells ( jstor )
Cytokines ( jstor )
Diabetes complications ( jstor )
Diseases ( jstor )
In vitro fertilization ( jstor )
Insulin ( jstor )
Protected health information ( jstor )
Research studies ( jstor )
Type 1 diabetes mellitus ( jstor )
City of Indian Rocks Beach ( local )

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University of Florida
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University of Florida
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Copyright Todd Michael Brusko. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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8/31/2008

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REGULATORY T CELLS AND MECHANISMS OF IMMUNE REGULATION IN TYPE 1 DIABETES By TODD MICHAEL BRUSKO A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Todd Michael Brusko

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To my wife, for her unrelenting support, encouragement, and love; as well as to all my instructors, for their ability to not only teach the fundamentals of science but to also inspire the curiosity and determination that lead me to earn a doctorate

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ACKNOWLEDGMENTS It is with great appreciation and sincere thanks that I acknowledge the following individuals whose contributions to various aspects of my professional and personal life made this manuscript possible. For all these contributions, whether by technical assistance, intellectual help, or simple support, I am infinitely grateful for your assistance throughout the years. I thank my mentor, Dr. Mark Atkinson, for his contributions to my professional and personal development through the years. I feel fortunate to have learned about the immunology of type 1 diabetes from one of the foremost pioneers in the field. Perhaps even more important than his scientific mentorship are the lessons that I have learned from Dr. Atkinson about how to conduct myself as a colleague, future investigator, and most importantly individual. The lessons from his character and conviction will serve as a guide for my actions well into the future. I am also grateful to my other committee members: Michael Clare-Salzler, Eric Sobel, and Sihong Song, for their time, efforts, advice, and support. I would also like to thank all of the other members of the Atkinson laboratory, both past and present, for their technical contributions and for making my graduate career enjoyable. I am deeply grateful for the ability to work side-by-side with Clive Wasserfall through the years. His near omniscient knowledge of immunology and techniques has served as a great resource throughout my project. Indeed, working with him has made science enjoyable, and I will continue to appreciate his friendship and support in the iv

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future. In addition, I wish to recognize the friendship and contributions of Clare Zhang, Brant Burkhardt, Matthew Powers, Jeff Cross, Matthew Parker, Matthew Kapturczak, Kevin Goudy, Fletcher Schwartz, Kieran McGrail, Hilla-Lee Viener, Joanne Anderson, Marcus Moore, Michael Stalvey, and every other colleague that I have worked with. I am also deeply indebted for all of the clinical support I have received through the years from the diabetes research program staff at the University of Florida. I wish to thank all the doctors and nurses of both adult and pediatric endocrinology for their assistance in patient recruitment. I am grateful to all the patients with diabetes, and healthy controls, who contributed to my research. Without their generosity and courage, none of these studies would have been possible. I am indebted to Neal Benson for his excellent support and assistance in flow cytometric analyses and sample separations. Finally, I wish to thank my family and friends for their support in my personal and professional development. They have provided support, helped me to overcome challenges and adversity, and ultimately pushed me to achieve this goal. I will certainly miss my classmates and friends I have gained through the years, but I would like to extend a special thanks to Michael Poulos for his help and support, and for being a true friend. I thank my parents for instilling within me a strong work ethic as well as holding high expectations. Lastly, I wish to thank my wife and her family, as well as my brother and his wife for their support. v

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES .............................................................................................................ix LIST OF FIGURES .............................................................................................................x ABSTRACT ......................................................................................................................xii CHAPTER 1 INTRODUCTION........................................................................................................1 Type 1 Diabetes............................................................................................................1 Incidence of Type 1 Diabetes................................................................................2 Impact of Type 1 Diabetes....................................................................................2 The Treatment of Type 1 Diabetes........................................................................3 Autoimmune Basis for Type 1 Diabetes...............................................................4 Type 1 Diabetes: A Disorder Involving Failed Immunoregulation.......................5 Regulatory T Cells and Mechanisms of Immune Regulation.......................................6 Regulatory T Cells: Functions and Characteristics...............................................7 Regulatory T Cell Development and Maintenance...............................................8 FOXP3 as a Marker of CD4 + CD25 + Regulatory T Cells......................................9 Strategies for the Prevention and Reversal of Type 1 Diabetes: Potential Benefits by Studies of Immunoregulation.......................................................12 Summary.....................................................................................................................13 2 GENERAL METHODS.............................................................................................14 Protocols for Patient Recruitment and Sample Collection.........................................14 Phenotypic Analysis of T Cells by Flow Cytometry..................................................15 In Vitro Suppression Assay........................................................................................17 Cell Purification...................................................................................................17 Suppression Assay Co-culture System................................................................18 Cell Culture.........................................................................................................18 Multiplex Analyte Detection......................................................................................19 Cytokine Determination from Suppression Assay Supernatants.........................19 Serum Analyte Determinations...........................................................................19 Purification of Genomic DNA....................................................................................20 vi

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Statistical Analyses and Software...............................................................................21 3 ANALYSIS OF REGULATORY T CELL FREQUENCIES....................................22 Introduction to Studies of CD4 + CD25 + Regulatory T Cells: Lessons from Animal Models of and Humans with Type 1 Diabetes.......................................................22 Methods for Phenotypic Analysis by Flow Cytometry..............................................26 Analysis of CD4 + CD25 + T cells..........................................................................26 Analysis of FOXP3 Expressing T cells...............................................................27 Extended Phenotypic Analysis............................................................................27 Results.........................................................................................................................28 CD4 + CD25 + T Cell Frequencies in Peripheral Blood are Stable Over Short to Intermediate Periods of Time...........................................................................28 Frequencies of CD4 + CD25 + T Cells in Peripheral Blood Associate with Age...29 Analysis of FOXP3 + T Cell Frequencies.............................................................32 Extended Phenotypic Analysis of CD4 + CD25 + and CD4 + CD25 T Cells...........37 Discussion...................................................................................................................39 Conclusions.................................................................................................................40 4 ANALYSIS OF REGULATORY T CELL FUNCTION IN TYPE 1 DIABETES...42 Introduction to Studies of CD4 + CD25 + Regulatory T Cell Function in Humans with Type 1 Diabetes.............................................................................................42 Methods......................................................................................................................44 Subjects................................................................................................................44 Suppression Assay...............................................................................................44 Cytokine Analysis...............................................................................................46 Analysis of FOXP3 + T cells in Peripheral Blood and the Degree of in Vitro Suppression......................................................................................................46 Results.........................................................................................................................46 Deficient Suppression by Treg in Patients with T1D..........................................46 Altered cytokine profile from stimulated cultures in patients with T1D.............48 Frequencies of CD25 + FOXP3 + T cells in Peripheral Blood Do Not Determine the Degree of in Vitro Suppression..................................................................51 Discussion...................................................................................................................53 Summary.....................................................................................................................55 5 EXTENDED ANALYSIS OF REGULATORY T CELL FUNCTION....................56 Introduction: The IL-2/CD25 Axis and Treg Function..............................................56 A Dichotomous Role for IL-2 in Tolerance and Immunity.................................57 Treg Require Stable CD25 Expression and Signalling.......................................58 Methods......................................................................................................................59 In Vitro Suppression Assays under Serum-Free Media Conditions....................59 Cell Purifications.................................................................................................60 Cell Culture.........................................................................................................60 Soluble CD25 and Matrix Metalloproteinase Determinations............................61 vii

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In Vitro Expansion Experiments.........................................................................61 Results.........................................................................................................................62 Soluble CD25 Levels in Serum of Patients with T1D.........................................62 Serum is Required for Suppression of Proliferation by Treg..............................63 Ontogeny of Soluble CD25 during the Suppression Assay.................................66 Regulatory T cells Retain the Capacity to Suppress Effector Cytokine Production under Serum-free Conditions........................................................67 Protease and Protease Inhibitor Control of Suppression.....................................68 The In Vitro Expansion of Regulatory T Cells...................................................70 Discussion...................................................................................................................72 Conclusions.................................................................................................................73 6 DISCUSSION AND CONCLUSIONS......................................................................74 Discussion...................................................................................................................74 Conclusions.................................................................................................................78 APPENDIX A INFORMED CONSENT FORM TO PARTICIPATE IN RESEARCH....................80 B INSTITUTIONAL REVIEW BOARD APPROVAL LETTER................................93 LIST OF REFERENCES...................................................................................................94 BIOGRAPHICAL SKETCH...........................................................................................108 viii

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LIST OF TABLES Table page 3-1 Regulatory T cell frequencies in type 1 diabetes.....................................................25 3-2 Patient demographics...............................................................................................27 4-1 Regulatory T cell function in type 1 diabetes..........................................................43 4-2 Cytokine elaborations monitoring regulatory and effector T cell function..............50 ix

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LIST OF FIGURES Figure page 3-1 Representative flow cytometric plots from a normal healthy control showing expression of CD4 and CD25...................................................................................28 3-2 Relationship between CD4 + CD25 + T cell frequency and age at time of testing. ...30 3-3 Frequencies of CD4 + CD25 + T cells and CD4 + CD25 +Bright T cells do not differ significantly between controls and patients with T1D when corrected for age.......31 3-4 Flow cytometric analysis of FOXP3 from fresh peripheral blood. ........................33 3-5 Analysis of T cell subpopulations reveals an association between age and their frequency in peripheral blood..................................................................................34 3-6 Frequencies of FOXP3 + regulatory T cells do not differ in subjects with T1D.......36 3-7 Expression of CD45RA, CD45RO, and CD62L......................................................37 3-8 Markers of cellular phenotype associate with subject ages......................................38 4-1 Procedure for isolating functional CD4 + CD25 + and CD4 + CD25 T cells for use during the in vitro suppression assay.......................................................................45 4-2 A representative suppression assay from a normal health control subject...............47 4-3 Functional suppression by CD4 + CD25 + regulatory T cells is deficient in patients with T1D..................................................................................................................48 4-4 Altered cytokine profile from stimulated cultures in patients with T1D.................49 4-5 The frequency of CD25 + FOXP3 + T cells in peripheral blood does not correlate with the degree of suppression by isolated CD4 + CD25 + T cells..............................52 5-1 Elevated levels of soluble CD25 (sCD25) in the serum of patients with T1D........62 5-2 FACS isolation of functional Treg and Teff cells....................................................64 5-3 CD4 + CD25 + Regulatory T cells require serum for suppression of proliferation.....65 x

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5-4 Production of soluble CD25 (sCD25) correlates with cellular proliferation in vitro in a time-dependent fasion...............................................................................66 5-5 Regulatory T cells maintain the capacity to suppress certain effector T cell cytokines under SFM conditions..............................................................................67 5-6 Concentrations of matrix metalloproteinase-9 (MMP-9) and matrix metalloproteinase-7 (MMP-7) correlate with sCD25 levels and cellular proliferation during the in vitro suppression assay..................................................69 5-7 Selective inhibition of matrix metalloproteinases augments the suppressive index.........................................................................................................................70 5-7 Phenotypic analysis of in vitro expanded human Treg and Teff cells.....................71 xi

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy REGULATORY T CELLS AND MECHANISMS OF IMMUNE REGULATION IN TYPE 1 DIABETES By Todd Michael Brusko August 2006 Chair: Mark A. Atkinson Major Department: Medical Sciences – Immunology and Microbiology Type 1 diabetes (T1D) is characterized by the autoimmune destruction of insulin producing pancreatic beta cells. Regulatory T cells (Treg) play a central role in maintaining dominant peripheral tolerance within the immune system and in averting autoimmunity. Therefore, these studies investigated the peripheral blood frequency and function of Treg in patients with T1D, first-degree relatives, and normal healthy controls. Whether assessed by the frequency of CD4+CD25+ T cells or the lineage-specific marker FOXP3, no deficiency in the frequency of Treg was observed in patients with T1D. We did, however, identify a positive correlation between the frequency of CD25+FOXP3T cells and age in all subject groups. The frequency of CD25+FOXP3+ T cells was independent of age. These age-associated increases in CD25 intermediate cells parallel a shift in the immune repertoire from a nave phenotype (CD45RA+) to a more antigen experienced one (CD45RO+). From a functional standpoint, Treg from patients with T1D were markedly reduced in their ability to suppress proliferation of autologous xii

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effector T cells in vitro. This T1D-associated defect in suppression was linked with reduced production of IL-2 and IFNby effector T cells and TGFby Treg. In addition, these studies highlight novel and relatively uncharacterized functional properties of Treg in vitro. Specifically, Treg maintain a stable form of membrane-bound CD25, while effector T cells transiently upregulate CD25 and then release it into culture medium. In addition, we identify a critical requirement for serum factors in full T cell activation and the mechanism of suppression by Treg. Collectively, these studies suggest that age strongly influences the development of CD4+CD25+FOXP3T cells, and that function, rather than frequency, may represent the means by which these cells associate with T1D. xiii

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CHAPTER 1 INTRODUCTION This introduction discusses the incidence, individual and social impact, and characteristics of type 1 diabetes (T1D). In addition, this introduction will present background supporting the notion of an autoimmune basis for T1D as well as provide a rationale for studying mechanisms of immune regulation, particularly those involving regulatory T cells (Treg), in the pathogenesis of the disease. Type 1 Diabetes Diabetes Mellitus refers to a heterogeneous group of metabolic disorders commonly characterized by hyperglycemia (elevated blood glucose levels) resulting from a deficiency in either the production or action of the endocrine hormone insulin (1). Insulin is a dimeric protein produced within the pancreatic cells of the Islets of Langerhans which facilitates glucose uptake and utilization by cells following elevations in blood glucose levels (2). Therefore, any disruption in either the production or function of insulin results in uncontrolled elevations in blood glucose levels and the subsequent symptoms associated with hyperglycemia. Two major forms of diabetes exist: type 1 diabetes, which is associated with deficient insulin production, and type 2 diabetes, which results primarily from defects in insulin action (3). 1

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2 Incidence of Type 1 Diabetes It is estimated that over 18 million Americans or 6.3% of the population have diabetes, with approximately 1 million Americans or over 2800 people each day, developing the disease (1). However, type 1 diabetes is much less common that type 2 diabetes and represents approximately 10% of the total population with diabetes. In the United States, more than 150,000 children younger than 18 years of age have T1D with an incidence in U.S. children between 15 and 17 per 100,000/year (4). Each year in the U.S., 10,000 to 15,000 new cases of T1D are diagnosed (5). Worldwide, the rates of T1D vary greatly by race and geographical location, representing greater than a 350-fold variation in the incidence rates among a set of 100 different population groups recorded (4). For example, T1D is relatively uncommon in China, India, and Venezuela where the incidence is only 0.1 per 100,000. On the other end of the spectrum, countries like Sardinia and Finland report incidences approaching 37 cases/100,000 per year (4). Perhaps more importantly, the incidence of T1D appears to be increasing throughout the world, particularly in industrialized countries that already report high incidence rates such as Sweden and Norway (4, 5). As far as gender is concerned, T1D unlike many other autoimmune disorders which predominantly affect women, appears to afflict both men and women at relatively equal rates (6). Taken collectively, differences in the disease prevalence and incidence rates among various populations suggest the pathogenesis of T1D is determined by complex interactions between both genetic and environmental factors (5). Impact of Type 1 Diabetes From the perspective of all individuals involved, diabetes poses a profound burden on individuals, families, and society. Diabetes is particularly unique in its presentation, in

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3 that it poses the need for both direct immediate care of diabetes related symptoms, and the subsequent care of the debilitating long-term effects of disease related to long-term hyperglycemia (7). Diabetes commonly leads to the development of major health complications later in life including increased rates of cardiovascular disease, nephropathy, retinopathy, and neuropathy. The end financial result is that the direct and indirect costs of diabetes care have been reported to cost the United States over $130 billion dollars as of 2002 (8). Thus, perhaps more than any other disease, the impact of diabetes on the healthcare system is pervasive and affects virtually all disciplines of medicine. Despite the rise in both the incidence and cost of diabetes, many physicians and scientists would argue that there has not been a concomitant increase in the attention to this disease or in the allocation of resources required for its prevention and/or treatment (1). The Treatment of Type 1 Diabetes The 1921 discovery of insulin was initially thought to represent a cure for T1D. However, as evidenced by the increased incidence of complication later in life, this is not the case. In fact, the disease has merely transformed over the years from a fatal condition to a chronic illness (9). Currently, children diagnosed with T1D face a lifetime of frequent glucose monitoring and insulin injections (5). Despite dramatic increases in the technology employed to monitor and treat T1D (examples include continuous glucose monitoring and insulin pumps), no broad-scale safe or effective treatment currently exists to reverse T1D (10). Even islet transplantation, which poses the attractive potential for replacement of cell mass, poses significant challenges and a relatively poor long-term prognosis (11). Thus, the ultimate goal for a cure for T1D remains the hope of bringing a

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4 halt to the autoimmune attack prior to the clinical onset of T1D along with reversal of beta cell loss following disease onset (10). Autoimmune Basis for Type 1 Diabetes Since the mid-1970s, an autoimmune pathogenesis has widely been accepted as the basis for how type 1 diabetes forms; a notion based on studies of patients revealing lymphocytic infiltrates of post-mortem pancreas (i.e., insulitis), islet cell reactive autoantibodies, and genetic susceptibility that includes (to a large extent) genes regulating immune reactivities (10). While autoantibodies to a wide number of beta cell autoantigens (e.g., insulin, glutamic acid decarboxylase, IA-2) are associated with the disorder (12), wherein they serve as serologic markers of disease activity, it is also generally thought that the process of beta cell destruction is intimately associated with T-lymphocytes (13). Indeed, type 1 diabetes can occur following allogeneic bone marrow transplantation from affected probands (14) whereas studies of animal models have been subject to conflicts in both results and interpretations, they do support roles for CD4 + and CD8 + T lymphocytes in these processes (15). At a fundamental level, the processes underlying this autoimmunity have been thought to involve defects in mechanisms of both central and peripheral tolerance (16, 17). Central tolerance to self-antigens involves a clonal deletion of sub-sets of autoreactive T cells in the thymus during development (18). It has been proposed that ineffective self-antigen binding to HLA molecules associated with risk for type 1 diabetes may lead to incomplete deletion of immature autoreactive T cells or alternatively, that insufficient expression of self-molecules (e.g., insulin, glutamic acid decarboxylase) may allow for escape of autoreactive T cells capable of beta cell destruction (19). To impart immune control mechanisms once cells

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5 are in the periphery, mechanisms of anergy or outright deletion (i.e., apoptosis) can be elicited upon encounter with self-antigens. In addition to these mechanisms, distinct lineages of T-cells, taking on the common title of regulatory T cells or “Tregs” has been described and are thought to play a major role in the processes averting autoimmunity (20). Type 1 Diabetes: A Disorder Involving Failed Immunoregulation A growing body of evidence suggests that failure to regulate the immune response in NOD mice and humans plays a major role in the pathogenesis of T1D (21). NOD mice have obvious defects in central and peripheral tolerance (22) and exhibit a variety of abnormalities in immune function (e.g., reduced production of IL-2, proliferative hyporesponsiveness, etc.) (23). Humans with T1D share many similar aspects, with recent interest directed toward lymphopenia (24) being one potential contributor to the disease process. In terms of the cellular basis for this immunoregulatory failure, it is important to note that both NOD mice and patients with type 1 diabetes have potential deficiencies in at least two regulatory T cell populations, NKT cells and CD4 + CD25 + T cells (25). In addition to defects in regulation, developmental and functional defects have also been reported in the antigen-presenting cells (APC) of both NOD mice and human type 1 diabetes patients; including those of differentiation and function of macrophages and dendritic cells (DC) (30). In terms of identifying prototypic outcomes of failed immunoregulation, a large number of studies over the last decade have identified islet antigen reactive T cells in the peripheral blood of patients with type 1 diabetes (36). While early works suggested a degree of disease (i.e., type 1 diabetes) specificity for such reactivities, many recent studies have identified autoreactive T cell populations in healthy

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6 controls or persons with various autoimmune disorders including multiple sclerosis (36–44). Hence, while the deletion of autoreactive T cells within the thymus and the induction of anergy in the periphery may represent major mechanisms in the maintenance of immune homeostasis; the identification in the periphery of autoreactive T cells suggest that additional mechanisms exist to regulate T cell responsiveness. This raises the obvious issue that if pathogenic cells are present in persons with type 1 diabetes, what system or systems are subject to this mechanistic “failure”? To this question, evidence has arisen to suggest that CD4 + CD25 + regulatory T cells may inhibit the expansion and/or effector function of autoreactive T cells. Thus, a hypothesis has developed that the failed immunoregulation of type 1 diabetes may (in part) develop due to either frequency or functionality of the CD4 + CD25 + regulatory T cell repertoire (45). Regulatory T Cells and Mechanisms of Immune Regulation The immune system is composed of extensive collection of cell types which all coordinate to elicit effective immunity (46). One key principle that has come to forefront over recent years is the notion that the maintenance of peripheral tolerance to autoantigens is an active ongoing process (47). T cells possess several key “classes” of regulatory T cells have been described in the literature to participate in immunoregulation, including Tr1 (IL-10 producing), Th3 (TGFproducing), and naturally occurring CD4 + CD25 + FOXP3 + regulatory T cells that suppress through direct cell-cell contact (48). However, T cells do not act alone in processes of immune regulation. Indeed, complex cellular networks coordinate at the immunological synapse to direct responses toward either immunity or tolerance (49). Two key cell types that participate in this process to influence T cell reactivity are antigen presenting cells (APC) and a class of invariant NKT cells (iNKT cells) (49, 50).

