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1 GENETIC AND IMMUNOLOGIC BIOMARKERS IN TYPE 1 DIABETES By DUSTIN K. BLANTON A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2013
2 2013 Dustin K. Blanton
3 To Lori
4 ACKNOWLEDGMENT S Few accomplishments are achieved in isolation. This work is no exception. These efforts represent the product of investments made by many other individuals over a long period of time. I will name a small subset of the most important contributors here, but my gratitude extends to a broad network of people who provided practical, scientific, and moral support through the last several years. I am tremendously grateful for Drs. Mark Atkinson and Desmond Schatz, my science and clinical mentors, respectively. Dr. Atkinsons patience, scientific guidance, moral support, and hospitality allowed me to make of his lab a second home. The wor k environment that he has fostered is truly unlike any other I have ever seen, and I will miss the daily positive interaction. Dr. Schatzs depth of thought, forbearance, generosity of time and spirit, and attention to detail were critical to keeping me on the right track. His willingness to educate me as to the practical and medical aspects of diabetes care opened my eyes to the importance of our work. My appreciation for Clive Wasserfall cannot be overstated. His mentorship and guidance at every step of the way have been absolutely indispensible in the completion of this work. He has been nothing but supportive in every possible way, and his day to day instruction is the standard by which I will measure my own quality as a mentor in the future. My th anks to my committee members. Dr. Charles Baers thoughts on the genetic aspects of the work has greatly facilitated my efforts. More importantly, Dr. Baers training during my undergraduate career formed the foundation upon which I built my scientific v alues and career, and it was his example that showed me what g ood science could be. Dr. Nicks insight and candor have served to keep me grounded and
5 motivated, and without his knowledge and the support of his laboratory members (in particular Justin Bick ford and Kimberly Aiken), this work would not have been possible. I am grateful to Maigan Hulme, whose guidance and experience, particularly in the areas of cell culture and immunological assays, made much of the work possible. Similarly, Drs. Todd Brusko Daniel Perry, and James Thompson have provided indispensable aid throughout this work. I am grateful to my mentees, undergraduates and postgraduates who have been laboratory assistants, collaborators and coconspirators throughout the process. These in clude Peter Hong, Sarah Green, Adim Moreb, Candace Worsham, Giselle del Valle, Kyle Ziegler, and Andrea Warren. I am grateful to my lab mates for their moral and logistical support and collaboration; Kieran McGrail, Sean McGrail, Theresa Sumrall, Young Mee Yoon, Courtney Myhr, John Alexander, Song Xue, Matt Parker, Patrick Rowe, Taylor Davis, Ricky, Zack Webster, Zhao Han, Amanda Posgai, Lindsey Bierschenk, and Marcus Moore. I owe much to the University of Florida Genetics Institute Graduate Program staff, including Hope Parmeter, Mimi Zarate, Diana Nolte, Marta Wayne, Wilfred Vermerris, Connie Mulligan, and Jorg Bungert. I am indebted to the University of Florida Clinical and Translational Science Institutes TL1 graduate training program, and in particular the efforts of Drs. Wayne McCormack and Marian Limacher in my training program. I am grateful to my wife, Lori, whose patience, support, and dedication have made this work possible and worthwhile.