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7 Regulatory T Cells: Functions and Characteristics Since the findings of Sakaguchi reporting multi-organ autoimmunity of mice subjected to thymectomy a day 3 of life, multiple studies have suggested that CD4 + CD25 + regulatory T cells function as major regulators of the immune response and impact the development of autoimmunity (51). CD4 + CD25 + T cells (Treg) comprise approximately 5% of the peripheral CD4 + T cell population in mice and humans (20, 53). The mechanisms underlying the action of CD4 + CD25 + regulatory T cells are unclear and as such, are subject to much debate. Why does this remain unclear? In short, the properties of these cells are quite unique. CD4 + CD25 + T cells do not by their nature proliferate in vitro (i.e., anergic) to antigenic stimulation, their suppressive properties require functional activation by antigenic stimulation and polyclonal T cell activation, and the strength of that signal combined with the degree of costimulation all affect the degree of regulator function (54, 55). In addition, another area of confusion revolves around the use of CD25 as marker for regulatory T cells. Unfortunately, to date no definitive surface marker exists for these cells that easily identifies them as “regulatory”, yet the constitutive expression of various markers by this population does distinguish them from un-activated CD4 + CD25T cells (56). Specifically, most CD4 + CD25 + cells constitutively express CTLA-4 and GITR (57, 58). Furthermore, populations of CD4 + CD25 + regulatory cells that are more suppressive in vitro and in vivo have increased expression of CD62L (L-selectin) or CD103 (E7 integrin) and (35, 59). Data by Baecher-Allan et al have reported that only cells expressing a high level of CD25 correlate with the regulatory functions ascribed to the CD4 + CD25 + regulatory T cells described in mice have more recently reported that T cells with the highest suppressor activity express the MHCII marker DR (60, 61).

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8 A majority of studies would suggest Treg control so called “effector T cell” (Teff) proliferation in vitro through direct cell-cell interaction, while TGFand other cytokines may also be involved in these processes (54, 62). In vitro cultures of CD4 + CD25 high T cells with CD4 + CD25 cells results in an inhibition of proliferation in conditions involving sub-optimal stimulation with soluble or plate bound anti-CD3 (20). Indeed, this suppressive affect as well as an induction of proliferation can be averted by increasing the signal strength by provision of strong co-stimulation involving CD28 cross-linking or by addition of exogenous IL-2 (61). Regulatory T Cell Development and Maintenance Mice deficient in MHC class II do not develop functional CD4 + CD25 + regulatory T cells (63). Hence, it would appear that CD4 + CD25 + regulatory T cell development requires high avidity agonistic interaction between T cell receptors and Class II MHC expressed on the thymic stromal cells (64). Many intracellular, surface expressed or secreted molecules have been reported as being involved in the development and/or maintenance of CD4 + CD25 + regulatory T cells. Examples would include (but not be limited to) IL-2, CD28/B7, CTLA-4, STAT-5a, ICOS/ICOSL, OX-40/OX-40L, CD40/CD40L, (27, 65–70). While each may play a significant role, a great deal of interest has recently been directed at IL-2 (71); with studies suggesting an essential role for this cytokine in CD4 + CD25 + T cell development during the neonatal period, and that IL-2 is key to the homeostatic maintenance of Foxp3 + CD4 + CD25 + T cells (72, 73). Studies of mice also suggest that other cytokines, including TGF-, can induce the conversion of CD4 + CD25 cells into CD4 + CD25 + regulatory cells in vitro (74). Using a murine model involving gene delivery, we observed the ability of over-expression of IL-10 to expand the numbers of CD4 + CD25 + T cells in vivo (75). CD4 + CD25 + regulatory T cell development has also

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9 been associated with STAT-1, a transcription factor associated with IFN signaling (76), a finding which suggests the development of this regulatory population of T cells may also be associated with interferons. Proliferation and a prolonged period of CD4 + CD25 + T cell survival can be imparted with lipolpolysaccharide via toll receptor ligand 4 (77). Again, as previously outlined, the interplay between specific cell populations with CD4 + CD25 + also appear to represent major facets of influence, with recent studies suggesting vital roles for activated-IL-2 secreting-CD1d-restricted NKT cells, as well as DC in CD4 + CD25 + T cell activation and function, among others (78, 79). Finally, the Foxp3 transcription factor has recently been shown to play an essential role in CD4 + CD25 + regulatory T cell development (80). FOXP3 as a Marker of CD4 + CD25 + Regulatory T Cells Scurfy mice represent a spontaneous inbred rodent stain that develops a T cell mediated X-linked autoimmune disorder (81). In humans, a clinical syndrome similar to that observed in the Scurfy mouse classified as IPEX (Immunodysregulation, polyendocrinopathy, enteropathy, X-linked syndrome) has been described (82). It has been through investigations of these animals that important assertions regarding the role for Treg cells and the development of autoimmunity have recently been described. Indeed, while autoimmunity can be imparted by adoptive transfer of Scurfy T cells, the disorder can also be reversed by delivery of non-mutant (wild-type) bone marrow (83, 84). In a related way, it is interesting to note that mice undergoing targeted disruption of IL-2 (85), IL-2 receptor (86, 87), TGF (88), or CTLA-4 (89) develop a similar form of autoimmunity that can be adoptively transferred by T cells which can also be reversed with transfer of wild type bone marrow. In terms of our mechanistic understanding of scurfy mice and IPEX, both syndromes have been characterized by the absence or near

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10 absence of regulatory T cells. Similarly, both conditions provide evidence for an inability of existing T cells to suppress the proliferation of T cells in response to antigenic challenge. Studies aimed at the genetic mapping of this defect revealed a key role for point mutations in a forkhead (FKH) transcription factor family member known as Foxp3 (80). Indeed, these Foxp3 mutations do appear responsible for the disease associated phenotype in Scurfy mice and IPEX patients and in addition, established a potential association between Foxp3 and the development of functional regulatory T cells (90, 91). Indeed, this latter notion finds support in a variety of means including the previously indicated studies by Sakaguchi involving reconstitution experiments wherein thymic expression of Foxp3 during CD4 + T cell maturation was observed to be essential for regulatory T cell production (92). Gene delivery studies have also supported this claim as retroviral gene transfer of Foxp3 into Scurfy bone marrow resulted in a correction of the T cell defect (95). While Foxp3 does appear to have some unique properties with respect to its DNA binding domain, the family of FKH transcription factors to which it belongs is extensive (95). Whereas an association between Foxp3 expression and the acquisition of a regulatory T cell phenotype has been reported, it is key to recognize that limited information exists as to the mechanisms underlying the regulation of Foxp3 or its transcriptional targets (96). As previously noted, one key modulator of regulatory T cell function (and potentially FOXP3) may be TGF-, as evidenced by the observation that TGFcan induce FOXP3 expression on human CD4 + T cells in vitro (97). However, it does remain uncertain as to the mechanism by which TGFinduces FOXP3 and functional suppression by Treg, with a least two models being proposed (98, 99). With the first, a

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11 lineage restricted population of Foxp3 expressing T cells would undergo selection within the thymus, while peripheral CD4 + T cells would gain regulatory function through induction of Foxp3 expression induced by TGF (98). Indeed, a number of studies increasingly support a key role for this cytokine in Treg biology including that TGFsignaling is required for the in vivo expansion and immunosuppressive capacity of regulatory CD4 + CD25 + T cells, that TGFmaintains suppressor function and FoxP3 expression in CD4 + CD25 + regulatory T cells, and that TGF non-responsive cells are not subject to regulation by CD4 + CD25 + T cells (100, 101). As FOXP3 has been reported (albeit now controversial, as indicated below) to have exclusive expression within CD4 + CD25 + T cells (16), one could speculate that Foxp3 may represent a superior marker of CD4 + CD25 + regulatory cells over that of CD25. However, one recent study of humans suggested that FOXP3 expression while correlating with CD4 + CD25 + regulatory T cell functions, CD4 + CD25 + T cells generated by antibody mediated stimulation of CD4 + CD25 also expressed FOXP3 and acquired regulatory properties (102). Recently, reagents have been developed that are capable of identifying the linage specific transcription factor FOXP3 at the protein level by FACS analysis. While FOXP3 expression appears less restricted in humans compared to mice (103), its expression (whether naturally occurring from thymic origin or induced in the periphery following tolerogenic conditioning) does none-the-less suggest a demarcation of functional Treg (104). Taken collectively, these studies suggest the potential existence of at least two different pathways for generating CD4 + CD25 + regulatory T cells, the first involving thymic selection while the second would result from immune recognition in the periphery coincident with tolerogenic signaling.

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12 Strategies for the Prevention and Reversal of Type 1 Diabetes: Potential Benefits by Studies of Immunoregulation The prevention and eventual cure for T1D requires a better understanding of the mechanisms of autoimmunity that underlie cell destruction along with the development safe and effective therapeutic interventions that will halt cell destruction (5). Several factors contribute to the lack of an effective treatment. These include, but are not limited to deficiencies in our understand of the immunologic factors that contribute to type 1 diabetes along with an absence of immunologic tools to understand the mechanisms of disease (10). Because of this, an intense degree of research interest has recently been generated to understand the mechanistic pathways that regulate the immune responses and form a state of immunological tolerance, among which CD4 + CD25 + regulatory T cell plays a central role (13). In a simplistic model of tolerance, autoreactive effector (destructive) T cells are kept in “check” by regulatory T cells under normal homeostatic conditions. In the case of T1D, for reasons that are not completely understood, this equilibrium may be disrupted by inappropriate activation of autoantigen-specific effector T cells, eventually leading to cell loss and clinical diabetes. Even when T cell activation finally overrides regulation, hope remains that targeted therapies might restore immunological tolerance by the stimulation of regulatory cells, or elimination of pathogenic effector T cells (105, 106). This therapeutic cellular shift is often linked with a deviation in the cytokine profile from a pro-inflammatory response to one predominated by more immunoregulatory cytokines, such as those of the Th2 and Th3 classes (primarily IL-10 and TGF-, respectively) (107). Several of these therapies are now being tested in clinical trials in prediabetics and/or recently diagnosed diabetes (108).

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13 Summary Type 1 diabetes is a heterogeneous disorder controlled by complex genetic and environmental factors. The natural history of the disease is thought to result from a breakdown in the mechanisms controlling peripheral tolerance, ultimately culminating in the autoimmune destruction of insulin producing pancreatic cells and complete insulin dependence. When considering the impact on the individuals afflicted, the social and economic consequences, or the healthcare burden brought on by its complications, the burden of diabetes is profound. The path to effective therapeutic treatments for the prevention and/or reversal of T1D will likely require an understanding of the mechanisms of autoimmunity that underlie cell destruction. It is with this goal in mind, that this manuscript will seek to elucidate a role for one such cell type which functions to maintain a state of immunological tolerance, that being a population of regulatory T cells (Treg) in the pathogenesis of type 1 diabetes.

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CHAPTER 2 GENERAL METHODS A broad array of cellular, immunological, and molecular techniques were employed in the course of this dissertation project. This chapter outlines some of the most commonly utilized techniques from the major experiments conducted and provides a sufficient degree of detail to facilitate their adaptation and/or replication by other investigators. More detailed descriptions and deviations from these outlined protocols are presented, when applicable, in subsequent chapters. Protocols for Patient Recruitment and Sample Collection Peripheral blood (up to 75 cc) was collected from all study participants to assess markers of cellular and humoral immunity. The study cohort consisted of children (>3 years of age) and adults from the general population and clinics of the University of Florida, College of Medicine. Institutional Review Board approved informed consents and assents were obtained for each study participant prior to sample collection (copies of which are included in appendices A and B). Study participants were classified into four major groups, non-diabetic healthy controls, those with new-onset T1D ( < 4 months post diagnosis), individuals with established T1D (>4 months post diagnosis), and first-degree relatives of persons with T1D at varying degrees of risk for T1D. Patients with T1D were diagnosed according to physician examination and current ADA criteria (3). Healthy controls lacked any autoimmune disorders or related probands with T1D, and were determined to be negative 14

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15 for the presence of either of the T1D associated autoantibodies, anti-glutamic acid decarboxylase (GADA) and anti-IA2 (IA2A) (109). Phenotypic Analysis of T Cells by Flow Cytometry Heparinized whole blood was collected and immediately subjected to methods for cellular staining. 100 l of whole blood was aliquoted (per 12x75mm tube) along with each appropriate test antibody, FITC anti-CD3 (clone HIT3a), PerCP anti-CD4 (SK3), PE anti-CD25 (M-A251), and APC anti-FOXP3 (PCH101). An extended analysis was conducted on a subset of T1D patients and controls with FITC anti-CD3 (clone HIT3a), PerCP anti-CD4 (SK3), PE anti-CD25 (M-A251), and APC labeled anti-CD62L (DREG-56), CD45RA (HI100), and CD45RO (UCHL1). The following isotype control antibodies were used: FITC mouse IgG1 (MOPC-21), PE mouse IgG1 (MOPC-21), PerCP mouse IgG1 (MOPC-21), APC labeled mouse IgG1 (MOPC-31C), mouse IgG 2A (G155-78), and mouse IgG 2B (clone 27). PE QuantiBRITE beads were included in certain runs to determine the levels of CD25 expression on gated cells and to standardize for instrument fluctuations in fluorescence readings (BD Biociences; San Jose, CA). All antibodies and reagents for cytometric analysis were purchased from BD Biociences, with the exception of anti-FOXP3 (eBioscience; San Diego, CA). Following surface staining for 30 minutes (4C), red blood cells were lysed and cells fixed in 2 ml of a combination fixation and lysing solution for 10 min at 23C (BD FACS Lysing solution). The resulting RBC lysed and fixed cell population was then centrifuged at 300 x g for 10 min at 4C. Supernatant was aspirated from the resulting cell pellet, followed by two washing cycles with stain buffer (BD Stain Buffer; containing 1X DPBS, 0.2% BSA and 0.09% Na azide, pH 7.4).

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16 For the subset of patients who were stained for FOXP3, the procedure follows the above outlined procedure for surface staining followed by intracellular FOXP3 staining using the human FOXP3 staining kit (eBiosciences). To the surface stained cell pellet, 1 ml of freshly made fixation/permeabilization buffer was added, pulse vortexed, and allowed to incubate for 30 min at 4C. Following centrifugation, the fixation buffer was removed with two washes in 1 ml 1X permeabilization buffer. To reduce non-specific staining, 2 l of normal rat serum was added to the remaining cell pellet in a total volume of 100 l and incubated for 15 minutes at 4C. Without washing, 20 l of APC anti-FOXP3 (PCH101) or APC Rat IgG2a isotype control were added and allowed to incubate for 30 min at 4C. Unbound antibody was removed with 2 washes in 2 ml 1X permeabilization buffer. The stained cell pellet was finally resuspended in 0.5 ml FACS staining buffer (BD Biosciences) and held in the dark at 4C prior to flow cytometric analysis. Stained cells were analyzed within 24 hr of processing on a four-color BD FACSCalibur cytometer. 5 x 10 4 events were acquired per test when assessing cell-surface phenotypes and 1.5 x 10 5 events acquired when assessing the frequency of FOXP3 expressing T cells. FCS Express (De Novo Software, version 2.200.0023, Thornhill, Ontario, CA) was used for analysis of cytometric data. For regulatory T cell frequency analyses, cells were gated based on scatter to remove large blasting cells and on CD3 to remove monocytes expressing low levels of CD4. Gates for each test marker were established from isotype control antibody staining (standardized to 1 percent). In order to calculate the absolute count of cells analyzed by FACS, a small volume of blood was collected in potassium EDTA containing tubes (Sarstedt) and analyzed for

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17 complete blood counts (CBC) with differential on a Coulter AC•T diff analyzer (Beckman Coulter, Inc., Fullerton, CA). When available, absolute counts were determined by multiplying the frequency of positive cells determined following FACS analysis by the number of lymphocytes x 10 3 /L as determined by CBC. In Vitro Suppression Assay A suppression assay was developed to test the capacity of CD4 + CD25 + regulatory T cells to suppress proliferation and cytokine production by co-cultured CD4 + CD25 Teff cells. Cell Purification Fresh peripheral blood was collected in sodium heparinized vacutainer tubes (BD Biosciences). An accessory cell population was produced by incubating a 3 ml aliquot of blood with 150 l a T cell depletion antibody cocktail (StemCell, Vancouver BC, Canada), followed by density gradient centrifugation according to manufacturer instructions (Cellgro, Herndon, VA). The CD4 + T cell population was purified from the remaining blood volume by negative selection using a CD4 + T enrichment cocktail (Stem Cell) by adding 50 l of cocktail per 1 ml of whole blood. This mixture was allowed to incubate following gentle mixing for 20 min at 23C. Following density gradient centrifugation and two washing cycles in 25 ml 1XPBS (Ca ++ and Mg ++ free) containing 2% human AB serum (Sigma, St. Louis, MO), the “untouched” CD4 + population then underwent a positive selection for CD4 + CD25 + regulatory T cells using CD25 microbeads (Mitenyi Biotec, Bergisch Gladbach, Germany) with separation on the AutoMACS sorter (Miltenyi). CD25 microbeads were added at a volume of 10 l of microbeads and 90 l of run buffer (Miltenyi) per 10 7 starting CD4 + T cells and incubated for 15 min at 4C. Excess CD25 microbeads were removed prior to sorting by washing

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18 the cell pellet in 1 ml run buffer per 10 7 cells, followed by resuspending the pellet in 500 l run buffer for sorting on the AutoMACS. The unlabeled CD4 + CD25 population provided the effector T cell (Teff) population for use in suppression assays. Suppression Assay Co-culture System Regulatory T cells were added in decreasing ratios (1:0, 1:1, :1, and 0:1) to a constant number of Teff cells (5 x 10 3 cells/well). A combination of 5 g/ml soluble anti-CD3 (clone HIT3a) and 2.5 g/ml soluble anti-CD28 (clone CD28.2; eBioscience, San Diego, CA) provided the polyclonal stimulus for proliferation over a six-day culture period. 5 x 10 4 irradiated (3300 rads) T cell depleted accessory cells were also added to each well in a total volume of 200 l. One Ci of 3 H-Thymidine (Amersham Biosciences, Piscataway, NJ) was added at day 5 for the final 16 h of culture to assess proliferation. Supernatants from six replicate wells were collected for each condition at 24 and 48 h, and at day 5 just prior to the addition of 3 H-thymidine to assess cytokine production. Suppression is determined by the reduction of 3 H-Thymidine incorporation in the combination of cells and is calculated by the following equation: Percent suppression= (1 (mean CPM Treg+Teff)/(mean CPM Teff) x 100%). Cell Culture Cells were cultured in RPMI 1640 medium (Cellgro, Herndon, VA) supplemented with 5 mM Hepes, 2 mM L-glutamine, Penicillin (50 g/ml)/Streptomycin (50 g/ml)/Neomycin (100 g/ml) (Invitrogen, Carlsbad, CA), 50 M 2-mercaptoethanol, 5% human type AB serum (Sigma) in U-bottom 96-well plates (Costar, Cambridge, MA).

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19 Multiplex Analyte Detection The analysis of a broad range of immunological analytes was assessed from serum and cell culture supernatants in a multiplex format utilizing the Luminex 100 xMAP System (Austin, TX). This detection system offers several advantages over standard ELISA techniques, including a significant reduction in sample volume requirements and a larger dynamic range of detection. Cytokine Determination from Suppression Assay Supernatants Supernatants from the suppression assays were analyzed utilizing a commercially available multiplexed kit (Beadlyte Human Multi-Cytokine Detection System 3; Upstate Biotechnology, Waltham, VA) on the xMAP platform (Luminex). Simultaneous measurement of ten cytokines was performed, specifically: IL-1, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12 (p70), TNF-, IFN-, and GM-CSF. TGF-1 (BioSource, Camarillo, CA) and soluble CD25 (BD Biosciences) levels were determined by standard ELISA. For technical reasons of limited sample volume, some assays were only performed at the 120 h time point. All assays were performed according to the manufacturers’ protocols. For the 24 and 48-h time points, 5 l was collected from 6 replicate wells and then diluted 1:2 in tissue culture media prior to analysis. At the 5-day time point, 20 l was removed from each replicate well and assessed neat. Cytokine concentrations were determined utilizing SOFTmax PRO software (Molecular Devices, Sunnyvale, CA) with four-parameter data analysis. Serum Analyte Determinations Serum was collected from all study participants for the analysis of immunological parameters and serum autoantibodies. Approximately, 10 ml of blood was collected in

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20 serum separator tubes and allowed to clot at 23C for 30 min. The samples were then centrifuged at 800 x g for 30 min at 4C. The resulting serum sample was then transferred into 3 separate aliquots to prevent multiple freeze-thaw cycles. All serum was held at -20C prior to analysis. Autoantibodies against two type 1 diabetes associated autoantigens were tested including those against GAD65 and IA-2. Assays were performed utilizing commercially available immunoassay kits provided by Kronus (Boise, Idaho) according to manufacturer’s recommendations. All samples were first screened for the presence of either GADA or IA-2A in a combination test. Positive results from the initial screening run were then confirmed in duplicate in individual assays for GADA and IA-2A. Purification of Genomic DNA Fresh peripheral blood was collected in EDTA containing vacutainer tubes for the purification of genomic DNA utilizing the Wizard Genomic DNA Isolation System (Promega; Madison, WI). 300 l of whole blood was added to 900 l of RBC lysis solution and incubated for 10 min at 23C. The sample was centrifuged at 13,000 x g for 20 sec. The supernatant is discarded and the cell pellet vortexed. To the pellet, 300 l of nuclei lysis solution and 100 l of protein precipitation solution are added with gentle mixing. Following another centrifugation step, the supernatant is transferred to a fresh microcentrifuge tube containing 300 l of pure isopropanol. The DNA pellet is centrifuged and washed with 300 l of 70% ethanol. Following the final centrifugation step, the pellet is resuspended in 100 l of DNA rehydration solution. DNA concentration and purity was determined by the A260/280 ratio on a SmartSpec 3000 (BioRad; Hercules, CA).

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21 Statistical Analyses and Software Statistical analyses were undertaken utilizing GraphPad Prizm 4.00 software (GraphPad, San Diego, CA, USA) and values at P<0.05 were deemed significant. Unless otherwise specified, Mann-Whitney tests were employed to compare cellular frequencies and Spearman’s correlations to compare cellular frequency to subject age. Cytokine profile comparisons were conducted using unpaired t tests (two-tailed).

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CHAPTER 3 ANALYSIS OF REGULATORY T CELL FREQUENCIES This chapter reviews the literature regarding studies of regulatory T cells frequency in T1D and presents data relating to regulatory T cell frequencies in T1D. As part of these studies, Treg was investigated as a function of disease duration. Therefore, both new-onset as well as established T1D patients were included. Longitudinal analyses of cellular phenotypes were also conducted to assess the temporal stability and reproducibility of each cellular phenotype. Finally, a historical caution for studies of T1D, a disorder which often initially presents in children and adolescents, involves a determination of whether age influences the factor under assessment. Therefore, an association analysis was performed on all study subjects correlating age at time of testing versus Treg frequency, an analysis that revealed important age associations which are also presented herein. Introduction to Studies of CD4 + CD25 + Regulatory T Cells: Lessons from Animal Models of and Humans with Type 1 Diabetes While much of our understanding of the role for CD4 + CD25 + T cells has been derived from investigations of Scurfy mouse, studies of other strains have also supported a crucial role for these cells in the regulation of autoimmunity (45). Indeed, analysis of CD4 + CD25 + T cells in various autoimmune prone animals have in most cases implied that such animals have an intrinsic defect in either the frequency or function of their regulatory T cells. Furthermore, such defects have often been related to actual disease development. In studies of NOD mice wherein the goal was to compare the frequency of 22

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23 CD4 + CD25 + T cells against other common inbred strains, most (but not all) suggested NOD mice express a relative deficiency in these regulatory T cells (27, 28). Furthermore, these cells were capable of imparting disease protection. Other investigations indicate that the administration of various self-antigens to spontaneous or transgenic based models induce regulatory T cells in the appropriate host (110). Interestingly, the regulatory T cells generated by this procedure provide transfer of disease protection in antigen as well in tissue specific fashion. While indirect evidence for a key role of CD4 + CD25 + T cells in disease modulation, NOD mice lacking B7-1/B7-2 demonstrated decreased numbers of CD4 + CD25 + T regulatory cells and in addition, resulted in a more rapid diabetes onset (27). In keeping with the aforementioned notions for TGF-, pancreatic expression of this cytokine in NOD mice also supported a potential for regulating the in vivo expansion of intra-islet CD4 + CD25 + regulatory T cells (111). In addition, very recent studies have suggested decreasing levels (as provided by single cell analysis) of Foxp3 + and TGF-1 + Treg during the natural history of type 1 diabetes development in NOD mice (112). This notion is consistent with another recent report by You and co-workers suggesting that qualitative rather than strictly quantitative differences in pathogenic T cells are associated with type 1 diabetes in NOD mice (113). As far as a role for CD4 + CD25 + regulatory T cells in human autoimmune disease, this question has (given the newness of the field) only come under relatively recent investigation. Studies of subjects with multiple sclerosis and autoimmune polyglandular syndrome type II (APSII) have both been described to have normal levels of CD4 + CD25 + T cells, but impaired suppressive function of these regulatory cells (114,

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24 115). In contrast, subjects with systemic l upus erythematosus have been reported to have reduced frequencies of CD4 + CD25 + T cells (116). The first report of Treg in subjects havi ng (solely) type 1 diabetes indicated a reduced frequency of CD4 + C25 + regulatory T cells in new ons et and long standing type 1 diabetic patients (33). Si nce that original submission, an additional three studies have been published addressing the frequency of CD4 + CD25 + T cells in human type 1 diabetes. At one level, these latter three st udies appear in univer sal agreement. Based on these studies, type 1 diabet es does not appear to be associated with diminished frequencies of CD4 + CD25 + T cells; albeit a number of caveats exist to that statement, including subject ages and the definition of Treg de fined by CD25 expression levels, among others (117). One key example of this is the use of different fluorochromes when assessing a molecule that is expresse d across a continuum of cells such as CD25. Different fluorochromes such as fluorescein isothiocyanate (FITC) and phycoerythrin (PE) have significantly different sensitivities, and thus, can result in dramatically different readouts when assessing Treg fr equency. Yet another point of contention revolves around the gating schemes used by th e operator to identify the propulations of interest. For example our studies relied upon CD 3 gating to increase the sensitivity of the test, reduce isotype control antibody background, and rule out monocytes which are capable of expressing low levels of the molecule CD4 (Table 3-1). Recently, a study reporting cytometric analyses of subjects at high-risk for T1D by genetic analysis of HLA class II genes (DQA1*0501-DQB1*0201, DQ A1*0301-DQB1*0302) and the CTLA-4 +49 A/G polymorphism reported reduced expr ession and frequencies of CTLA-4 and CD4 + CD25 HI cells (120).

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25 Table 3-1. Regulatory T cell frequencies in type 1 diabetes. Publication Patient Group Age Range Markers Cell % & Range P value Preparation Notes Kukreja et al. Control (N=12) mean37 + 5.66* CD4 + CD25 + 6.9 + 0.4 PBMC No CTLA-4 link New-onset T1D (N=21) 9.4 + 2.16 (of CD4 + cells) 2.6 + 0.23 <0.001 observed Established T1D (N=9) 45.2 + 9.7 3.7 + 0.69 <0.002 Type 2 Diabetes (N=15) 35.35 + 19.63 6.3 + 0.48 NS Putnam et al. Control (N=19) mean 32; range 22 CD4 + CD25 + med 2.9; 0.4 .7 PBMC Analyzed during CD4+CD25 high med 0.9; 0.3–1.6 FACS Established T1D (N=17) mean 31; range 25 CD4 + CD25 + med 2.4; 0.6–6.5 NS purification CD4+CD25 high med 1.0; 0.3–2.3 NS protocol Lindley et al. Control (N=15) mean 30.3 + 6.8 CD4 + CD25 + (HLA matched) (lymph & CD3 + ) 16.9 + 5.6 PBMC Elevated CD25 high 93.8 + 22.4 intracellular Type 1 Diabetes (N=21) mean 32.3 + 6.8 CD4 + CD25 + 18.7 + 6.7 NS CTLA-4 and CD25 high 95.4 + 16.7 NS CD69 in T1D on CD4 + CD25 + cells Kriegel et al. Control (N=10) mean 36, range 24 CD4 + CD25 + 9.3 no range report Not reported PBMC Type 1 Diabetes (N=4) mean 40, range 22 3.0 Brusko et al. Control (N=37) mean 24.78, range 10–56 CD4 + CD25 + 19.03 + 5.54 Whole blood No observed CD25 high 1.66 + 1.25 staining difference in (lymph & CD3 + ) preparation CD45RA, New-onset T1D (N=9) mean 14.1, range 8 CD4 + CD25 + 12.80 + 2.97 0.0007 CD45RO, or Established T1D (N=61) mean 18.94, range 5.4 CD4 + CD25 + 15.21 + 5.54 0.0006 CD62L All T1D patients (N=70) CD25 high 1.19 + 0.61 NS Age corrected controls (N=14) CD4 + CD25 + 14.89 + 2.32 (below 20 yrs of age) 0 CD25 high 1.57 + 0.84 Age corrected T1D (N=49) CD4 + CD25 + 13.46 + 4.26 NS CD25 high 1.19 + 0.59 NS *Based on reported ages for all subjects studied. The groups reported for CD4 + CD25 + T cell frequency represent a sub-set of the study sample set.

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26 The lack of a specific marker for Treg (FOXP3) limited each of these previous studies. CD25 can also be expressed on T cells of alternate lineages or activation states, allowing for a potential overestimation of the true Treg pool (121). Recently, reagents capable of identifying a linage specific transcription factor more intimately associated with Treg, the forkhead molecule FOXP3, have been developed. While FOXP3 expression is less restricted in humans compared to mice (103), FOXP3 expression in human cells, whether naturally occurring from thymic origin or induced in the periphery following tolerogenic conditioning, continue to demarcate functional Treg (104). Thus, these associations with FOXP3 and Treg provide the rationale for performing analyses of FOXP3 + T cells in subjects with or at varying degrees of risk for T1D. Methods for Phenotypic Analysis by Flow Cytometry These studies consisted of two major cohorts to assess the frequency of regulatory T cells. The first cohort consisted of patients analyzed for co-expression of the surface markers CD3, CD4, and CD25. From the time of those initial studies, additional reagents have become available to assess the expression of the intracellular transcription factor FOXP3, and thus form the basis of the second subject cohort. Analysis of CD4 + CD25 + T cells Frequencies of CD3 + CD4 + CD25 + T cells were assessed from 61 children and adults with established T1D (25 male/36 female; 53 Caucasian, 5 African American, 3 Hispanic; mean age 18.94 + 7.26 yr, range 5.44 – 44 yr; mean disease duration 8.17 + 6.19 yr) and 37 non-diabetic healthy individuals (21 male/16 female; 31 Caucasian, 3 African American, 2 Hispanic, 1 Asian; mean age 24.78 + 11.46 yr, range 10 yr) from the general population. A patient with T1D was classified as new onset if collected within four months of the initial date of diagnosis. The new onset T1D patient group consisted

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27 of nine individuals (6 male/3 female; 8 Caucasian, 1 African American; mean age; 14.11 + 6.49 yr, range 8 – 26 yr). Hence, a total of 70 T1D patients were subject to investigation. Analysis of FOXP3 Expressing T cells For the FOXP3 subject cohort, peripheral blood samples were obtained from 94 individuals including those with recent-onset (<12 wk from diagnosis) or established T1D, their first-degree relatives, and healthy controls (Table 3-2). Table 3-2. Patient demographics Group Subjects (N) Gender (M/F) Age (years) GADA IA-2A Duration (y) New onset T1D* 11 6/5 14.1 + 4.4 9/11 7/11 0.11 + 0.07 median 13.5 median 0.11 range 8.4.5 range 0.01.24 Established T1D 13 9/4 18.6 + 10.6 13/13 10/13 6.7 + 10.1 median 13.5 median 3.6 range 8.4.5 range 1.0.2 Relatives 42 22/20 29.3 + 17.4 4/42 5/42 median 33.9 range 3.5.6 Healthy control 28 15/13 24.8 + 10.1 0/27 0/27 median 23.4 range 6.3.9 *New onset T1D patients were analyzed within 3 months of the date of diagnosis. The established T1D group contained all subjects with disease duration greater than three months. Serum was not available for one control subject. Extended Phenotypic Analysis This antibody recognizes CD62L, known as L-selectin, a 76 kDa molecule which is a member of the selectin family of adhesion receptors. These function in leucocyte binding to activated endothelium and in lymphocyte homing to high endothelial venules (122). Treg have been reported to express high levels of CD62L expression (59). Also of interest to studies of Treg, is whether any possible differences in CD25 expression result

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28 from alterations in the repertoire of cells expressing markers of nave (CD45RA) or memory (CD45RO) T cells (122). Therefore, an analysis of these markers was conducted on gated CD4 + CD25 + and CD4 + CD25 T cell sub-populations. Results CD4 + CD25 + T Cell Frequencies in Peripheral Blood are Stable Over Short to Intermediate Periods of Time To establish the frequency of CD4 + CD25 + T cells, whole blood was stained with relevant phenotypic markers (CD3, CD4, CD25) and analyzed by FACS . Lymphocytes were gated based upon scatter and CD3 expression (a representative healthy control is shown in Fig. 3-1) then analyzed for expression of CD4 and CD25 (Fig. 3-1B). Figure 3-1. Representative FACS plots from a normal healthy control showing expression of CD4 and CD25. A) Regions were set individually for each subject by gating on CD3 + lymphocytes with isotype background staining of one percent (5 x 10 4 events acquired). B) lymphocyte and CD3 + gated CD4 + CD25 + T cells. C) Plot showing gate for CD4 + CD25 + T cells with a fluorescence intensity of CD25 exceeding 100 defined as bright. D) Stability of CD4 + CD25 + T cells over time. Whole blood samples from eleven healthy control subjects spanning a time period of up to 12 months were tested (X-axis), with initial and each re-analysis shown (bars shown represent mean and SEM).

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29 In order to assess the so-called CD4 + CD25 +Bright T cells, cells exhibiting a florescence intensity of greater than 100 units were considered positive (Fig. 3-1C), as previously described (116). One parameter of interest for studies of CD4 + CD25 + T cells involved the questions of reproducibility and longitudinal variation within an individual. To assess this aspect, we performed an analysis of CD4 + CD25 + T cells on 11 healthy controls for various amounts of time spanning up to one year between the initial test and each subsequent re-analysis. The CD4 + CD25 + T cell frequency demonstrated a remarkable level of stability (Fig. 1D; median CV 6.83%, range 1.69 to 13.91%). Frequencies of CD4 + CD25 + T Cells in Peripheral Blood Associate with Age An association analysis was performed on all study subjects correlating age at time of testing versus the CD4 + CD25 + frequency (Fig. 3-2A), an analysis that revealed increasing age was associated with an increase in CD4 + CD25 + frequency (r=0.60, P<0.0001). To determine whether this association with age influenced healthy controls (Fig. 3-2B) or T1D patients (Fig. 3-2C) uniquely, similar analyses were performed and indicated that in both study groups, age influenced the frequency of CD4 + CD25 + T cells (r=0.64, P<0.0001 and r=0.51, P<0.0001 for healthy controls and T1D subjects, respectively), and that the two groups were not significantly different (P=NS) in terms of their age associations. Furthermore, the age associations were isolated to the population of cells isolating intermediate levels of CD25. No correlation with age was observed in all subject groups for the population of cells expressing CD25 fluorescence intensity greater than 100 mean fluorescence intensity units (P=NS). In other words, the functional Treg population appears independent of subject age.

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30 Figure 3-2. Relationship between CD4 + CD25 + T cell frequency and age at time of testing. Frequency versus age studies in A) all subjects analysed (N=107; circles), B) normal healthy controls (N=37; squares), and C) patients with new-onset and established T1D (N=70; diamonds). Frequencies of CD4 + CD25 + T Cells Do Not Differ in Healthy Controls and in Patients with T1D of Similar Age Healthy controls and patients with T1D demonstrated similar percentages of lymphocyte gated CD3 + T cells (68.41 + 7.98 vs. 70.04 + 7.75, P=NS respectively) and lymphocyte and CD3 + gated CD4 + T cells (62.00 + 8.21 vs. 60.35 + 7.62, P=NS). When the frequency of CD4 + CD25 + T cells was plotted, T1D patients exhibited lower frequencies than controls (Fig. 3-3A, 15.21 + 5.54 vs. 19.03 + 5.54 respectively; P=0.0006).

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31 Figure 3-3. Frequencies of CD4 + CD25 + T cells and CD4 + CD25 +Bright T cells do not differ significantly between controls and patients with T1D when corrected for age. Frequencies of CD4 + CD25 + T cells (upper panels; A, B) and CD4 + CD25 +Bright T cells (lower panels; C, D). Cellular frequencies for all controls (N=37; black squares) and patients with T1D (N=70; black diamonds) (left panels; A, C). Cellular frequencies for normal healthy controls (n=14; black squares), and patients with T1D (N=49; black circles) under the age of 20 yrs old (right panels; B, D). This trend was even more pronounced in the new-onset T1D group, which averaged only 12.80 + 2.97 (data not shown, P=0.0007). However, as indicated previously, a strong association exists between age of a subject at the time of testing and the frequency of CD4 + CD25 + T cells. Thus, comparisons were then performed between subjects below the age of 20 (a common age limit for studies of age and T1D). Interestingly, the frequency of CD4 + CD25 + cells amongst these two populations, once

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32 limits of age were applied, was very similar (Fig. 3-3B; healthy controls (N=14), 14.89 + 2.32 and T1D (N=49) 13.46 + 4.26, P=NS). A major focus of attention in immune regulation as it pertains to those with T1D has been directed at a population of Treg known as CD4 + CD25 +Bright T cells. Their definition in terms of gating has not been subjected to universal acceptance, but for our studies we used a uniform gate across all samples dependent on units of fluorescence intensity. Specifically, we utilized a definition of those CD4 + CD25 + T cells with fluorescence intensity of CD25 expression exceeding 100 units as CD4 + CD25 +Bright T cells. Under these conditions, no significant difference in frequency was observed between healthy controls and the T1D population for the percentage of CD4 + CD25 +Bright T cells either when all subjects were analyzed (Fig. 3C, 1.66 + 1.25 vs. 1.19 + 0.61; control and T1D respectively) or when these analyses were restricted to subjects under 20 yrs of age (Fig. 3-3D; 1.57 + 0.84 vs. 1.19 + 0.59; control and T1D respectively). Furthermore, quantitation of the number of PE molecules per CD4 + CD25 + gated T cell utilizing standardized PE-labeled beads showed slightly higher levels of CD25 per gated cell in the T1D population compared to controls (949.7 + 135.9 vs. 834 + 103.2, P=0.01). Analysis of FOXP3 + T Cell Frequencies To more specifically determine the frequency of Treg in peripheral blood, lymphocytes were gated based on cell scatter and cells were analyzed for their expression of the surface markers CD3, CD4, CD25, and the intracellular transcription factor FOXP3 (representative plots in Fig. 3-4, A-G).

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33 Figure 3-4. Flow cytometric analysis of FOXP3 from fresh peripheral blood. Plots depict a representative healthy control sample gated on lymphocytes and CD3 + T cells showing A) isotype control or B and C) CD4 and CD25 staining, as well as D) isotype control and E) intracellular staining for FOXP3. In this sample, FOXP3 + cells predominantly reside within the CD4 + CD25 + T cell quadrant (91.1%; upper right quadrant of plot C). In the 28 healthy controls utilized in this study, the FOXP3 + population represented 0.96% + 0.45 of all cells analyzed, or 4.53% + 1.27 of CD3 + lymphocytes. F) Isotype control staining and G) the correlation between CD25 expression and intracellular FOXP3 expression. The longitudinal stability in the frequency of H) FOXP3 + , I) CD25 + FOXP3 , and J) CD25 + FOXP3 + T cells over a period of time up to three months in duration (N=4; bars shown represent mean and SE from the initial analysis to subsequent reanalysis). The majority of FOXP3 + T cells co-expressed CD4 and CD25 (Fig. 3-4, C), supporting specificity of the staining procedure. To establish the stability of these cellular phenotypes, we also performed a longitudinal analysis on a limited number of subjects. No significant variations were observed in a period up to 3 months, as the frequency of CD25 + and FOXP3 + cells (alone or in combination) remained relatively stable (Fig. 3-4, H–J, Student’s paired t test, P = NS).