6 TABLE OF CONTENTS page A CKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 8 LIST OF FIGURES .......................................................................................................... 9 ABSTRACT ................................................................................................................... 10 CHAPTER 1 BACKGROUND .......................................................................................................... 12 Type 1 Diabetes: Etiology and History ................................................................... 12 Genotype, Environment, and Models of Pathogenesis ........................................... 13 Genetics of Type 1 Diabetes ................................................................................... 15 General Background ........................................................................................ 15 HLA Specific ..................................................................................................... 16 IL 2 Pathway .................................................................................................... 19 Environmental Influences on Type 1 Diabetes ........................................................ 21 General Background ........................................................................................ 21 Viruses ............................................................................................................. 23 Nutrition ............................................................................................................ 24 Vitamin D Pathway ........................................................................................... 25 Summ ary ................................................................................................................ 27 2 ASSOCIATION BETWEEN VITAMIN D BINDING PROTEIN GENOTYPE AND LEVELS AND DISEASE STATE IN TYPE 1 DIABETES ........................................ 33 Introduction ............................................................................................................. 33 Methods .................................................................................................................. 34 Participants ....................................................................................................... 34 VDBP levels ..................................................................................................... 35 SNP Genotyping ............................................................................................... 35 Statistical Methods ........................................................................................... 36 Results .................................................................................................................... 37 Levels of Serum VDBP Associate with Type 1 Diabetes .................................. 37 Serum VDBP Levels Associate with Gender, but Not Age or Serum 25OH Vitamin D Levels ........................................................................................... 37 VDBP Genotypes Do Not Associate with Type 1 Diabetes. ............................. 38 Discussion .............................................................................................................. 39 3 A SNP IN THE PROMOTER REGION OF THE INTERLEUKIN2 GENE IS ASSOCIATED WITH MODULATION OF HUMAN SERUM SCD25 LEVELS ......... 52 Introduction ............................................................................................................. 52
7 Methods .................................................................................................................. 56 Participants ....................................................................................................... 56 SNP Genotyping ............................................................................................... 56 Cell Culture E xperiments .................................................................................. 56 IL 2 Protein Detection by ELISA ....................................................................... 57 sCD25 Protein Detection by ELISA .................................................................. 57 Statistical Methods ........................................................................................... 57 Results .................................................................................................................... 58 Rs2069762 Genoty pe Frequencies by Disease State ...................................... 58 IL 2 Levels in Cell Culture and rs2069762 ....................................................... 58 sCD25 Levels in Human Serum and rs2069762 .............................................. 59 sCD25 Levels by Disease State ....................................................................... 59 Associations with Age and Type 1 Diabetes Duration ...................................... 60 Discussion .............................................................................................................. 60 4 IMPLICATIONS AND FUTURE DIRECTIONS ....................................................... 75 LIST OF REFERENCES ............................................................................................... 78 BIOGRAPHICAL SKETCH ............................................................................................ 93