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34 Previously data (Fig. 3-2) indicated the frequency of CD4 + T cells expressing low to intermediate levels of CD25 (CD4 + CD25 LOW ; defined by CD25 staining above isotype control and <100 FIU) increase with age and was independent of T1D. Utilizing these markers and including FOXP3 as a more specific indicator of Treg (Fig. 3-5, A-C), a significant correlation (utilizing all study subjects) between the frequency of CD25 LOW FOXP3 T cells (upper-left quadrant of Fig. 3-5D) and age (Fig. 3-5E; N=94, r=0.75, P < 0.0001) is observed for all subjects analyzed. Figure 3-5. Analysis of T cell subpopulations reveals an association between age and their frequency in peripheral blood. Representative plots (one healthy control) indicating A–C) expression of CD4 & CD25 and D) CD25 & FOXP3. D) CD25 + FOXP3 gated cells (upper-left quadrant of plot) co-express A) CD4 and low levels of CD25. D) CD25 + FOXP3 + T cells (upper-right quadrant of plot) express B) CD4 and high levels of CD25. C) CD4 and CD25 expression and gates for the analysis of CD45RO and CD45RA expression on T cells. C) Analysis of CD45RA and CD45RO on CD4 + CD25 + or CD4 + CD25 T cells indicate that CD4 + CD25 + T cells predominantly express CD45RO whereas CD4 + CD25 T cells express CD45RA. The frequency of E) CD25 + FOXP3 T cells from all subjects analyzed (N=94) increases with age while F) CD25 + FOXP3 + cells remain relatively stable.

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35 The cellular phenotypes of cells which are strongly influenced by age are of interest. Therefore, we included the analysis of two markers which distinguish between nave and memory T cells, namely CD45RA and CD45RO, respectively. Analysis of CD45RA and CD45RO on CD4 + CD25 + (Fig. 3-5C, upper-right boxed region), or CD4 + CD25 T cells (Fig. 3-5C, lower-right boxed region), indicate that CD4 + CD25 + T cells predominantly express CD45RO (N=26 controls, 84.4% + 8.3 versus CD45RA 38.9 + 10.5). In contrast, CD4 + CD25 T cells predominantly express CD45RA (75.9 + 9.8 versus CD45RO 43.7 + 17.1; depicted in sliding scale to the right of Fig 5-3C). In contrast, the frequency of CD25 + FOXP3 + T cells (upper-right quadrant of Fig. 3-5D) appears independent of subject age (Fig. 3-5F; r=0.17, P = NS). A similar age association was also observed following both CD3 and CD4 gating (CD25 + FOXP3 , r=0.65, P < 0.0001 and CD25 + FOXP3 + , r=0.03, P = NS). As previously observed with the frequency of CD4 + CD25 + T cells, the influence of age was independent of disease state (data not shown). These findings, taken together with the relative stability of CD4 + CD25 + FOXP3 T cells over time (Fig 3-4,I; mean CV% + SD, 7.3 + 4.9), suggest that long-term alterations in T cell phenotype, rather than an increase in acutely activated cells, underlie the observed age associated differences in the frequency of CD4 + CD25 + cells. Since lymphopenia has been reported in association with T1D in NOD mice (24), we assessed both the frequency and absolute number of FOXP3 + T cells in the study populations. The frequency of Treg defined by either the frequency FOXP3 + T cells, frequency of CD4 + CD25 + FOXP3 + T cells, or the absolute number of FOXP3 + T cells, did not significantly differ as a function of T1D state or disease-risk (Fig. 3-6, A–C).

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36 Figure 3-6. Frequencies of FOXP3 + regulatory T cells do not differ in subjects with T1D. For all populations analyzed, A) frequency of total FOXP3 + cells B), frequency of CD25 + FOXP3 + and C), absolute number of FOXP3 + cells, no significant differences were identified as a function of the study groups (all P = NS). D) The frequency of CD25 + FOXP3 T cells was elevated in two situations: relatives of T1D patients (21.2 + 8.4) versus new onset subjects (13.3 + 4.6; P = 0.003) and relatives of T1D patients versus healthy controls (17.4 + 6.1; P = 0.03). A modest difference was, however, observed in the frequency of CD4 + CD25 LOW FOXP3 T cells (Fig. 3-6D) in first degree relatives; a facet that was related to age as opposed to disease state (Fig. 3-5E). Likewise, neither the duration of T1D nor autoantibody titer influenced the frequency of CD4 + CD25 + FOXP3 + T cells (P = NS). For reasons of limited subject availability, we elected to study a random sampling of first-degree relatives of T1D patients independent of their autoantibody status, to identify potential genetic associations between Treg frequency and disease risk. While

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37 none were identified, future efforts could benefit from analysis of individuals at high (i.e., autoantibody positive) versus low–(i.e., autoantibody negative) risk for the disease. Extended Phenotypic Analysis of CD4 + CD25 + and CD4 + CD25 T Cells Expression patterns of the surface markers CD45RA, CD45RO, and CD62L contribute to the understanding of T cell functional capacity, antigen exposure, and tracking/adhesion potential. Therefore, these markers where assessed on gated CD4 + CD25 + and CD4 + CD25 T cells of study participants to further characterize T cell phenotypes (Fig. 3-7). Figure 3-7. Expression of CD45RA, CD45RO, and CD62L by control subjects (open bars, N=28), relatives (hatched bars, N=42), and all subjects with T1D (closed bars, N=24). Graphs represent the percent of cells expressing of each marker following gating on CD4 + CD25 + (upper-right quadrant of Fig. 1A) or CD4 + CD25 T cells (lower-right quadrant of Fig. 1A). B) CD4 + CD25 + T cells predominantly express the memory T cells marker CD45RO. C) CD4 + CD25 T cells predominantly express the naive T cells marker CD45RA. Significance is indicated as follows: * P < 0.05, ** P < 0.01.

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38 Age has been shown to strongly influence the frequency of CD4 + CD25 + T cells (Fig. 3-2) as well as CD25 + FOXP3 T cells (Fig. 3-5E). Therefore, it is reasonable to question whether age would also have an impact on the expression of the markers CD45RA, CD45RO, and CD62L (Fig. 3-8). Figure 3-8. Markers of cellular phenotype associate with subject ages. Expression of the nave T cell marker CD45RA decrease with age on both A) CD4 + CD25 + and D) CD4 + CD25 T cells (N=94, all subjects analyzed). The frequency of CD45RO + T cells increases with age on B) CD4 + CD25 + and E) CD4 + CD25 T cells. No correlation with age was observed for CD62L expression on C) CD4 + CD25 + T cells. A negative correlation was observed between the frequency of CD62L + T cells and subject age on CD4 + CD25 T cells. Thus, it appears that the immune repertoire undergoes a shift from a nave (CD45RA expressing) phenotype to a memory (CD45RO expressing) with age and antigen exposures. This analysis once again highlights the influence of subject age on T

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39 cell sub-set distribution and the strict requirement for age consideration when assessing these markers as a function of disease state. Discussion Despite an abundant interest in CD4 + CD25 + T cells as they relate to the pathogenesis and perhaps more importantly, susceptibility to T1D, only a limited number of studies of these cells in humans with the disorder have thus far been reported (33, 115, 117). To this issue, the data outlined herein indicates that the frequency of Treg defined by either the expression of CD4 and CD25, or following the inclusion of FOXP3, do not appear to differ in individuals with T1D versus healthy controls. In addition, these studies portend that persons with T1D express normal frequencies of CD4 + CD25 Bright T cells, which purportedly identify Treg cells exhibiting the greatest suppressive capacity (20). Despite the lack of any apparent deficiency of Treg in T1D, it should be noted that a significant degree of heterogeneity in CD4 + CD25 + and FOXP3 + T cells was detected for both T1D patients and controls. Considering the stability in these cell populations over short to intermediate periods of time, it is of interest whether these cellular frequencies are influenced by genetic polymorphisms, especially for those genes which have been associated with T1D susceptibility such as HLA, CTLA-4, and CD25, etc (123). Several factors could contribute to the lack of concordance between the findings outlined herein and those of Kukreja and colleagues who indicated reduced Treg frequencies in patients with T1D (33). Some discrepancy may be explained by differences in methodology or patient populations; however, the variances are most likely explained by the requirement for strict age matching in comparisons. Indeed, one key facet to these descriptions regarding “normal” frequencies of Treg was the discovery of age related

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40 influences on the percentage of peripheral blood CD4 + CD25 + T cells. More specifically, the influence of age appears to be due to an increase in CD4 + CD25 intermediate T cells which are negative for the regulatory gene FOXP3. This age related alteration is further defined by the apparent shift from a nave to memory T cell repertoire with increasing age. In the end, perhaps the definitive answer on the exact frequency of regulatory populations in cases of autoimmune disorders including T1D will only come about when the exact effector mechanism(s) of Treg are identified; a facet that currently does not exist. Yet, even with such an advance, studies of Treg in T1D, unlike those of investigating juvenile idiopathic arthritis (124), would involve extrapolation of results away from the actual site of inflammation (i.e., the pancreatic islets). It is possible that tissue or lymph node specific tropisms of Treg could mask important clues as to the pathogenic role of such cells in situations like T1D. Yet another current limitation is the identification of polyclonal rather than antigen-specific Treg. Clearly, studies of Treg would benefit from the ability to discriminate between clonal autoreactive pathogenic T cells and autoreactive Treg cells in studies of T1D. Conclusions Two major questions have characterized a large number of recent studies of immunoregulation in T1D; those being are there defects in the frequency or functionality of regulatory T cells. The data outlined in this chapter argues against any apparent deficiency in the frequency of CD4 + CD25 + T cells, CD4 + CD25 Bright cells, or FOXP3 + T cells by either frequency or absolute number in T1D. These studies do, however, bring to light important age related influences over the T cell repertoire with age. Undoubtedly, future studies will seek to identify what, if any, effect this shift in T cell phenotype has over conditions associated with ageing (such as replicative senescence, increased

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41 susceptibility to autoimmunity, infection and cancer, etc). Finally, despite the lack of any apparent Treg deficiency in human T1D, studies in the NOD model of disease clearly indicate that immunomodulatory therapeutics are capable of increasing the proportion of Tregs, and that this increase is associated with protection from disease (75, 105). Therefore, although not associated, these studies of Treg frequency highlight important parameters to consider when assessing the influence of any immunomodulatory therapy aimed at increasing the proportion of Treg.

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CHAPTER 4 ANALYSIS OF REGULATORY T CELL FUNCTION IN T1D This chapter addresses the second major question regarding a possible role for Treg in T1D; that being is there a defect in the functional capacity of Treg in T1D? This chapter will review the literature regarding studies of regulatory T cell function and present novel data assessing Treg function in T1D. In addition, experiments are presented which simultaneously compare the frequency of FOXP3 + T cells present in peripheral blood and the degree of functional suppression observed in vitro. Introduction to Studies of CD4 + CD25 + Regulatory T Cell Function in Humans with Type 1 Diabetes Currently, the most common means of assessing Treg function is by utilizing the in vitro suppression assay. In this assay, CD4 + CD25 + T cells (Treg) are mixed at different ratios with autologous CD4 + CD25 effector T cells (Teff). Following polyclonal T cell stimulation, Teff cells proliferate and produce effector cytokines. Conversely, Treg are anergic (do not proliferate) and actually suppress proliferation and cytokine production by co-cultured Teff cells (20). While the issue of Treg frequency seems to have come to a consensus—type 1 diabetes does not appear to be associated with diminished Treg frequency; less consistent are the findings of functional abnormalities in CD4 + CD25 + T cells, with defective suppressor function only noted in two reports (117, 119), while two other studies (115, 118) reported no such association (outlined in Table 4-1). 42

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Table 4-1. Regulatory T cell function in type 1 diabetes Publication Patient Group Treg:Teff % Suppression P value Stimulant Isolation method Conditions Putnam et al. Control (N=17) 1:1 mean 81.1 + 7.6 Sol. anti-CD3 (2.5 g/ml) & High-speed FACS RPMI* Sol. anti-CD28 (2.5 g/ml) 4 day culture Established T1D (N=19) 1:1 mean 64.7 + 7.2 NS 5% Human Type AB sera Control (N=17) 1:1 mean 44.2 + 10.5 P.B. anti-CD3 (0.01 g/ml) Established T1D (N=19) 1:1 mean 58.5 + 8.0 NS Lindley et al. Control (N=13) 1:1 mean 57.3 + 23.5 P.B. anti-CD3 (5 g/ml) MACS RPMI* Sol. anti-CD28 CD4 + negative sel. 5 day culture Established T1D (N=11) 1:1 mean 25.9 + 17.9 0.007 CD25 + positive sel. 5% Human Type AB sera Kriegel et al. Control (N=10) 1:1 Graphed only; NS PHA (1.0 g/ml) MACS RPMI* Patients with single not individually CD4 + negative sel. 7 day culture endocrinopathies including reported CD25 + positive sel. 10% FCS T1D (N=8; 4 T1D) 43 Brusko et al. Control (N=9) 1:1 med 63.30 Sol. anti-CD3 (5.0 g/ml) & CD4 + negative sel. RPMI* Established T1D (N=10) 1:1 med 14.99 0.002 Sol. anti-CD28 (2.5 g/ml) MACS 5 day culture CD25 + positive sel. 5% Human Type AB sera *Indicates the base media formulation with standard supplementation of antibiotics and buffering reagents. Abbreviations: NS, not significant; FACS, Fluorescence activated cell sorting; MACS, microbead cell sorting; Sol., soluble; P.B., plate-bound; sel., selection procedure.

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44 As far as a possible mechanism underlying the reported functional defects in T1D, these two reports indicated potential associations with CTLA-4 or the aberrant production of cytokines by both Treg and Teff cells (117, 119). Still, the exact immunologic and genetic mechanisms underlying these observations remain unclear. While polymorphisms in the FOXP3 gene have been reported, it is unlikely (but not beyond possibility) that this gene will be directly involved in the generation of type 1 diabetes in humans since allelic variation in FOXP3 does not provide a significant degree of inherited susceptibility to disease (125). However, a recent genetic association with type 1 diabetes of a region on chromosome 10p15, spanning the IL2RA/CD25 locus, forms at least one possible site for future genetic studies implicating a gene central to Treg function with type 1 diabetes (126). Methods Subjects A suppression assay was employed to determine the suppressive capacity of peripheral blood CD4 + CD25 + T cells from healthy controls (N=9; mean age 23.75 + 7.03 yr) and patients with T1D (N=10; 18.11 + 7.77 yr) of similar age. For experiments analyzing the frequency of FOXP3 + T cells present in peripheral blood and the degree of functional suppression observed in vitro, a sub-set of patients were analyzed consisting of normal healthy controls (N=5; mean age 21.06 + 5.77 yr) and patients with T1D (N=5, 13.8 + 4.66). Suppression Assay Suppression assays were performed as described in detail in the methods section of Chapter 2 (Fig. 4-1).

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45 Figure 4-1. Procedure for isolating functional CD4 + CD25 + and CD4 + CD25 T cells for use during the in vitro suppression assay. Two separate aliquots of sodium heparinized whole blood underwent two negative selection procedures to yield untouched T cell depleted accessory cells (irradiated with 3300 rads) and a CD4 + T cell fraction (Stem Cell, Vancouver, Canada). The CD4 + T cell fraction was then split into functional CD4 + CD25 + Treg and CD4 + CD25 Teff cell populations utilizing CD25 microbeads in a subsequent positive selection procedure (AutoMACS, Miltenyi Biotech, Auburn, CA). Various ratios of Treg were added to a constant number of Teff cells (1:0, 1:1, :1 and 0:1; where 1=5000 cells) in the presence of 5.0 x 10 4 irradiated antigen presenting cells. Anti-CD3 (5.0 g/ml) and anti-CD28 (2.5 g/ml) provided the polyclonal stimulus over a 5-day culture period. 3 H-Thymidine (1 Ci) was added at the 5-day time point for the final 12 hr of culture to assess

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46 proliferation. Percent suppression was calculated by the reduction in 3 H-thymidine uptake from the following equation: % suppression= [1-(mean CPM Treg+Teff/mean CPM Teff alone) x 100]. Cytokine Analysis Supernatants were collected from suppression assay cultures at 24, 48, and 120 Hr time points and analyzed for the production of 11 cytokines (IL-1, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12 (p70), TNF-, IFN-, GM-CSF, and TGF-1) as previously outlined in the methods section of Chapter 2. Analysis of FOXP3 + T cells in Peripheral Blood and the Degree of in Vitro Suppression FOXP3 + T cells were analyzed by FACS as previously described in methods section of Chapter 2 (identification of CD25 + FOXP3 + cells depicted in Fig. 3-5D, upper-right quadrant). Correlation analysis between the percent CD25 + FOXP3 + T cells present in peripheral blood and the degree of in vitro suppression observed at a ratio of 1:1 Treg:Teff cell were conducted utilizing Spearman’s correlation analysis with P<0.05 deemed significant. Results Deficient Suppression by Treg in Patients with T1D The ability to suppress proliferation and cytokine production by responding Teff cells is a hallmark of Treg cells. A suppression assay was employed to determine the suppressive capacity of peripheral blood CD4 + CD25 + T cells from healthy controls and patients with T1D of similar age (Fig. 4-2).

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47 Figure 4-2. A representative suppression assay from a normal health control subject. Note that CD4 + CD25 + T cells (1:0; where 1=5000 cells) are both anergic and suppressive when stimulated by anti-CD3 (5.0 g/ml) and anti-CD28 (2.5 g/ml) in the presence of autologous CD4 + CD25 T cells and a 10-fold excess of irradiated T cell depleted accessory cells. Proliferation (y-axis) is recorded by incorporation of 3 H-thymidine. These studies indicated that Treg from patients with T1D were functionally deficient in their ability to suppress Teff cells in vitro. Specifically, at a ratio of one Treg to one Teff cell, T1D patients suppressed proliferation less than healthy controls (20.12% + 61.13 vs. 56.47% + 18.02, respectively; P=0.003) (Fig. 4-3A, left plots). This trend continued in T1D patients and healthy controls at a ratio of Treg to 1 Teff (right plots, 15.60% + 43.99 vs. 42.74% + 14.32; P=0.012). Although a trend for Teff cell hyporesponsiveness is observed in Teff cells of T1D patients, for all cell ratios of Treg to Teff (1:0, 1:1, :1, and 0:1), the mean CPM in T1D patients and healthy controls did not differ significantly (Fig. 4-3B, P=NS). Interestingly, in certain patients with T1D, Treg cells not only failed to suppress the proliferation of Teff cells, but also acted in synergy leading to increased proliferation over Teff cells alone (Fig. 4-3A).

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48 Figure 4-3. Functional suppression by CD4 + CD25 + regulatory T cells is deficient in patients with T1D. Data plotted represent the percent inhibition of proliferation by CD4 + CD25 + Treg cells from normal healthy controls (N=9; black squares) and patients with T1D (N=10; black circles). CD4 + CD25 + Treg cells were plated alone (1:0; 5 x 10 3 /well) and in decreasing ratios (1:1, :1, 0:1) to a constant number of CD4 + CD25 Teff cells. Percent inhibition was calculated from the mean CPM of six replicate wells at a Treg to Teff cell ratio of A) 1:1 (left plots) and :1 (right plots), respectively with ** P<0.01. Proliferation measured by 3 H-Thy incorporation during suppression assays by indicated cell populations from B) patients with T1D (black bars) and normal controls (white bars). Bars represent the mean + SEM. Altered cytokine profile from stimulated cultures in patients with T1D Cytokines play an important role in every step of T1D pathogenesis; in the processes of disease initiation, progression, and even prevention. In order to identify

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49 mechanistic factors that may contribute to this defect in suppression by Treg in vitro, supernatants from these suppression assay cultures from T1D patients and healthy controls were analyzed for the production of a variety of cytokines at periods of 24, 48, and 120 h. Specifically, multiplexed cytokine detection (10-plex) was conducted to measure levels of IL-1, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12 (p70), TNF-, IFN-, and GM-CSF, while TGF-1 was determined by conventional ELISA. Significant alterations in the levels of IFNwere identified in supernatants from T1D patients compared to healthy controls at nearly all time points (Fig. 4-4A), with diminished production in Teff populations (i.e., 0:1) from T1D being the most significant. Patients with T1D also displayed a deficiency in the production of TGF-1 (Fig. 4-4B; P<0.03) in Treg cultures (i.e., 1:0). Figure 4-4. Altered cytokine profile from stimulated cultures in patients with T1D. Cytokine profiles from healthy controls (n=6, black squares) and patients with T1D (n=5, black circles). Supernatants were collected at 24, 48, and 120-hour time points and pooled from six replicate wells and stored at -20C prior to analysis. Only 120 h cytokine data are shown. Graphs represent the mean + SD with situations identifying statistical significance indicated. Shown are the results for A) IFNand B) TGFfor all ratios Treg to Teff cells (i.e. 1:0, 1:1, :1, and 0:1).

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50 Table 4-2. Cytokine elaborations monitoring regulatory and effector T cell function _______________________________________________________________________ Treg:Teff 24 Hr 48 Hr 120 Hr Cytokine Ratio Control T1D Control T1D Control T1D 1 to 0 35.1 + 29.2 40.8 + 50.6 48.8 + 34.0 69.3 + 84.2 66.7 + 41.4 98.4 + 121.6 1 to 1 37.8 + 26.2 42.8 + 44.5 84.9 + 31.9 84.0 + 78.6 194.1 + 102.0 138.9 + 108.0 1/2 to 1 25.3 + 17.8 40.0 + 49.9 71.0 + 22.8 63.1 + 64.3 200.27 + 123.0 122.8 + 120.5 GM-CSF 0 to 1 9.2 + 1.8 11.3 + 8.5 46.5 + 34.6 21.5 + 10.9 319.6 + 190.9 66.6 + 35.5** 1 to 0 40.2 + 25.5 ND 97.3 + 42.0 ND 68.3 + 33.6 22.5 + 23.6 1 to 1 107.8 + 59.3 12.9 + 28.8** 197.9 + 121.4 85.7 + 102.7 343.3 + 162.3 261.5 + 335.5 1/2 to 1 116.0 + 47.8 ND 247.5 + 134.4 56.9 + 66.8* 476.9 + 265.3 157.8 + 158.3 IFN0 to 1 92.3 + 36.0 ND 244.3 + 174.0 33.2 + 53.3* 757.6 + 381.5 127.0 + 118.2** 1 to 0 4.6 + 3.6 5.6 + 5.6 7.4 + 6.7 6.2 + 6.8 17.1 + 16.7 6.1 + 6.7 1 to 1 5.1 + 4.3 5.9 + 5.2 12.7 + 10.0 7.3 + 6.5 19.4 + 15.6 7.5 + 7.0 1/2 to 1 2.4 + 2.6 5.6 + 4.9 10.8 + 11.0 6.8 + 6.1 20.0 + 18.9 7.8 + 8.0 IL-10 0 to 1 ND 2.4 + 0.6 6.3 + 7.6 3.1 + 2.4 20.5 + 17.9 4.0 + 3.0 1 to 0 73.2 + 79.5 268.0 + 494.9 56.7 + 66.6 212.5 + 389.2 22.2 + 27.2 101.4 + 193.6 1 to 1 85.9 + 95.9 297.7 + 538.6 64.40 + 74.8 196.7 + 357.3 23.7 + 26.3 88.1 + 161.9 1/2 to 1 54.0 + 69.4 216.4 + 393.4 38.8 + 52.1 123.3 + 214.8 15.9 + 20.6 69.7 + 130.3 IL-1 0 to 1 3.1 + 3.7 21.0 + 41.0 1.8 + 2.3 14.4 + 26.0 1.1 + 1.3 8.0 + 12.7 1 to 0 37.0 + 17.4 4.1 + 6.2** 33.7 + 16.8 9.2 + 14.4* 7.8 + 2.4 ND 1 to 1 77.3 + 42.3 23.2 + 35.9 76.5 + 45.4 24.0 + 30.3 10.6 + 6.3 ND 1/2 to 1 72.7 + 41.6 14.3 + 19.7 77.0 + 45.1 15.1 + 17.4 9.0 + 1.9 ND IL-2 0 to 1 57.9 + 29.7 7.9 + 11.5* 71.5 + 39.9 7.4 + 10.3** 12.6 + 5.8 1.34 + 3.0** 1 to 0 16.9 + 1.2 ND 17.8 + 2.3 ND 9.8 + 2.0 ND 1 to 1 17.9 + 2.1 ND 21.5 + 7.0 ND 12.6 + 4.1 ND 1/2 to 1 17.5 + 1.8 ND 21.6 + 5.3 ND 12.1 + 3.4 ND IL-4 0 to 1 16.6 + 1.2 ND 20.2 + 3.1 ND 13.7 + 4.3 ND 1 to 0 554.8 + 399.4 546.2 + 558.8 604.7 + 478.9 637.0 + 640.9 556.1 + 484.9 676.4 + 779.9 1 to 1 568.9 + 389.6 580.8 + 515.1 630.0 + 468.0 588.8 + 547.1 580.9 + 463.2 654.7 + 695.6 1/2 to 1 370.0 + 287.4 548.1 + 611.1 435.2 + 369.7 522.3 + 559.6 319.6 + 378.5 628.5 + 842.7 IL-6 0 to 1 68.4 + 34.9 173.1 + 183.8 72.9 + 36.3 182.1 + 184.4 65.5 + 34.9 191.6 + 221.2 1 to 0 335.9 + 220.7 233.9 + 268.3 184.0 + 134.9 113.0 + 123.2 78.8 + 88.7 64.6 + 112.7 1 to 1 375.5 + 176.4 240.5 + 211.5 270.3 + 61.8 127.8 + 93.1* 130.9 + 50.5 75.3 + 104.3 1/2 to 1 288.0 + 135.4 200.5 + 186.6 250.2 + 53.8 112.7 + 104.1 125.58 + 42.3 75.7 + 113.6 TNF0 to 1 116.9 + 34.1 68.6 + 58.4 170.0 + 128.4 58.3 + 45.7 136.9 + 81.8 33.5 + 26.0 1 to 0 2443.5 + 1276.7 672.6 + 812.2* 1 to 1 1182.0 + 1838.7 798.8 + 1076.8 1/2 to 1 853.1 + 999.0 815.0 + 708.8 TGF0 to 1 1450.5 + 1380.2 594.5 + 191.3 ________________________________________________________________________ Supernatants were collected from in vitro suppression assays in subjects with T1D or healthy controls at 24, 48, and 120 hr time points and at various ratios of regulatory Tto effector T cells. *P<0.05; **P<0.01; ND = not detected. The production of IL-2 and IL-4 in cultures from subjects with T1D was also clearly diminished, but in the case of IL-4, such variances were uniform and independent of Treg to Teff ratios (Table 4-2). At 120 h, a trend towards reduced levels of IL-10 were seen in

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51 T1D patients (6.9 + 6.77 vs. 17.1 + 16.6 pg/ml; Treg:Teff of 1:0), yet the difference was not statistically significant (P=0.2). Only at the 120 h time point, Teff cell cultures from healthy controls produced higher levels of GM-CSF than did patients with T1D (319.55 + 190.86 vs. 66.61 + 35.46 pg/ml respectively; P<0.01; Treg:Teff of 0:1). No significant differences in the innate mediators IL-1, IL-6, and TNFwere detected at any time point. IL-8 levels were at or above the upper limit of detection for the assay (10 ng/ml) in both subject groups and IL-12 (p70) levels were undetectable at all time points. Frequencies of CD25 + FOXP3 + T cells in Peripheral Blood Do Not Determine the Degree of In Vitro Suppression While the exact mechanisms of suppression employed by Treg remains subject to debate, it appears clear that Treg cells require IL-2 signaling and FOXP3 expression for normal development and function (73, 80, 92). Therefore, we sought to determine whether the frequency of CD4 + CD25 + FOXP3 + T cells in fresh peripheral blood analyzed by FACS analysis would correlate with the degree of suppression conferred by Treg in vitro. Interestingly, no correlation, either in control or T1D patients, was observed between the peripheral blood frequency of CD4 + CD25 + FOXP3 + T cells and the magnitude of in vitro suppression (N=10, all subjects P=NS; Fig. 4-5B). Likewise, no correlation was observed between the mean MFI values for CD25 or FOXP3 expression and the degree of suppression (P = NS). Support for this apparent disconnect may find some basis in the findings that FOXP3 + Treg frequencies do not correlate with long-term tolerance following allogeneic stem cell transplantation (127). These findings highlight the need to further elucidate the downstream mechanism(s) of suppression conferred by Treg.

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52 Figure 4-5. The frequency of CD25 + FOXP3 + T cells in peripheral blood does not correlate with the degree of suppression by isolated CD4 + CD25 + T cells. A) The percent inhibition of Teff cell proliferation by Treg from controls (N=5, closed triangles) and patients with T1D (N=5, open squares). Percent inhibition of proliferation was assessed at a ratio of 1:1, Treg:Teff cell (left plots, A) and :1 (right plots). B) For all subjects analyzed (N=10), no correlation was observed between the frequency of CD25 + FOXP3 + T cells detected in fresh peripheral blood and the percent suppression observed in vitro calculated at a ratio of 1:1, Treg to Teff cell (N=5 controls; median age 20.6 y, range 15.1 to 29.74; N=5 T1D, 13.5 y, 7.3 to 19.4, P = NS). The aforementioned studies of Treg in T1D (115, 117) lacked agreement with respect to the question of whether functional differences exist between T1D patients and healthy individuals in the capacity of their CD4 + CD25 + T cells to suppress polyclonal stimulation of autologous Teff responses. In contrast to previous findings indicating reduced suppression by CD4 + CD25 + T cells from T1D patients (119), only a subtle reduction in their suppressive capacity was observed in this smaller study cohort (Fig. 3E, % suppression at a 1:1 Treg to Teff ratio 50.3 + 23.9 for T1D and 64.2 + 17.21 for controls, P = 0.42). As noted previously (119), a large variation in the degree of in vitro suppression was noted in this current investigation, particularly for the T1D group (open squares, Fig.

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53 4-5A). This observation is consistent with studies (118) suggesting that differences in Treg function are not, in fact, associated with T1D. While not the primary subject of this experiment, the issues of whether functional defects in Treg activity are specifically associated with T1D, as well as identification of the factors (e.g., age, disease duration, metabolic dysregulation, genetics, etc.) which underlie the marked degree of functional heterogeneity observed in Treg in certain patients with T1D, require further investigation. Discussion At a functional level, meaning the ability of Treg cells to suppress activities associated with Teff action, key differences were observed between persons with T1D and healthy controls. Those differences were associated with deficiencies in the suppression of Teff proliferation and the production of a number of cytokines. Specifically, our studies support a clear association between the production of IFNand TGFin the degree of suppression observed in vitro. The production of IL-2, while noted as being reduced in subjects with T1D, has for decades been noted as a defect associated with their cellular immune reactivity. In this context, if a dose dependent influence of IL-2 was required for the maintenance of the suppressive capacity of Treg, differences in the functional assays such as those in this study might be observed. This very issue of IL-2 signaling and receptor stability being a critical component to Treg function will be further addressed in Chapter 5. However, with this collective listing of cytokine variances, we must emphasize a notion mentioned previously that direct cell contact between Treg and Teff is thought, by a majority of published studies, to be a key facet to this process. Despite this, it remains

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54 plausible to speculate that the production of these cytokines may influence Treg function through effects on antigen presenting cells and Teff populations. While these studies support the potential for abnormal immune regulation in T1D, it must be emphasized that to date, there remains no definitive surface marker for Treg cells. An additional complicating factor for these types of analyses is the notion that the -chain of the IL-2R (i.e., CD25) is expressed across a continuum of cells, with the most potent suppressor function purportedly attributed to Treg cells comprising the bright population utilizing flow cytometric techniques (60). Such limitations, along with differences in methodology, may explain some of the discrepancies between our studies and those claiming no functional defects in T1D (115, 118). Unfortunately, the mechanisms conferring the suppressive capabilities of Treg are poorly understood and much of the data that does exist has been derived from murine systems. Most models suggest a requirement for direct cell-cell contact between Treg and Teff (20). In terms of soluble factors, direct suppressive functions of Treg appear to act independent of IL-10 and TGF(99, 128). Other studies suggest an important role for TGFbased on the association between a reduction of suppression with blockade of TGF(129, 130). A role for IFNin the process has also been suggested by studies involving indoleamine 2,3 dioxygenase and Treg (131). Indeed, this latter notion is an appealing hypothesis because it links the terminal activation of effector T cells with two mechanistic pathways which reinforce peripheral tolerance, those being IDO and through the action of Treg (reviewed by Brusko, et al. in (132)). One note of caution in these associations between cytokine elaboration and Treg function is that these studies were performed on a limited number of subjects.

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55 Considering the heterogeneity of responses, these findings need to be confirmed through analysis of larger populations of controls and type 1 diabetes patients. In addition, it would be of interest to know whether any possible defect is stable and presumably genetically determined, or whether defects in Treg activity are more transient, and thus potentially under the influence of environmental factors. Yet to be investigated are the interesting questions of whether age influences the regulatory functions of these cells in persons with T1D. Indeed, a study by Tsaknaridis et al. indicates that the suppressive capacity of Treg may actually decline with age (133). A study of Treg function through the natural history of disease is required to address these specific questions. One potential limitation of these studies is the potential for over interpretation of a defect lying solely in the CD25 + population over the CD25 population as our studies presented herein used CD25 cells from T1D patients as responders. While we did not observe significant differences in proliferation between T1D patients and control Teff cells, the T1D patient responses were lower and produced statistically significant lower levels of IFN-. Summary Finally, despite the conflicting reports and substantial overlap in the degree of suppression by Treg in T1D patients and controls, the therapeutic potential of this cell population holds great promise (134). This study provides preliminary support for functional defects in a population of cells critical for the maintenance of peripheral tolerance. The future employment of effective treatment modalities utilizing Treg should consider the functional defects outlined herein along with the mechanisms of control underlying them.

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CHAPTER 5 EXTENDED ANALYSIS OF REGULATORY T CELL FUNCTION This chapter outlines a series of experiments aimed at improving our understanding of the mechanism of action by Treg. Specifically, this chapter will outline a series of experiments investigating how surface and soluble forms of CD25 are differentially controlled between Treg and Teff cells. In addition, these experiments test the influence of serum on the in vitro suppression assay. Finally, these findings will be applied to experiments with provide a means to expand Treg in vitro, thus addressing important technical issues that can be utilized by future immunomodulatory therapies which seek to expand Treg populations in the treatment of autoimmunity. Introduction: The IL-2/CD25 Axis and Treg Function The notion of a “suppressor” or regulatory T cell (Treg) is not a new one, over 30 years ago, Gershon and Kondo recognized certain T cells possessed “suppressor” function (135). However, the lack of a specific marker with which to identify and isolate the population, lead in part, to waning interest in the field. Then, in 1995 the seminal work of Sakaguchi and colleagues reinvigorated that interest by identifying CD25 as a reliable marker for Treg (51). The high-affinity IL-2 receptor complex consists of three major sub-units; the -chain (designated CD25), the -chain (CD122), and the common cytokine receptor -chain (CD132) (136). Given that one of the defining features of Treg is expression of CD25 (the IL-2R chain), it is not surprising that IL-2 signaling has been found to play an important role in the development and function of these cells (137). Indeed, recent work in mice and 56

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57 humans has elucidated a critical role for the IL-2 axis in regulatory T cell development and function (92). The presence of IL-2, the IL-2 receptor, and IL-2 downstream signaling elements all appear critical for the development of a functional Treg compartment (80). In a series of elaborate studies, Rudensky and colleagues utilized a transgenic model expressing GFP under the Foxp3 promoter to track the presence of Treg (137). Utilizing this system, Rudensky was able to show both quantitative and qualitative defects in Treg activity following crosses with IL-2 and IL-2R deficient mice. Thus, Foxp3 + Treg, while not completely absent in IL-2 deficient mice, are functionally deficient in the absence of IL-2 signalling (137). A Dichotomous Role for IL-2 in Tolerance and Immunity The cytokine IL-2 has been recognized for over three decades to play a critical role in T cell proliferation in vitro (138), but only recently have we gained an appreciation for its somewhat paradoxical role in maintaining tolerance in vivo(139). IL-2 is mainly produced by CD4 + T cells, but the role of T cell-derived IL-2 in vivo is controversial (140). What forms the basis of this apparent dichotomy? The major findings that lead to the notion of IL-2 playing a central role in tolerance were the observations that mice deficient in IL-2, IL-2 receptor -chain, or IL-2 receptor chain exhibit hyperproliferative and hyperactive CD4 + T cells, resulting in lethal multi-organ autoimmune disease (65, 86, 141). Contrary to traditional theory, mice with these deficiencies still mount effective immune responses to a broad range of foreign antigens in the absence of IL-2 (reviewed in (139)). IL-2 does, however, contribute to T-cell immunity to foreign antigens in vivo, where it seems to be more important during the late stages of immune responses. Specifically, IL-2 has been shown to influence both the type and magnitude of effector T cell response in vivo as well as influencing the ability of T

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58 cells to track to non-lymphoid tissues (142, 143). Thus, IL-2 paradoxically contributes to both immunity and tolerance to foreign and self-antigens in vivo (140). Treg Require Stable CD25 Expression and Signalling While Treg constitutively express CD25, the receptor molecule is also upregulated on recently-activated effector T cells, thus rendering it an unreliable marker following activation (56, 129). This forms some of the basis for why FOXP3 is considered a more reliable marker of Treg. However, even in the case of FOXP3, its strict segregation to Treg is often questioned in humans (102, 104). Exposure of T cells to IL-2 both in vitro and in vivo (144) appears to drive FOXP3 expression in T cells by a pathway reported to involve STAT5 signaling (145). This process can be utilized for the polyclonal (146, 147) and antigen-specific expansion of Treg (148). What then, if anything separates Treg from Teff cells? One possible explanation can be gained from a recent study which suggests that the persistence and degree of antigen exposure alters the programmed response in T cells from a reactive phenotype to a more regulated response classically associated with Treg (149). CD25 Instability Predisposes to Autoimmunity If a stable IL-2 signal reinforces FOXP3 expression and Treg function, one would then expect situations which interrupt IL-2/CD25 signaling to interfere with Treg activity. One intriguing example of this situation was recently reported by Kohm and colleagues, who observed that the in vivo injection of CD25 monoclonal antibody led to the functional inactivation, but not the depletion of Foxp3 + Treg as was previously thought (150). The reduction in CD4 + CD25 + T cells was reportedly associated with increased internalization or “shedding” of surface CD25 on Treg. Mice treated with CD25 mAb were subsequently more susceptible to experimental autoimmune encephalomyelitis

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59 (EAE)(150). In addition, multiple reports in conditions of autoimmune disease and HTLV-1 associated lymphoma report elevated serum levels of the soluble form of CD25 (sCD25) and defective suppression by Treg (114, 151, 152). What is the basis for the generation of the sCD25 form? while an alternative splice variant can not be ruled out; it is generally thought that sCD25 is generated from the proteolytic cleavage from the surface of T cells (151). At least three candidates, to date, have been reported to be capable of cleaving CD25 including the endogenous enzymes elastase and matrix metalloproteinase-9 (MMP-9), and the house dust mite allergen Der P1 (153). This chapter will present our findings from a series of experiments investigating the control of both membrane and soluble forms of CD25 on Treg and Teff cell populations. In addition, this chapter will present data investigating the effects of serum on the in vitro suppression assay and on the functional activity of Treg. These concepts have important implications for Treg biology and in therapeutic modalities aimed at modulating Treg function. Methods The methods outlined in this section cover several modifications to the existing suppression assay previously described. In addition, this section will outline the methods utilized to determine the levels of soluble CD25 in tissue culture supernatants and in serum. In Vitro Suppression Assays under Serum-Free Media Conditions The isolation procedure outlined previously in Chapter 2 was modified to allow for the sorting of cells by high-speed cell sorting (FACSVantage Cell Sorter; BD Biosciences; San Jose, CA). For this series of experiments, samples were collected from

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60 seven normal healthy control subjects without any apparent autoimmune diseases (N=6 male, N=1 female; ages mean + SD 29.4 + 6.9 and median 26.3, range 25.54 to 42.34 yr). Cell Purifications Blood was collected in sodium heparinized blood collection tubes (40 ml total) (BD Biosciences) and processed as previously described to yield T cell depleted accessory cells and an untouched total CD4 + T cell fraction. The unlabeled CD4 + T cell fraction was subsequently stained by the addition of FITC anti-CD3 (clone HIT3a), PE anti-CD25 (M-A251), and APC anti-CD4 (SK3) antibodies at a volume of 20 l each/10 6 cells. To the staining cocktail, 1XPBS containing 2% human AB serum was added for a total staining volume of 100 l/10 6 CD4 + T cells. The staining cocktail was incubated for 30 min at 4C in the dark. Following staining, the resulting cell population was washed in 25 ml PBS/2% serum wash buffer, centrifuged at 300 x g, aspirated, and subsequently resuspended in 3 ml of the staining buffer prior to high-speed cell sorting. During the sorting procedure, purified CD4 + CD25 + and CD4 + CD25 T cell fractions were collected in sterile tissue culture tubes (BD Biosciences) containing cold (4C) AIM V serum-free media (SFM) (Invitrogen; Carlsbad, CA). Cell Culture To investigate the production of sCD25 from regulatory and effector T cells during the in vitro suppression assay, certain suppression assays were conducted in the presence of AIM V serum-free medium. This modification was employed because of the observation that the media conditions utilized previously (RPMI contained 5% human type AB serum) already contains high levels of sCD25 in the serum fraction. For certain experiments, freshly obtained autologous serum was supplemented into cultures containing AIM V medium.