8 LIST OF TABLES Table page 2 1 Hardy Weinberg equilibrium of patients and controls from Georgia samples ..... 42 2 2 Assocation analysis of VDBP SNPs rs7041 (G>T) and rs4588 (C>A) with type 1 diabetes. .................................................................................................. 43 2 3 Association an alysis of VDBP SNPs rs7041 (G>T) and rs4588 (C>A) after stratification for sex, onset of type 1 diabetes, and HLA risk ............................ 44 2 4 H eterogeneity tests to determine whether the odds ratios for homozygous genotypes significantly differ between stratified groups. ..................................... 46 3 1 rs2069762 Genotype by Disease State (Counts). .............................................. 65 3 2 rs2069762 Allele Frequencies ............................................................................ 66
9 LIST OF FIGURES Figure page 1 1 The Threshold Hypothesis.. ................................................................................ 29 1 2 Non HLA associated loci in type 1 diabetes. ...................................................... 30 1 3 CD4+ T cells recognize antigen in the context of MHC Class II. ........................ 31 1 4 The Vitamin D/VDBP system.. ............................................................................ 32 2 1 Serum levels of vitamin D binding protein by disease state .. .............................. 47 2 2 Serum levels of vitamin D binding protein by gender ......................................... 48 2 3 No association between VDBP levels and disease duration by linear regression analysis. ............................................................................................ 49 2 4 Linear regression of serum 25OH vitamin D levels and vitamin D binding protein levels.. .................................................................................................... 50 2 5 No statistically significant association between VDBP levels and genotype at rs7041 and rs4588. ............................................................................................. 51 3 1 IL 2 production measured by ELISA in stimulated PBMCs by rs2069762 genotype.. ........................................................................................................... 67 3 2 sCD25 levels by rs2069762 genotype. ............................................................... 68 3 3 Soluble CD25 levels by disease state in type 1 diabetes. .................................. 69 3 4 sCD25 by autoantibody positivity (GAD and IA 2). ............................................. 70 3 5 Disease state by age in type 1 diabetes. ............................................................ 71 3 6 Soluble CD25 lev els by age in type 1 diabetes. .................................................. 72 3 7 Soluble CD25 levels by disease duration in type 1 diabetes. ............................. 73 3 8 Genotype by age in type 1 diabetes. .................................................................. 74
10 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 GENETIC AND IMMUNOLOGIC BIOMARKERS IN TYPE 1 DIABETES By Dustin K. Blanton August 2013 Chair: Mark A. Atkinson Co chair: Desmond Schatz Major: Genetics and Genomics While human leukocyte antigen typing, autoantibody measurement, and the characterization of many regions affording genetic susceptibility have contributed tremendously to our ability to predict the onset of, comprehend the etiology of, and track the progression of type 1 diabetes, these approaches are far from complete in terms of their understanding Individuals with high risk human leukocyte antigen, autoantibody, and genotypic profiles still escape overt disease, while, in contrast individuals with low risk factors can progress to type 1 diabetes This may be due in part to the influence of environmental factors, but estimates suggest that up to one quarter of the heritability for type 1 diabetes remains unaccounted for by existing knowledge of the genetic architecture To that e nd, this effort sought to characterize genetic and immunologic biomarkers that might provide novel insight s into type 1 diabetes pathogenesis and progression. We investigat ed two pathways: the Vitamin D pathway and the i nterleukin2 /interleukin 2 receptor pathway ; th ese based on a variety of efforts that hinted at their potential involvement We observed an association between Vitamin D Binding Protein levels and disease state; individuals with type 1 diabetes have lower levels of Vitamin D
11 Binding Prot ein than controls. Relatives were intermediate between healthy controls and subjects with type 1 diabetes In vestigating the interleukin 2/interleukin2 receptor pathway, we observed an association between a T>G SNP in the promoter region of Interleukin2 (rs2069762) and serum levels of the soluble isoform of the Interleukin2 receptor component CD25. Specifically, t he G allele was associated with elevated serum levels of sCD25. Elevated serum levels of sCD25 were significantly associated with type 1 di abetes However, genotype at the rs2069762 locus did not directly associate with disease state. We have provided further evidence that the Vitamin D pathway is i nvolved in autoimmune diabetes, potentially not just at the level of Vitamin D itself, but also at the level of its principal transporter, Vitamin D Binding Protein. F urther investigation of the role of vitamin D binding protein, sCD25, r s2069762 and disease sta te in type 1 diabetes will be necessary before we can fully appreciate the meaning o f the complex interactions between genetics and environment that lead to type 1 diabetes