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61 Soluble CD25 and Matrix Metalloproteinase Determinations sCD25 levels were determined by ELISA from serum and tissue culture supernatants that were collected and stored (-20C) according to manufacturer instructions (BD Biosciences). Serum was diluted 1:20 in 1XPBS containing 10%FBS (pH 7.0) assay diluent. To determine sCD25 levels in tissue culture supernatants, samples were diluted in assay diluent 1:10 and 1:20 when necessary. In addition, Matrix Metalloproteinase (MMP) levels (including MMP-1, 2, 3, 7, 8, 9, 12, and 13) were detected in serum and cell culture supernatant using the human MMP base kit (R&D Systems; Minneapolis, MN) on the Luminex xMAP platform and processed according to manufacturers recommendations. For certain in vitro experiments, a chemical inhibitor of MMP-9 ((2R)-[(4-Biphenylylsulfonyl)amino]-N-hydroxy-3-phenylpropionamide, used at an IC 50 of 250 nM) was added to assess its influence on T cell proliferation during the in vitro suppression assay (EMD Biosciences; San Diego, CA). In Vitro Expansion Experiments The ability to expand regulatory T cells facilitates extended studies of Treg which are normally at low frequency in peripheral blood (range 0.5.5% of peripheral blood cells). Treg expansion cultures were conducted from cells purified by high-speed cell sorting as previously described. To expand Treg, 1 x 10 4 cells per well were added with an equal number of anti-CD3 & anti-CD28 coated T cell expander microbeads (Invitrogen) in 96 well U-bottom plates (Costar; Cambridge, MA). Recombinant human IL-2 (Invitrogen); was added to cultures at a concentration of 10 ng/ml and replaced every 48 to 72 hrs when cultures depleted media substrates. Every 6 days, cells were harvested, washed in fresh medium, counted and then re-plated at the same bead to cell ratio to continue expansions.

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62 Results Soluble CD25 Levels in Serum of Patients with T1D Previous reports have indicated that the soluble form of CD25 (sCD25) is elevated following T cell activation and in certain forms of allergy and autoimmune disease (151). Therefore, we sought to investigate the levels of sCD25 in the serum of patients with T1D as well as from normal healthy controls (Fig. 5-1). Interestingly, elevated levels of sCD25 were detected in the serum of patients with T1D compared to normal healthy control subjects (Fig. 5-1A; mean + SD, 2616 + 1101 pg/ml for T1D patients versus 2039 + 899.8 pg/ml for control, P<0.0001. Figure 5-1. Elevated levels of soluble CD25 (sCD25) in the serum of patients with T1D. A) Serum sCD25 levels from normal healthy controls (N=60) and new-onset and established patients with T1D (N=94) A negative correlation exists between sCD25 and age in B) controls but not in C) patients with T1D.

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63 In light of the prior observations that age strongly influences the levels of CD25 expressed on the surface of cells (Chapter 2), we also questioned what effect subject age would have on the levels of sCD25 detected in serum. Interestingly, the opposite relationship observed for membrane-bound CD25 was observed with regard to the levels of soluble CD25 detected in serum of normal healthy controls. Specifically, control subjects observed a negative correlation between sCD25 levels and subject age (N=60; r=-0.28, P=0.03). On the other hand, patients with T1D exhibited no significant correlation between age and sCD25 levels (N=94; r=-0.08, P=NS). When the samples were then segregated into two groups (ie. those below the age of 20 y and those 20 and over), the group comparison only detected significant differences in sCD25 levels in the over 20 cohort (mean + SD, 2330.0 + 796.9 pg/ml for T1D patients versus 1847.0 + 751.4 pg/ml for control, P=0.002). Interestingly, a positive correlation was observed between the levels of MMP-9 and sCD25 detected in the serum of both patients and controls (N=119; Spearman r=0.23, P=0.05). This may suggest increased CD25 shedding in T1D, or perhaps, may simply result from inflammatory metabolic derangement in the case of long-term T1D. This matter could, in part, be addressed by future studies including patients with type 2 diabetes or possibly by correcting for alterations in HbA1c levels. Serum is Required for Suppression of Proliferation by Treg In order to isolate de novo sCD25 production from the high levels present in serum, suppression assays were conducted on FACS sorted cells in the presence of serum-free medium (SFM) (an example control sorting plot is shown in Fig. 5-2).

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64 Figure 5-2. FACS isolation of functional Treg and Teff cells. Plots depict A) isotype control or B) CD4 and CD25 staining from fresh peripheral blood. C) Whole blood was pre-enriched for total CD4 + T cells. D) Plots show sort gates for E) CD4 + CD25 Teff and F) CD4 + CD25 hi Treg cells. While the exact formulation of the serum-free medium is proprietary information, it is known to contain a fraction of human serum albumin as a carrier protein, human transferrin, and recombinant human insulin in addition to the other standard substrates, buffers, and antibiotics. Growth of both Treg and Teff cells in the presence of anti-CD3 & anti-CD28 coated beads under serum-free conditions over a three week period supported the capacity of this media to support viable cell growth (data not shown). Despite good cell viability, Teff cell responses were dramatically reduced under serum-free conditions. In contrast to the standard suppression response in the presence of serum, under SFM conditions Tregs fail to suppress proliferation and often lead to increased proliferation in the co-culture. In terms of suppression, under serum-free conditions, the percent suppression observed was -197.8 + 270.6 for SFM vs. 70.4 + 17.1 under SFM with 1.0% AS (N=7; P=0.04 at a ratio 1:1 Treg:Teff). This trend continued at a ratio of

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65 :1 Treg:Teff cell; -103.1 + 91.5 vs. 34.8 + 18.1, for SFM and 1%AS respectively (P=0.014) (Fig. 5-3). Figure 5-3. CD4 + CD25 + Regulatory T cells require serum for suppression of proliferation. Suppression assays were conducted in parallel under either A) serum-free media (SFM) conditions or in the presence of B) SFM supplemented with 1.0% autologous serum (AS) (N=7 normal healthy controls). C) The percent suppression calculated at a ratio of 1:1 Treg:Teff cells (left plots) under SFM conditions (open squares) and SFM with 1.0% AS (closed squares) and at a ratio of :1 Treg:Teff cells (right plots) . Graphs represent the mean + SD with situations identifying statistical significance indicated (*P<0.01).

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66 Ontogeny of Soluble CD25 during the Suppression Assay Soluble CD25 levels were determined from various co-culture conditions during the in vitro suppression assay (Treg:Teff ratio 1:0, 1:1, :1, 0:1, APC only, and APC + Ab) (Fig. 5-4). Figure 5-4. Production of soluble CD25 (sCD25) correlates with cellular proliferation in vitro in a time-dependent fasion. Supernatants from triplicate wells were pooled and analyzed for sCD25 by ELISA (N=7 control). Under both SFM and 1.0% AS, the highest levels of sCD25 were detected in the 1:1 Treg:Teff co-culture conditions (48 hr, A and B). At a later time point (96 hr, C and D) production of sCD25 correlates with cellular proliferation (see Fig. 5-3). At the 96 hr, the highest levels of sCD25 are observed in the 1:1 Treg to Teff co-culture under C) SFM conditions, as opposed to Teff cultures alone under D) 1.0% AS. Under both E) SFM and F) 1.0% AS conditions, the levels of cellular proliferation correlate with the amount of sCD25 production at all ratios of Treg to Teff cells (1:0, 1:1, :1, and 0:1; 96 Hr).

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67 Regulatory T cells Retain the Capacity to Suppress Effector Cytokine Production under Serum-free Conditions In light of the observation that Treg are dramatically reduced in their capacity to suppress Teff cell proliferation, we sought to assess the production of cytokines by effector T cells during the in vitro assay under serum-free conditions or containing autologous serum (Fig. 5-5). Figure 5-5. Regulatory T cells maintain the capacity to suppress certain effector T cell cytokines under SFM conditions. Pooled supernatants from suppression assay cultures (N=5) were assessed for the production of 22 cytokines on multiplex analyte detection platform. Standard suppression of effector T cell cytokine production by Treg was observed under both SFM and 1.0% AS for IFN(shown above for A) SFM and B) 1.0%AS), as well as for MCP-1, IL-3, IL-2, IL-1R, IL-12p40, IL-12p70, MIP-1, RANTES, TNF and IL-6. Increased cytokine production in the co-culture under SFM conditions was observed for IL-10 (shown above C and D), IL-5, IL-13, IL-10, GM-CSF, and IP-10. No variation was observed for IL-8, eotaxin, IL-7, IL-1, and IL-4. No detection (ND) indicates analyte readings were below the limit of detection for the assay.

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68 Surprisingly, even though higher levels of proliferation were observed in the co-culture under serum-free conditions when compared to effector T cell wells alone (Fig. 5-3A), cytokine production was still suppressed by Treg under serum-free conditions (Fig. 5-5A). This observation suggests that the control of proliferation and control of cytokine production may be under to distinct regulatory pathways. Protease and Protease Inhibitor Control of Suppression The observation that Treg express a stable form of CD25 during the in vitro suppression assay under standard serum-containing conditions raises several important questions. Are Treg and Teff cells producing different forms of CD25, with a soluble form predominantly expressed by Teff cells and a membrane-stable form predominantly produced by Treg? Is CD25 expressed in Teff culture wells more susceptible to proteolytic cleavage following activation? At least indirect support for this latter hypothesis was provided by Sheu and colleagues who described the capacity of cancer cells to upregulate the proteolytic enzyme matrix metalloproteinase-9 (MMP-9) and cleave CD25 from the surface of infiltrating T cells (155). Because MMP-9 is also formed in an autocrine fashion by T cells (156), it represents an attractive candidate to investigate for the generation of sCD25 during the in vitro suppression assay. In other words, are Teff cells responsible for producing high levels of proteases which are capable of cleaving membrane-bound CD25 into its soluble form? With this question in mind, supernatants were collected from suppression assay cultures of Treg and Teff wells during the suppression assay and assessed for the production of eight MMPs by multiplex immunoassay. Of the eight MMPs analyzed, only MMP-9 and MMP-7 were significantly elevated in Teff cell cultures compared to Treg wells (Fig. 5-6; 1.9 and 2.8 fold, respectively).

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69 Figure 5-6. Concentrations of matrix metalloproteinase-9 (MMP-9, gelatinase-B) and matrix metalloproteinase-7 (MMP-7, matrilysin) correlate with sCD25 levels and cellular proliferation during the in vitro suppression assay. Supernatants from suppression assay cultures (APC, APC+Ab, Treg, 1:1 Treg:Teff, Teff only) were pooled from six replicate wells for each condition and analyzed to determine the concentration of sCD25 along with 8 matrix metalloproteinases (R&D Systems). Shown above is the relationship between the levels of MMP-9 and A) sCD25 or B) cellular proliferation and MMP-7 and C) sCD25 or D) cellular proliferation. No correlation was observed for the MMPs-1, 2, 3, 8, 12, or 13 (not shown). Note the highest levels of MMP-9 and MMP-7 detection correspond to Teff wells which exhibited the greatest levels of proliferation during the in vitro suppression assay. We then wondered whether modulating the activity of MMP-9 in vitro would alter the in vitro suppression assay. To test this question, a chemical inhibitor of MMP-9 (gelatinase B) and the related enzyme MMP-2 (gelatinase A) was added to an in vitro suppression assay (Fig. 5-7).

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70 Figure 5-7. Selective inhibition of matrix metalloproteinases augments the suppressive index. Shown is a representative suppression assay set up in the presence of either a vehicle control (open bars) or a the selective MMP 2/9 inhibitor at the IC50 concentration of 250 nM. Note the increased Teff cell proliferation and increased suppression from 69 to 86 percent at a 1:1 Treg to Teff cell ratio and from 16 to 66 percent at a :1 ratio. Increased Teff cell proliferation represented the major outcome following MMP-2/9 inhibition. Similar results were obtained by using the broad-spectrum MMP inhibitor Galardin (Calbiochem, San Diego, data not shown). The In Vitro Expansion of Regulatory T Cells The ability to expand regulatory T cells in vitro has allowed for an extended phenotypic analysis of Treg by increasing the starting quantity initially obtained from peripheral blood (146). In addition, such an system has also been suggested as a possible therapeutic approach to increase the pool of polyclonal and antigen-specific Treg for the prevention of T1D (157). These reports clearly indicate that not only is it possible to expand Treg in vitro, but that the resulting cellular component appears to be augmented in functional capacity following these in vitro expansion protocols. For these reasons, we sought to develop our own means to expand regulatory T cells in vitro (Fig. 5-7).

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71 Figure 5-7. Phenotypic analysis of in vitro expanded human Treg and Teff cells. FACS sorted CD4 + CD25+ and CD4 + CD25 T cells were expanded in vitro over a 28 day period with the addition of exogenous IL-2 (10 ng/ml) along with anti-CD3 and anti-CD28 coated microbeads. The expanded T cells were subsequently surface stained with either A) isotype control antibodies or anti-CD4 and anti-CD25 (B and C; Teff and Treg respectively). In addition, D) intracellular FOXP3 expression was analyzed in Treg (red histogram) and Teff cells (green histogram along with appropriate isotype control (grey histogram). E) Note that Teff cells experience a lower level of CD25 and FOXP3 induction compared to expanded Treg. In vitro expanded CD4 + CD25 + T cells maintain their ability to suppress freshly isolated CD4 + CD25 T cells. It should be mentioned that the conditions necessary to overcome the normally anergic (and suppressive) phenotype of Treg include the provision of strong cross-linking anti-CD3 and anti-CD28 stimulation along with the addition of exogenous IL-2 (20). Under these expansion conditions, Treg do in fact produce sCD25 in the absence of all other cell types, although not to the same levels as expanding Teff cells (data not shown).

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72 Thus, these data might suggest that the anergic and suppressive state of Treg can be overcome by destabilizing CD25 on the surface of T cells. Discussion These data highlight critical and relatively uncharacterized aspects of the immune response, which likely play an important role in autoimmune disease initiation, progression, and potential resolution. These studies suggest the stability of CD25, as measured by supernatant sCD25 (Fig. 5-4D), follows the standard model of suppression. Thus, high levels of sCD25 correspond with elevations in T cell activation and proliferation. In addition, we have obtained data indicating essential constituents in serum contributing to the suppressive capacity of Treg and which are required for full activation of effector T cell responsiveness. By modulating the levels of proteases and protease inhibitors during in vitro suppression assays, we have observed that this interplay is critical to the amount of suppression afforded by Treg. Taken collectively, our preliminary data supports a novel model that predicts Treg, by the production of anti-apoptotic TGF-, may actually allow for immune progression early in the time course of an immune response as evidenced by the increased sCD25 observed in the co-culture at the 48 hr time point under both serum-free and replete conditions. Once Teff cells are fully active and producing proteases (Fig. 5-6), TGFmay be cleaved into its immunosuppressive active form (156). Thus, in the context of our previous findings regarding deficient suppression responses, we provide at least two novel mechanistic links between Teff cell responses and full immune resolution mediated by Treg in T1D: those being deficient signaling in the IL-2 axis and the ineffective activation of TGFon the surface of Treg.

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73 Conclusions Multiple studies now exist throughout the literature investigating the frequency of CD4 + CD25 + T cells and their relation to autoimmune diseases. Until now, very few of these studies simultaneously assessed both the surface and soluble levels of CD25 as a means of assessing T cell reactivity. These data support the possibility for increased soluble CD25 in the serum of patients with T1D, a finding that is now clearly linked with effector T cell activation and proliferation. Beyond the disease associations with sCD25, these studies uncover mechanistic pathways for novel therapeutic interventions aimed at altering the stability of CD25 on the surface of T cells by manipulating the balance of proteases and proteinase inhibitors. Despite the recent surge of interest in the field Treg and immunoregulation, very little is know about the exact mechanism of suppression by Treg. In an effort to isolate the de novo production of sCD25 from the levels present in serum, these studies serendipitously discovered a critical requirement for serum factors in the mechanism of suppression by Treg. A great deal of interest has recently been directed toward therapies which seek to Treg for therapeutic purposes. This observation contradicts traditional dogma that serum is required for optimal T cell growth and expansion and could aid efforts to expand polyclonal or antigen-specific Treg.

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CHAPTER 6 DISCUSSION AND CONCLUSIONS Discussion Immune therapies aimed at correcting the autoimmune basis of type 1 diabetes offer the greatest hope for the prevention and/or reversal of disease. For this hope to develop into practical therapies we must first understand the mechanistic defects in the immune system that precipitate the autoimmune destruction of insulin producing cells. In an effort to gain a better understanding for the defects within the immune system of individuals who develop T1D, we sought to investigate the frequency and function of a population of T cells which plays a critical role in maintaining peripheral tolerance--that being the population of regulatory T cells that co-express the phenotypic markers CD4, CD25, and the transcription factor FOXP3. In addition, these aims led us to more in depth mechanistic studies which highlight novel pathways controlling Treg function. Our initial studies focused on assessing the frequency of regulatory T cells in patients with type 1 diabetes and normal healthy controls by flow cytometric analysis of CD4 + CD25 + T cell frequencies. At first glance, our studies appeared to confirm the findings of Kukreja and colleagues who previously reported deficiencies in the frequency of CD4 + CD25 + T cells in patient with T1D (33). Subsequent analyses indicated that those observed differences were more likely attributed to differences in subject group age, rather than disease state. In fact, it appears the frequency of CD4 + CD25 +intermediate T cells is strongly influenced by subject age, with the frequency of these cells increasing most dramatically in youth (from birth to age 20). This increase in cells expressing 74

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75 intermediate levels of CD25 corresponds with a shift in the immune repertoire in individuals from cells expressing markers of a nave phenotype (CD45RA) to markers of an antigen experienced or memory phenotype (CD45RO). A longitudinal study of CD4 + CD25 + T cells indicated a remarkable degree of stability over relatively short periods of time (periods less than 3 years). Thus, the increase in cells expressing intermediate levels of CD25 most likely represents long-term changes in immune development rather than the presence of acutely activated T cells circulating in the periphery. Although not specifically the focus of these studies, additional experiments which depleted all CD25 + cells (by the addition of depleting antibody coated microbeads), did correspond to reductions in antigen-specific responses to foreign pathogens such as Candida. Thus, a portion of these cells may actually represent memory T cells (based on CD45RO expression), which express higher affinity IL-2 receptors primed for immune reactivity upon exposure. As noted through the text, one of the major limitations of the previous studies of CD4 + CD25 + T cells was their reliance upon CD25 as a sole marker of Treg. As indicated previously, activated T cells can also upregulate CD25, thus, raising the possibility of overestimating the true Treg pool. In an effort to address this limitation, our studies of Treg were extended to include the analysis of the transcription factor FOXP3. In line with our previous findings for CD4 + CD25 + T cells, no deficiencies in the frequency or absolute number of FOXP3 + T cells were observed. Despite this seemingly negative finding, we were able to extend our previous age associations by isolating the age effect to an increase in the frequency of cells which express intermediate levels of CD25 and are negative for FOXP3. Thus, the age-associated increases in CD4 + CD25 + T cells

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76 appears to reside outside of what would normally be considered the naturally occurring Treg population or CD4 + CD25 + FOXP3 + T cells. In order to gain a more complete understanding for the role of Treg in T1D, our studies of Treg were then extended to include an analysis of the functional capacity of these cells in vitro. Specifically, in vitro suppression assays were conducted on purified Treg populations and tested for their capacity to suppress the proliferation and cytokine production by co-cultured CD4 + CD25 T cells. This analysis indicated that although no defect in the frequency of Treg was observed in T1D, a function deficiency was detected in the capacity of Treg from patients with T1D to suppress proliferation by autologous Teff cells in vitro when compared to controls. This observation was accompanied by alterations in the cytokine profiles produced in the stimulated supernatants from both Treg and Teff cultures. Specifically, Teff cell responses from patients with T1D were deficient or reduced in the production of IL-2, IL-10, IFN-, and GM-CSF. Likewise, Treg responses from patients with type 1 diabetes were deficient in the production of the immunoregulatory cytokine TGF-. This is particularly interesting because the functionality of Treg has been linked to their capacity to produce TGF(129). In cytokine addition experiments, we confirmed previous reports which suggested TGFwas capable of upregulating both CD25 and FOXP3. In addition, other investigators have been able to show that TGFexpression under the rat insulin promoter in NOD mice causes a dramatic increase in the proportion of infiltrating T cells which express CD25 (greater than 40% of infiltrating cells) (111). Collectively, these findings suggest the restoration of TGFin a directed approach might serve as a possible therapeutic approach to averting diabetes related autoimmunity.

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77 Although the major portion of these studies is focused on Treg, we believe the in vivo function of these cells is intimately linked to the proper and effective function of effector T cells. Indeed, functional suppression by Treg is an active process that requires T cell activation, co-stimulation, and IL-2 signalling (27, 47, 137). Specifically in the setting of T1D, injection of neutralizing antibodies to IL-2 in NOD mice accelerates diabetes progression and produces a wide spectrum of T cell mediated autoimmune reactivities including gastritis, sialitis, thyroiditis, and severe neuropathy (73). From a genetic standpoint, the NOD IDD3 susceptibility locus is thought to contain IL-2 as the primary candidate gene, with a deficiency in production lending susceptibility to disease and other defects in tolerance induction (123). Thus, while defective Treg function may be a final outcome, it remains possible that these observed defects may initiate as a broad T cell activation defect or even larger immune defect when considering the broad influence of other cell types which can influence net helper T cell function. These notions question the paradigm that T1D results from a dominant, overaggressive immune response, and suggests that treatments which push immune activation and immunoregulation, rather than immunosuppression may be more therapeutically efficacious in the setting of T1D. Despite the surge in interest for Treg and the field of immunoregulation over the last decade, still very little is known about the mechanisms of suppression by Treg. Therefore, as part of these studies we also set out to gain a better understanding for the mechanisms which control Treg and Teff cell function. Two key observations were brought to light by this series of experiments. First, these experiments suggest that CD25 not only serves as a means of identifying Treg, but also remains expressed in a stable

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78 form following T cell activation. Effector T cells, on the other hand, upregulate CD25, but then shed it from the surface of cells. This rate of soluble CD25 generation is almost directly correlated to the amount of cellular proliferation observed when assessed by standard 3 H-thymidine incorporation. The second major finding is that specific factors within serum are required for full Teff cell responses and the suppressive properties of Treg. Contrary to the normal action of Treg, under serum-free conditions, Treg appear to lose their anergic properties and contribute to the proliferation observed in the suppression assay co-culture. In serum titration experiments, the addition of just one percent autologous serum was able to fully restore the anergic and suppressive capacity of Treg, while also bolstering Teff cell responses. This suggested that the critical factors that allowed for normal T cell reactivity were likely at relatively high concentrations in serum. This notion, and the findings of the sCD25 experiments, helped to identify three primary candidates which contribute to the properties of serum—those being TGF-, the serine proteinase inhibitor -1 anti-trypsin, and matrix metalloproteinase MMP-9. Although not the primary focus of this dissertation, these findings are being investigated further to gain a better mechanistic insight into Treg action and as possible targets for therapeutic treatments. Conclusions The experiments presented within this dissertation focus on the role of regulatory T cells in the pathogenesis of T1D. This cell population has been identified in both mice and humans to play a central role in maintaining peripheral tolerance and averting autoimmunity.

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79 Collectively, these studies suggest no deficiency in the frequency of Treg, but rather, do suggest defects in the functional capacity of Treg in T1D. Beyond the implications to T1D, these studies also identified key uncharacterized aspects of immune development with age and novel functional properties of Treg and Teff cells. The importance of these studies in human patients with T1D cannot be understated. While multiple challenges and limitations are associated with such studies, these represent perhaps the best hope for identifying the specific immune defects which allow for autoimmune destruction in T1D. Clearly the field is experiencing a renaissance, but before the therapeutic potential of Tregs can be realized, a great deal of work must be done. In particular, we need a better understand of the mechanisms by which Treg exert their suppressive effects. In addition, long-term studies are needed to assess the role of Treg through the natural history of disease. Although therapies are just now being suggested to exploit the therapeutic potential of Treg, these cells present perhaps the greatest promise for restoring antigen-specific tolerance for the prevention and/or reversal of T1D.

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APPENDIX A INFORMED CONSENT FORM TO PARTICIPATE IN RESEARCH IRB# 372-96_ Informed Consent to Participate in Research and Authorization for Collection, Use, and Disclosure of Protected Health Information If you are a parent, as you read the information in this Consent Form, you should put yourself in your child’s place to decide whether or not to allow your child to take part in this study. Therefore, for the rest of the form, the word “you” refers to your child. If you are an adult, child or adolescent reading this form, the word “you” refers to you. You are being asked to take part in a research study. This form provides you with information about the study and seeks your authorization for the collection, use and disclosure of your protected health information necessary for the study. The Principal Investigator (the person in charge of this research) or a representative of the Principal Investigator will also describe this study to you and answer all of your questions. Your participation is entirely voluntary. Before you decide whether or not to take part, read the information below and ask questions about anything you do not understand. If you choose not to participate in this study you will not be penalized or lose any benefits to which you would otherwise be entitled. 1. Name of Participant ("Study Subject") _____________________________________________________________________ 80

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81 2. Title of Research Study IMMUNE FUNCTION DURING VARIOUS STAGES OF INSULIN DEPENDENT DIABETES Sub Titles: PGS2 in the pathogenesis of IDD in humans and NOD Mice Monocyte Dysfunction in Pre-IDDM: Spontaneous Expression of Prostaglandin Synthase-2 The Role of Antigen Presenting Cells in the Immunopathogenesis of IDDM Antigen Presenting Cell and T-Lymphocyte Function in High and Low Risk Genotypes in Pre-IDD Mechanisms of Immunotherapy in IDD Prevention Trials Immune Function in High and Low Risk Genotypes in IDD Dendritic Cell Function in IDD Activation Induced Cell Death in Pre-IDD DQB1*0602 Relatives: Mechanisms for Disease Protection STAT5 and PGS2 Dysfunction in Type 1 Diabetes Immune Function and the Progression to Type 1 Diabetes B-Lymphocyte Subsets in Type 1 Diabetes PGS2 in the Pathogenesis of Type 1 DM Cellular Immunoregulation by DC and Diabetes Progression Cytokine Signaling in Autoimmune APC Dysfunction Development of Tolerogenic Dendritic Cells: Application of tolerogenic dendritic cells in prevention and reversal of type 1 diabetes in NOD mice Dysregulation of STAT5 in Autoimmune Disease

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82 Interferon / in Type 1 Diabetes Pathogenesis Immune Regulation and Type 1 Diabetes Pathogenesis 3. Principal Investigator and Telephone Number(s) Mark Atkinson, Ph.D. (352) 392-0048 (352) 514-1777 (for emergencies after hours) Michael Clare-Salzler, M.D. (352) 392-9885 4. Source of Funding or Other Material Support University of Florida The National Institutes of Health The Juvenile Diabetes Foundation American Diabetes Association The General Clinical Research Center 5. What is the purpose of this research study? It is currently believed that the immune system (the body’s defense mechanism) may be responsible for someone developing insulin dependent diabetes. You are being invited to participate in this study because you have one of the following – insulin dependent diabetes, non-insulin dependent diabetes, an autoimmune disease other than insulin dependent diabetes, no known autoimmune disease, or you are a relative of someone who has insulin dependent diabetes. The purpose of this study is to learn more about the genetics and immune function of blood cells, diet, and viruses in insulin dependent diabetes. It is our hope that the collection of such information will lead to improved ways of treating the disease as well as uncovering a method to cure (prevent) the disease. 6. What will be done if you take part in this research study? Blood samples will be drawn from you by experienced personnel at the time of the study. The amount of blood to be drawn from you will be up to 75 cc (which is equivalent to about 9 tablespoons). Your blood sample will be sent to a research lab where it will be tested for how well certain blood cells react to foreign substances. In addition, the blood cells will be tested for certain genes related to diabetes. Most tests will be performed immediately, however a small portion of your blood (about tablespoon) will be frozen for repeat testing (if necessary) at a later date. For most people, blood samples will be drawn on only one occasion. However, if your blood sample identifies you as being at

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83 increased risk for developing insulin dependent diabetes, you may be requested to participate further in this study by donating additional blood samples at time periods ranging from 3 to 12 months. These tests are for research purposes only and will not be entered into your medical records, as they are of unpredictable clinical value and as already stated, are for research purposes only. Your identity will be protected as everyone participating in these studies will be identified with a code number. These numbers will be utilized in all matters of communication (including research publications.). Only the Principal Investigator and data entry individuals have authority to unlock these protective codes. All information you provide (including these consent forms) will be kept in locked cabinets to which only the principal investigator or data administrator(s) have access. If you have any questions now or at any time during the study, you may contact the Principal Investigator listed in #3 of this form. 7. If you choose to participate in this study, how long will you be expected to participate in the research? Until the completion of the study. This information will be used and disclosed forever since it will be stored for an indefinite period of time. If you wish to withdraw, then your information will be destroyed and participation in the study stopped. 8. How many people are expected to participate in this research? Approximately 1600 subjects will be enrolled in this ongoing study. 9. What are the possible discomforts and risks? This is a laboratory study, so it poses no health risk to you, other than the minimal risks associated with drawing blood. The blood samples needed for this study will be drawn from you by experienced personnel. The risks of drawing blood from a vein include discomfort at the site of puncture; possible bruising and swelling around the puncture site; rarely an infection; and uncommonly, faintness from the procedure. Throughout the study, the researchers will notify you of new information that may become available and might affect your decision to remain in the study. If you wish to discuss the information above or any discomforts you may experience, you may ask questions now or call the Principal Investigator or contact person listed on the front page of this form.

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84 10a. What are the possible benefits to you? You may or may not personally benefit from participating in this study. Currently, there is no direct health benefit of this study for you. 10b. What are the possible benefits to others? One possible overall benefit of this study would be a better understanding of diabetes and why some have it. The knowledge we gain from this study may help in the future treatment of patients with this disease. 11. If you choose to take part in this research study, will it cost you anything? There are no financial risks for you participating in this study. You will not be charged for any expenses as a result of participating in this study. Costs for routine medical care procedures that are not being done only for the study will be charged to you or your insurance. These costs may not be charged if you are a veteran and you are being treated at the North Florida/South Georgia Veterans Health System (NF/SG VHS). 12. Will you receive compensation for taking part in this research study? You will not receive any monetary compensation for taking part in this research study. 13. What if you are injured because of the study? If you experience an injury that is directly caused by this study, only professional medical care that you receive at the University of Florida Health Science Center will be provided without charge. However, hospital expenses will have to be paid by you or your insurance provider. No other compensation is offered. Please contact the Principal Investigator listed in Item 3 of this form if you experience an injury or have any questions about any discomforts that you experience while participating in this study. 14. What other options or treatments are available if you do not want to be in this study? The option to taking part in this study is doing nothing: your consent is totally voluntary for participation. If you do not want to take part in this study, tell the Principal Investigator or his/her assistant and do not sign this Informed Consent Form.

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85 15a. Can you withdraw from this research study? You are free to withdraw your consent and to stop participating in this research study at any time. If you do withdraw your consent, there will be no penalty, and you will not lose any benefits you are entitled to. If you decide to withdraw your consent to participate in this research study for any reason, you should contact Dr. Mark Atkinson at (352) 392-0048 or Dr. Michael Clare-Salzler at (352) 392-9885. If you have any questions regarding your rights as a research subject, you may phone the Institutional Review Board (IRB) office at (352) 846-1494. 15b. If you withdraw, can information about you still be used and/or collected? As stated in item #6, a small amount of your blood will normally be kept for research. If you decide to withdraw from the study, tell Dr.’s Atkinson and Clare-Salzler and they will remove and destroy any of your blood sample that they will have. Otherwise, the samples may be kept until they are used up, or until Dr.’s Atkinson and Clare-Salzler decide to destroy them. In addition, information previously collected on your sample would no longer be included as part of these research studies. 15c. Can the Principal Investigator withdraw you from this research study? You may be withdrawn from the study without your consent for the following reasons: You do not qualify to be in the study because you do not meet the study requirements. Ask the Principal Investigator if you would like more information about this. The study is cancelled by the National institutes of Health (NIH) and/or other administrative reasons. 16. If you agree to participate in this research study, the Principal Investigator will create, collect, and use private information about you and your health. Once this information is collected, how will it be kept secret (confidential) in order to protect your privacy? Information collected about you and your health (called protected health information), will be stored in locked filing cabinets or in computers with security passwords. Only certain people have the legal right to review these research records, and they will protect the secrecy (confidentiality) of these records as much as the law allows. These people include the researchers for this study, certain University of Florida officials, the hospital or clinic (if

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86 any) involved in this research, and the Institutional Review Board (IRB; an IRB is a group of people who are responsible for looking after the rights and welfare of people taking part in research). Otherwise your research records will not be released without your permission unless required by law or a court order. If you participate in this research study, the researchers will collect, use, and share your protected health information with others. Items 17 to 26 below describe how this information will be collected, used, and shared. 17. If you agree to participate in this research study, what protected health information about you may be collected, used and shared with others? Your protected health information may be collected, used, and shared with others to determine if you can participate in the study, and then as part of your participation in the study. This information can be gathered from you or your past, current or future health records, from procedures such as physical examinations, x-rays, blood or urine tests or from other procedures or tests. This information will be created by receiving study treatments or participating in study procedures, or from your study visits and telephone calls. More specifically, the following information may be collected, used, and shared with others: Complete past medical history to determine eligibility criteria listed in informed consent Information about HIV/AIDS Information about hepatitis infection Information about sexually transmitted diseases Information about other infectious diseases that must be reported to Public Health authorities Records of physical exams Laboratory and other tests results Records about study medications or drugs Records about study results If you agree to be in this research study, it is possible that some of the information collected might be copied into a "limited data set" to be used for other research purposes. If so, the limited data set may only include information that does not directly identify you. For example, the limited data set cannot include your name, address, telephone number, social security number, or any other photographs, numbers, codes, or so forth that link you to the information in the limited data set. If used, limited data sets have legal agreements to protect your identity and confidentiality and privacy. 18. For what study-related purposes will your protected health information be collected, used, and shared with others?

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87 Your protected health information may be collected, used, and shared with others to make sure you can participate in the research, through your participation in the research, and to evaluate the results of the research study. More specifically, your protected health information may be collected, used, and shared with others for the following study-related purpose(s): to determine the defects in the immune system that lead to the development of insulin dependent diabetes to determine the genes that contribute to the development of insulin dependent diabetes and other autoimmune diseases to develop and evaluate new blood tests that will help determine whether an individual has a risk for developing insulin dependent diabetes and other autoimmune diseases to use this information to develop new ways to cure or prevent insulin dependent diabetes and other autoimmune diseases 19. Who will be allowed to collect, use, and share your protected health information? Your protected health information may be collected, used, and shared with others by: the study Principal Investigator Dr. Atkinson or Dr. Clare-Salzler and their staff other professionals at the University of Florida or Shands Hospital that provide study-related treatment or procedures the University of Florida Institutional Review Board 20. Once collected or used, who may your protected health information be shared with? Your protected health information may be shared with: the study sponsor National Institutes of Health, Juvenile Diabetes Research Foundation, and the American Diabetes Association United States and foreign governmental agencies who are responsible for overseeing research, such as the Food and Drug Administration, the Department of Health and Human Services, and the Office of Human Research Protections Government agencies who are responsible for overseeing public health concerns such as the Centers for Disease Control and Federal, State and local health departments 21. If you agree to participate in this research, how long will your protected health information be used and shared with others? Your protected health information will be collected until the end of the study. This information will be used and disclosed forever since it will be stored for an indefinite period of time in a secure database.” If you allow subjects to withdraw, you may wish to add the following sentence: “If you withdraw your permission for the use and sharing of

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88 your protected health information, then your information will be removed from the database. 22. Why are you being asked to allow the collection, use and sharing of your protected health information? Under a new Federal Law, researchers cannot collect, use, or share with others any of your protected health information for research unless you allow them to by signing this consent and authorization. 23. Are you required to sign this consent and authorization and allow the researchers to collect, use and share with others your protected health information? No, and your refusal to sign will not affect your treatment, payment, enrollment, or eligibility for any benefits outside this research study. However, you cannot participate in this research unless you allow the collection, use and sharing of your protected health information by signing this consent/authorization. 24. Can you review or copy your protected health information that has been collected, used or shared with others under this authorization? You have the right to review and copy your protected health information. However, you will not be allowed to do so until after the study is finished. 25. Is there a risk that your protected health information could be given to others beyond your authorization? Yes. There is a risk that information received by authorized persons could be given to others beyond your authorization and not covered by the law. 26. Can you revoke (cancel) your authorization for collection, use and sharing with others of your protected health information? Yes. You can revoke your authorization at any time before, during, or after your participation in the research. If you revoke, no new information will be collected about you. However, information that was already collected may still be used and shared with others if the researchers have relied on it to complete and protect the validity of the research. You can revoke your authorization by giving a written request with your signature on it to the Principal Investigator. 27. How will the researcher(s) benefit from your being in this study? In general, presenting research results helps the career of a scientist. Therefore, the Principal Investigator may benefit if the results of this study are presented at scientific meetings or in scientific journals.

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89 28. Signatures As a representative of this study, I have explained to the participant the purpose, the procedures, the possible benefits, and the risks of this research study; the alternatives to being in the study; and how the participant’s protected health information will be collected, used, and shared with others: ___________________________________________________________________ Signature of Person Obtaining Consent and Authorization Date Consenting Adults. You have been informed about this study’s purpose, procedures, possible benefits, and risks; the alternatives to being in the study; and how your protected health information will be collected, used and shared with others. You have received a copy of this Form. You have been given the opportunity to ask questions before you sign, and you have been told that you can ask other questions at any time. Adult Consenting for Self. By signing this form, you voluntarily agree to participate in this study. You hereby authorize the collection, use and sharing of your protected health information as described in sections 17 above. By signing this form, you are not waiving any of your legal rights. ___________________________________________________________________ Signature of Adult Consenting & Authorizing for Self Date Parent/Adult Legally Representing the Subject. By signing this form, you voluntarily give your permission for the person named below to participate in this study. You hereby authorize the collection, use and sharing of protected health information for the person named below as described in sections 17 above. You are not waiving any legal rights for yourself or the person you are legally representing. After your signature, please print your name and your relationship to the subject. ___________________________________________________________________ Consent & Authorization Signature Date of Parent/Legal Representative _____________________________________________________________________ Print: Name of Legal Representative of and Relationship to Participant:

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90 Participants Who Cannot Consent But Can Read and/or Understand about the Study. Although legally you cannot "consent" to be in this study, we need to know if you want to take part. If you decide to take part in this study, and your parent or the person legally responsible for you give permission, you both need to sign. Your signing below means that you agree to take part (assent). The signature of your parent/legal representative above means he or she gives permission (consent) for you to take part. __________________________________________________ __________________ Assent Signature of Participant Date Consent to Collect and Store Tissue For Future Research When Identify of Subject is Coded And the Codes are kept in Locked Files By the Person Conducting the Research As part of the research project Immune Function During Various Stages of Insulin Dependent Diabetes (and all subsequent subtitles), Dr. Mark A. Atkinson, would like to store some of your blood that is not needed for your medical treatment and that would otherwise be thrown away. If you agree, the samples will be kept in a specimen bank so that they may be used in future research to learn more about diabetes and other medical problems. Researchers are trying to learn more about diabetes, such as what causes diabetes, how to prevent it, how to treat it better and how, hopefully, to cure it. Even if the research that is done on your tissue cannot be used to help you, it might help other people who have diabetes or other medical problems. Many medical problems may arise due to the environment or from genetic factors. Your disease may come from one or both of these causes. Genetic factors are those that people are born with and that can affect other family members. There may be genetic testing done in the future that would provide information about traits that were passed on to you from your parents or from you to your children. The principal investigator of this study or his/her successor, will be responsible for making sure that your samples are protected in the specimen bank and that your medical information is kept confidential. Your samples will not be stored with your name or other identifying information but instead will be given a code number to protect your identity. The samples and this code number will only be given to researchers whose research is approved by the Institutional Review board (IRB). (An IRB is a group of people who are responsible for looking after the rights and welfare of people taking part in research.) The researchers will not be told who you are. Because of the nature and value of any future research cannot be known at this time, any results obtained from using your tissue will not be given to you or your doctor. The people who use your samples to do research may need to know more about your health. If researchers ask for reports about your health (information from your medical records,) the Principal Investigator will not give them or anyone else your name, address,

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91 or phone number (unless you are willing to be contacted in future to take part in more research). Although every effort will be made to keep your information confidential, there is a small risk that an unauthorized person may review your information. Therefore, there is a very slight risk that a test result could be linked to your identity and inadvertently disclosed you or to a third part. If you were to receive the result of a genetic test that indicated a problem, it could cause anxiety or other psychological distress. In addition, you might have to decide whether or not to discuss the findings with members of your family. If a third party (like your employer or insurer) learned the results, there is a risk of discrimination that could affect your employability or insurability, of stigma, and of the unpredicted disclosure of this information to others. You can discuss these issues further with your doctor or nurse and you can request a consultation with a genetic counselor if you wish to discuss these possible risks. In addition, there are laws that require that research records that have your name on them may be shown to people who make sure that the research is being done correctly. As mentioned in this consent form, the National institutes of Health, other sponsoring agencies, FDA and the Institutional Review Board have the legal right to review and copy your medical records related to this research. There will be no cost to you for any specimens collected and stored in the blood specimen storage bank. Your tissues will be used only for research and will not be sold. Some new products might be made because of the results of the research that uses your samples. These products might be sold sometime in the future, but, should this occur you will not get paid. The choice to let the investigators to keep your tissue for doing research is entirely up to you. No matter what you decide to do, it will not affect your care. If you decide that your tissue can be kept for research but you later change your mind, tell Dr. Atkinson who will remove and destroy any of your tissue that he still has. Otherwise, the sample may be kept until they are used up, or until Dr. Atkinson decides to destroy them. Please review statements 1, 2, 3, and 4 then circle the answer that is right for you. If you have questions, please talk to your doctor or nurse. I agree that my samples may be stored, coded to protect my identity, and that my identity will not be disclosed to anyone without my permission, except when required by law. YES NO Initials______ I agree that some excess blood tissue may be kept by Dr. Mark Atkinson for use in future research to learn about, prevent, treat or cure diabetes. YES NO Initials______ I agree that my blood tissue may be used for research to answer other medical questions that are not necessarily related to diabetes.