12 CHAPTER 1 BACKGROUND Type 1 Diabetes: Etiology and History Type 1 diabetes is a potentially fatal wasting disease. In the absence of therapy, patients exhibit polydipsia, polyuria, polyphagia, and severe weight loss all symptomatic of absolute insulin deficiency The five year survival rate for untreated type 1 diabetes is below 1 %, and this survival rate is still observed today in SubSaharan Africa where, in some cases, insulin is available less than 25% of the time [ 1 3 ] Since the 1921 discovery of insulin, most patients in industrialized nations have access to exogenous insulin. This lifesavin g t reatment has afforded many patients the opportunity to live long, healthy lives. Unfortunately, exogenous insulin therapy is not a cure; patients must conform to rigorous therapeutic protocols to minimize risk of any of a series of diseaseassociated complication s, including multiple finger pricks and needle sticks per day for blood glucose monitoring and insulin injection. Even with intensive therapy, patients still face risk of complications including neuropathy, retinopathy, and cardiovascular disease. The medical costs of patients with diabetes are approximately double the national average; diabetes patients incur about $7,900 of diabetes related expenses per annum [ 4 ] Diabetes is particularly burdensome in part due to its indiscriminate timing; the two peaks of onset for type 1 diabetes are between 5 and 7 years of age and during puberty [ 5 ] In this introduction, we will explore what is known about type 1 diabetes potentia l causative factors in the genotype and environment, the important role that biomarkers of
13 disease could play in detection and prevention of disease, and the relevance of the Interleukin2 ( I L 2 ) and Vitamin D pathways to the aforementioned factors. Genoty pe Environment, and Models of Pathogenesis Type 1 diabetes is a complex autoimmune disorder in which aberrant immune recognition of self antigen ( s) is believed to result in a T cell mediated attack on the insulin secreting pancreatic beta cells located in the islets of Langerhans. This results in a progressive decline in pancreatic beta cell mass concurrent with progressive insulin insufficiency ultimately leading to a loss of glycemic control Clinically, p atients typically present with polydipsia, polyuria, and polyphagia [ 5 8 ] at which time they are diagnosed via blood sugar and confirmed as ype 1 with autoantibody testing. After confirmation of diagnosis, patients are followed closely by health care professional s and are typically prescribed an intensive regimen consisting of frequent blood sugar testing, multiple daily injections or the administration of insulin via an ins ulin pump. Poor control can lead to long term complications including nephropathy, neuropathy, vascular disease, and retinopathy and acute, potentially lifethreatening complications including hypoglycemic coma and diabetic ketoacidosis. I t is believed th at an inciting event in the pancreatic islet leads to a release of self antigen [ 9 ] These antigens are then picked up by antigen presenting cells, which subsequently migrate to the nearby pancreatic lymph nodes. There, antigen is p resented via MHC (major histocompatibility complex) class II molecules to nave autoreactive T and B cells [ 10] These cells then become armed effector and memory cells, proliferating and expanding in the lymph node, secreting inflammatory cytokines and entering circulation through the lymphatic ducts. The immune response expands as effector cells are drawn to the site of inflammation and initiate beta cell destruction,
14 releasing additional epitopes and driving a broader attack by cells with diverse antigen specificities. A utoantibodies to self antigens are produced by B cells; in humans, auto antibodies to insulin is most often the first to occur; others including glutamic acid decarboxylase (GAD), insulinoma antigen 2, Zn transporter ZnT8, and likely a host of other epitopes [ 11 ] often follow These autoantibodies are the most commonly used means of diagnosing and attemp ting to predict type 1 diabetes Though the sensitivity of autoantibody assays is greater than 70% in new onset patients autoantibodies can be found in individuals who do not progress to type 1 diabetes and there exist individuals who progress to type 1 diabetes but who do not exhibit detectable auto antibodies [ 1214 ] This fact has led experts in the field to note, there are no biomarkers of the disease process that are reliably correlated with the pathogenic process [ 15] For this reason, a need exists to develop reliable biomar kers of disease progression and treatment efficacy. There have been many models of disease pathogenesis and progression over the years, all of which have sought to reconcile the competing pathogenic and protective influences of genetic and environmental factors. Models from the mid80s to the early 2000s focused on progression through stages, with an environmental trigger acting upon a genetically predisposed individual to incite a progression to overt disease marked by decline of beta cell mass and capaci ty to regulate blood glucose [ 8 16] Others have expanded upon these ideas, pointing out the possible contributory role of the beta cell itself and the internal cytokine environme nt to antigen availability, and highlighting the role of internal and external environmental stressors like childhood obesity which could contribute to the release of beta cell antigens [ 17 19]