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92 YES NO Initials______ I agree that my doctor (or someone he/she chooses) can contact me in the future to ask me to take part in more research. YES NO Initials______

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APPENDIX B INSTITUTIONAL REVIEW BOARD APPROVAL LETTER 93

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95 13. Bach, J.F., and Chatenoud, L. 2001. Tolerance to islet autoantigens in type 1 diabetes. Annu.Rev.Immunol. 19:131. 14. Beard, M.E., Willis, J.A., Scott, R.S., and Nesbit, J.W. 2002. Is type 1 diabetes transmissible by bone marrow allograft? Diabetes Care 25:799. 15. Serreze, D.V., and Leiter, E.H. 2003. Tracking autoimmune T cells in diabetes. J.Clin.Invest 112:826. 16. Hori, S., Takahashi, T., and Sakaguchi, S. 2003. Control of autoimmunity by naturally arising regulatory CD4+ T cells. Adv.Immunol. 81:331. 17. Bach, J.F. 2002. Current concepts of autoimmunity. Rev.Neurol. (Paris) 158:881–886. 18. Kyewski, B., and Klein, L. 2006. A central role for central tolerance. Annu Rev Immunol 24:571. 19. Reijonen, H., Mallone, R., Heninger, A.K., Laughlin, E.M., Kochik, S.A., Falk, B., Kwok, W.W., Greenbaum, C., and Nepom, G.T. 2004. GAD65-specific CD4+ T-cells with high antigen avidity are prevalent in peripheral blood of patients with type 1 diabetes. Diabetes 53:1987. 20. Baecher-Allan, C., Brown, J.A., Freeman, G.J., and Hafler, D.A. 2001. CD4+CD25high regulatory cells in human peripheral blood. J.Immunol. 167:1245. 21. Atkinson, M.A., and Leiter, E.H. 1999. The NOD mouse model of type 1 diabetes: as good as it gets? Nat.Med. 5:601. 22. Rapoport, M.J., Lazarus, A.H., Jaramillo, A., Speck, E., and Delovitch, T.L. 1993. Thymic T cell anergy in autoimmune nonobese diabetic mice is mediated by deficient T cell receptor regulation of the pathway of p21ras activation. J.Exp.Med. 177:1221. 23. Gombert, J.M., Herbelin, A., Tancrede-Bohin, E., Dy, M., Carnaud, C., and Bach, J.F. 1996. Early quantitative and functional deficiency of NK1+-like thymocytes in the NOD mouse. Eur.J.Immunol. 26:2989. 24. King, C., Ilic, A., Koelsch, K., and Sarvetnick, N. 2004. Homeostatic expansion of T cells during immune insufficiency generates autoimmunity. Cell 117:265–277. 25. Lederman, M.M., Ellner, J.J., and Rodman, H.M. 1981. Defective suppressor cell generation in juvenile onset diabetes. J.Immunol. 127:2051.

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97 glutamate decarboxylase and coxsackie virus in insulin-dependent diabetes. J.Clin.Invest 94:2125. 37. Roep, B.O., Kallan, A.A., Duinkerken, G., Arden, S.D., Hutton, J.C., Bruining, G.J., and de Vries, R.R. 1995. T-cell reactivity to beta-cell membrane antigens associated with beta-cell destruction in IDDM. Diabetes 44:278. 38. Peakman, M., Stevens, E.J., Lohmann, T., Narendran, P., Dromey, J., Alexander, A., Tomlinson, A.J., Trucco, M., Gorga, J.C., and Chicz, R.M. 1999. Naturally processed and presented epitopes of the islet cell autoantigen IA-2 eluted from HLA-DR4. J.Clin.Invest 104:1449. 39. Brooks-Worrell, B.M., Starkebaum, G.A., Greenbaum, C., and Palmer, J.P. 1996. Peripheral blood mononuclear cells of insulin-dependent diabetic patients respond to multiple islet cell proteins. J.Immunol. 157:5668. 40. Alleva, D.G., Crowe, P.D., Jin, L., Kwok, W.W., Ling, N., Gottschalk, M., Conlon, P.J., Gottlieb, P.A., Putnam, A.L., and Gaur, A. 2001. A disease-associated cellular immune response in type 1 diabetics to an immunodominant epitope of insulin. J.Clin.Invest 107:173. 41. Viglietta, V., Kent, S.C., Orban, T., and Hafler, D.A. 2002. GAD65-reactive T cells are activated in patients with autoimmune type 1a diabetes. J.Clin.Invest 109:895. 42. Roep, B.O. 2003. The role of T-cells in the pathogenesis of Type 1 diabetes: from cause to cure. Diabetologia 46:305. 43. Arif, S., Tree, T.I., Astill, T.P., Tremble, J.M., Bishop, A.J., Dayan, C.M., Roep, B.O., and Peakman, M. 2004. Autoreactive T cell responses show proinflammatory polarization in diabetes but a regulatory phenotype in health. J.Clin.Invest 113:451. 44. Tree, T.I., Duinkerken, G., Willemen, S., de Vries, R.R., and Roep, B.O. 2004. HLA-DQ-regulated T-cell responses to islet cell autoantigens insulin and GAD65. Diabetes 53:1692. 45. Chatenoud, L., Salomon, B., and Bluestone, J.A. 2001. Suppressor T cells--they're back and critical for regulation of autoimmunity! Immunol.Rev. 182:149. 46. Janeway, C. 2001. Immunobiology : the immune system in health and disease. London ; New York, NY, US: Garland Pub. xviii, 732 p. pp. 47. Bach, J.F. 2003. Autoimmune diseases as the loss of active "self-control". Ann.N.Y.Acad.Sci. 998:161. 48. Homann, D., and von Herrath, M. 2004. Regulatory T cells and type 1 diabetes. Clin.Immunol. 112:202.

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98 49. Juedes, A.E., and von Herrath, M.G. 2003. Using regulatory APCs to induce/maintain tolerance. Ann.N.Y.Acad.Sci. 1005:128. 50. Godfrey, D.I., and Kronenberg, M. 2004. Going both ways: immune regulation via CD1d-dependent NKT cells. J Clin Invest 114:1379. 51. Sakaguchi, S., Sakaguchi, N., Asano, M., Itoh, M., and Toda, M. 1995. Immunologic self-tolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25). Breakdown of a single mechanism of self-tolerance causes various autoimmune diseases. J.Immunol. 155:1151. 52. von Boehmer, H. 2005. Mechanisms of suppression by suppressor T cells. Nat Immunol 6:338. 53. Sakaguchi, S. 2004. Naturally arising CD4+ regulatory t cells for immunologic self-tolerance and negative control of immune responses. Annu.Rev.Immunol. 22:531. 54. Takahashi, T., Kuniyasu, Y., Toda, M., Sakaguchi, N., Itoh, M., Iwata, M., Shimizu, J., and Sakaguchi, S. 1998. Immunologic self-tolerance maintained by CD25+CD4+ naturally anergic and suppressive T cells: induction of autoimmune disease by breaking their anergic/suppressive state. Int Immunol 10:1969. 55. Thornton, A.M., and Shevach, E.M. 2000. Suppressor effector function of CD4+CD25+ immunoregulatory T cells is antigen nonspecific. J.Immunol. 164:183. 56. Zola, H., Mantzioris, B.X., Webster, J., and Kette, F.E. 1989. Circulating human T and B lymphocytes express the p55 interleukin-2 receptor molecule (TAC, CD25). Immunol.Cell Biol. 67 ( Pt 4):233. 57. Bluestone, J.A. 1997. Is CTLA-4 a master switch for peripheral T cell tolerance? J.Immunol. 158:1989. 58. McHugh, R.S., Whitters, M.J., Piccirillo, C.A., Young, D.A., Shevach, E.M., Collins, M., and Byrne, M.C. 2002. CD4(+)CD25(+) immunoregulatory T cells: gene expression analysis reveals a functional role for the glucocorticoid-induced TNF receptor. Immunity. 16:311. 59. Fu, S., Yopp, A.C., Mao, X., Chen, D., Zhang, N., Chen, D., Mao, M., Ding, Y., and Bromberg, J.S. 2004. CD4+ CD25+ CD62+ T-regulatory cell subset has optimal suppressive and proliferative potential. Am.J.Transplant. 4:65. 60. Baecher-Allan, C., Brown, J.A., Freeman, G.J., and Hafler, D.A. 2003. CD4+CD25+ regulatory cells from human peripheral blood express very high levels of CD25 ex vivo. Novartis.Found.Symp. 252:67.

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99 61. Baecher-Allan, C., Wolf, E., and Hafler, D.A. 2006. MHC class II expression identifies functionally distinct human regulatory T cells. J Immunol 176:4622–4631. 62. Stephens, L.A., Mottet, C., Mason, D., and Powrie, F. 2001. Human CD4(+)CD25(+) thymocytes and peripheral T cells have immune suppressive activity in vitro. Eur.J.Immunol. 31:1247. 63. Bhandoola, A., Tai, X., Eckhaus, M., Auchincloss, H., Mason, K., Rubin, S.A., Carbone, K.M., Grossman, Z., Rosenberg, A.S., and Singer, A. 2002. Peripheral expression of self-MHC-II influences the reactivity and self-tolerance of mature CD4(+) T cells: evidence from a lymphopenic T cell model. Immunity. 17:425–436. 64. Hsieh, C.S., Liang, Y., Tyznik, A.J., Self, S.G., Liggitt, D., and Rudensky, A.Y. 2004. Recognition of the peripheral self by naturally arising CD25+ CD4+ T cell receptors. Immunity. 21:267. 65. Suzuki, H., Kundig, T.M., Furlonger, C., Wakeham, A., Timms, E., Matsuyama, T., Schmits, R., Simard, J.J., Ohashi, P.S., and Griesser, H. 1995. Deregulated T cell activation and autoimmunity in mice lacking interleukin-2 receptor beta. Science 268:1472. 66. Malek, T.R., Porter, B.O., Codias, E.K., Scibelli, P., and Yu, A. 2000. Normal lymphoid homeostasis and lack of lethal autoimmunity in mice containing mature T cells with severely impaired IL-2 receptors. J.Immunol. 164:2905. 67. Wolf, M., Schimpl, A., and Hunig, T. 2001. Control of T cell hyperactivation in IL-2-deficient mice by CD4(+)CD25(-) and CD4(+)CD25(+) T cells: evidence for two distinct regulatory mechanisms. Eur.J.Immunol. 31:1637. 68. Kagami, S., Nakajima, H., Suto, A., Hirose, K., Suzuki, K., Morita, S., Kato, I., Saito, Y., Kitamura, T., and Iwamoto, I. 2001. Stat5a regulates T helper cell differentiation by several distinct mechanisms. Blood 97:2358. 69. Takeda, I., Ine, S., Killeen, N., Ndhlovu, L.C., Murata, K., Satomi, S., Sugamura, K., and Ishii, N. 2004. Distinct roles for the OX40-OX40 ligand interaction in regulatory and nonregulatory T cells. J.Immunol. 172:3580. 70. Kumanogoh, A., Wang, X., Lee, I., Watanabe, C., Kamanaka, M., Shi, W., Yoshida, K., Sato, T., Habu, S., Itoh, M., et al. 2001. Increased T cell autoreactivity in the absence of CD40-CD40 ligand interactions: a role of CD40 in regulatory T cell development. J.Immunol. 166:353. 71. Scheffold, A., Huhn, J., and Hofer, T. 2005. Regulation of CD4+CD25+ regulatory T cell activity: it takes (IL-)two to tango. Eur J Immunol 35:1336–1341.

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100 72. Bayer, A.L., Yu, A., Adeegbe, D., and Malek, T.R. 2005. Essential role for interleukin-2 for CD4(+)CD25(+) T regulatory cell development during the neonatal period. J Exp Med 201:769. 73. Setoguchi, R., Hori, S., Takahashi, T., and Sakaguchi, S. 2005. Homeostatic maintenance of natural Foxp3(+) CD25(+) CD4(+) regulatory T cells by interleukin (IL)-2 and induction of autoimmune disease by IL-2 neutralization. J Exp Med 201:723. 74. Chen, W., Jin, W., Hardegen, N., Lei, K.J., Li, L., Marinos, N., McGrady, G., and Wahl, S.M. 2003. Conversion of peripheral CD4+CD25naive T cells to CD4+CD25+ regulatory T cells by TGF-beta induction of transcription factor Foxp3. J.Exp.Med. 198:1875. 75. Goudy, K.S., Burkhardt, B.R., Wasserfall, C., Song, S., Campbell-Thompson, M.L., Brusko, T., Powers, M.A., Clare-Salzler, M.J., Sobel, E.S., Ellis, T.M., et al. 2003. Systemic overexpression of IL-10 induces CD4+CD25+ cell populations in vivo and ameliorates type 1 diabetes in nonobese diabetic mice in a dose-dependent fashion. J.Immunol. 171:2270. 76. Nishibori, T., Tanabe, Y., Su, L., and David, M. 2004. Impaired development of CD4+ CD25+ regulatory T cells in the absence of STAT1: increased susceptibility to autoimmune disease. J.Exp.Med. 199:25. 77. Caramalho, I., Lopes-Carvalho, T., Ostler, D., Zelenay, S., Haury, M., and Demengeot, J. 2003. Regulatory T cells selectively express toll-like receptors and are activated by lipopolysaccharide. J.Exp.Med. 197:403. 78. Fehervari, Z., Yamaguchi, T., and Sakaguchi, S. 2006. The dichotomous role of IL-2: tolerance versus immunity. Trends Immunol 27:109. 79. Jiang, S., Game, D.S., Davies, D., Lombardi, G., and Lechler, R.I. 2005. Activated CD1d-restricted natural killer T cells secrete IL-2: innate help for CD4+CD25+ regulatory T cells? Eur J Immunol 35:1193. 80. Fontenot, J.D., and Rudensky, A.Y. 2004. Molecular aspects of regulatory T cell development. Semin.Immunol. 16:73. 81. Clark, L.B., Appleby, M.W., Brunkow, M.E., Wilkinson, J.E., Ziegler, S.F., and Ramsdell, F. 1999. Cellular and molecular characterization of the scurfy mouse mutant. J Immunol 162:2546. 82. Wildin, R.S., Ramsdell, F., Peake, J., Faravelli, F., Casanova, J.L., Buist, N., Levy-Lahad, E., Mazzella, M., Goulet, O., Perroni, L., et al. 2001. X-linked neonatal diabetes mellitus, enteropathy and endocrinopathy syndrome is the human equivalent of mouse scurfy. Nat.Genet. 27:18.

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101 83. Wildin, R.S., Smyk-Pearson, S., and Filipovich, A.H. 2002. Clinical and molecular features of the immunodysregulation, polyendocrinopathy, enteropathy, X linked (IPEX) syndrome. J.Med.Genet. 39:537. 84. Smyk-Pearson, S.K., Bakke, A.C., Held, P.K., and Wildin, R.S. 2003. Rescue of the autoimmune scurfy mouse by partial bone marrow transplantation or by injection with T-enriched splenocytes. Clin.Exp.Immunol. 133:193. 85. Sadlack, B., Merz, H., Schorle, H., Schimpl, A., Feller, A.C., and Horak, I. 1993. Ulcerative colitis-like disease in mice with a disrupted interleukin-2 gene. Cell 75:253. 86. Willerford, D.M., Chen, J., Ferry, J.A., Davidson, L., Ma, A., and Alt, F.W. 1995. Interleukin-2 receptor alpha chain regulates the size and content of the peripheral lymphoid compartment. Immunity. 3:521. 87. Suzuki, H., Zhou, Y.W., Kato, M., Mak, T.W., and Nakashima, I. 1999. Normal regulatory alpha/beta T cells effectively eliminate abnormally activated T cells lacking the interleukin 2 receptor beta in vivo. J.Exp.Med. 190:1561. 88. Leveen, P., Larsson, J., Ehinger, M., Cilio, C.M., Sundler, M., Sjostrand, L.J., Holmdahl, R., and Karlsson, S. 2002. Induced disruption of the transforming growth factor beta type II receptor gene in mice causes a lethal inflammatory disorder that is transplantable. Blood 100:560. 89. Waterhouse, P., Penninger, J.M., Timms, E., Wakeham, A., Shahinian, A., Lee, K.P., Thompson, C.B., Griesser, H., and Mak, T.W. 1995. Lymphoproliferative disorders with early lethality in mice deficient in Ctla-4. Science 270:985. 90. Bennett, C.L., Christie, J., Ramsdell, F., Brunkow, M.E., Ferguson, P.J., Whitesell, L., Kelly, T.E., Saulsbury, F.T., Chance, P.F., and Ochs, H.D. 2001. The immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome (IPEX) is caused by mutations of FOXP3. Nat.Genet. 27:20. 91. Khattri, R., Kasprowicz, D., Cox, T., Mortrud, M., Appleby, M.W., Brunkow, M.E., Ziegler, S.F., and Ramsdell, F. 2001. The amount of scurfin protein determines peripheral T cell number and responsiveness. J.Immunol. 167:6312–6320. 92. Fontenot, J.D., Gavin, M.A., and Rudensky, A.Y. 2003. Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. Nat.Immunol. 4:330. 93. Hori, S., Nomura, T., and Sakaguchi, S. 2003. Control of regulatory T cell development by the transcription factor Foxp3. Science 299:1057.

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BIOGRAPHICAL SKETCH Todd Michael Brusko was born on October 2, 1978 in Clearwater, Florida. He lived and attended school during his early youth in Seminole, Florida, where he attended and graduated from Seminole High School in 1997. Following high school, he attended St. Petersburg College in St. Petersburg, Florida, where he obtained an associate of arts degree. During this period, he worked as a laboratory assistant in the natural sciences department under Dr. Jack Gartner. He then moved to Gainesville, Florida, where he entered the College of Agriculture to obtain a bachelor’s degree in science, majoring in microbiology and cell science. During this time, he worked as an undergraduate technician in a laboratory studying the genetics of type 1 diabetes under the supervision of Dr. Jing-Xiong She. He proceeded to graduate in May 2001 with honors and was admitted to the Golden Key National Honor Society. It is at this time when he entered the laboratory of Dr. Mark Atkinson as a research laboratory technician investigating the immunological basis of type 1 diabetes. Following a year of research work experience, Todd entered the Interdisciplinary Program (IDP) in Biomedical Sciences in the College of Medicine at the University of Florida in August 2002. He joined the immunology concentration of the IDP and subsequently joined the laboratory of Dr. Mark Atkinson. It is there where he initiated studies investigating the mechanisms of cellular immune regulation conferred by regulatory T cells and their impact on the pathogenesis of type 1 diabetes. Following his doctorate work, Todd plans 108

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109 on continuing investigations into the immunological basis of type 1 diabetes by pursuing a post-doctoral position focused on mechanisms which confer immunological tolerance.