15 With this, it appears clear, the p athogenesis of type 1 diabetes is a complex, multifactorial process that may require tissue and timespecific antigen presentation and T cell specificity to multiple self antigens, and further, the relative importance of th e various factors involved (i.e., beta cel ls, immune system, and environment) may vary from patient to patient [ 20] To reflect this complexity, a threshold m odel has been recently proposed which takes into account the relative input of genetic and environmental contributions to total risk and accounts for the possibility that the relative contributions of each may vary on a per patient basis according to some as yet unknown (and likely highly variable) function [ 21] (Figure 1 1) The discussion below will consider each of these contributors individually and will discuss how novel biomarkers might contribute to our understanding of disease pr ogression and treatment efficacy, especially in light of recent developments in our understanding of diabetes Genetics of Type 1 Diabetes General B ackground The concordance rate for type 1 diabetes among monozygotic twins has been estimated at 50%, but more recent estimates reveal that, on longer timelines, concordance rates approximate 65% [ 22 ] By comparison, the nonmonozygotic sibling risk is 5 6%, suggesting that shared environment does not explain the concordance between monozygotic twins and suggesting a powerful role for genetics [ 23, 24 ] The ratio between sibling risk and general population risk, known as s, for type 1 diabetes is between 12 and 15, suggesting a moderate influence of heritable factors on disease progres sion [ 25 27] Type 1 diabetes does not follow any particular pattern of inheritance. There are more than 60 known susceptibility regions for type 1 diabetes most of which were
16 identified through genome wide association studies (GWAS), but the susceptibility in few of these regions has been mapped to a specific variant or even to a s pecific gene [ 23, 28, 2 9 ] (Figure 1 2 ) While approximately 8 0% of the heritability can be explained by the genes identified thus far a surprisingly high proportion, as compared to other complex disease there remains considerable unaccounted for (or missing ) heritability in type 1 diabetes [ 23 28 30, 31] This heritability could be attributed t o as yet uncharacterized structur al variation, it could be attributable to rare variants of large effect, similar to the highly protective but extremely rare recently discovered variants of interferon induced with helicase C domain 1 ( IFIH1 ) or it could b e a product of genegene or geneenvironment interactions [ 31 32] Clearly, m ore work needs to be performed to characterize the regions of disease susceptibility, the genes w ithin them, and the various alleles of these genes. As noted above, t ype 1 diabetes involves interaction between t he endocrine and immune systems and as such there are multiple opportunities for genetic defects to influence the course of disease. From antigen presentation to cell signaling molecules, from genes that govern and allow the expansion of self reactive cells to those that interfere with immune regulation, as well as those that influence beta cell surv ival and possible regeneration; there are many pathways that could hypothetically be implicated in the disease process [ 29] Among the important known risk regions are the human leukocyte antigen ( HLA ) region which contributes an o verwhelming majority of risk (i. e., odds r atio of 6.8) insulin, the alpha subunit of the IL 2 receptor, and IL 2 itself [ 29 33 ] HLA S pecific The HLA region, a 3.6 Mb 7.6 Mb region in chromosome 6 (6p21.3), accounts for ~ 50 % of the genetic risk associated with type 1 diabetes [ 34 37] The HLA region
17 codes for the M HC molecules, and the region is distinguished by high degrees of both poly gen y and polymorphism in order to address a broad range of potential antigens There exist three classes of MHC molecules: class I, found on nearly all cell types and responsible for presentation of antigen to CD8 cytotoxic T cells, class II, found on pr ofess ional antigen presenting cells and responsible for presenting antigen to CD4 helper T cells, and class III, which encodes for other immune (particularly complement) proteins. In type 1 diabetes the principal risk is associated with alleles in the MHC class II region. MHC class II alleles are expressed as transmembrane heterodimers composed of an alpha chain and a beta chain (Figure 1 3) These MHC proteins function to present antigen to CD4+ helper T cells, as T cells will not recognize antigen and will not activate without the context of MHC. There are three MHC class II antigen receptors that participate directly in antigen presentation to T cells; these are HLA DP, HLA DQ, and HLA DR. Genes encoding the HLA DP apha and beta chains may have as m any as 23 and 120 alleles circulating in a population respectively Genes encoding the HLA DQ alpha and beta chains may have as many as 32 and 68 alleles circulating, respectively HLA DR has but one locus for the alpha chain, which is largely invariable, but nine loci for the beta chain, usually two of which (DRB 1 and typically one other) may be expressed in any individual. DRB 1 is highly polymorphic, with over 500 variants known [ 38] With respect to how the combination of these complex fact ors contribute to disease pathogenesis, the late George Eisenbarth has long championed the idea of the trimolecular complex [ 39] Here, three molecules are necessary for pathogenicity.
18 These molecules, the T cell receptor, the MHC molecule, and the insulin peptide (and in specific, insulin B9 23) are required for the generation of an autoimmune response [ 39] While unproven, currently, an extensive effort has been extended to testing this model. Because there exists a high degree of linkage disequilibrium in the MHC, risk is generally associated with haplotypes; in fact, the term haplotype, for haploid genotype, was coined due to the study of the HLA region [ 40 41] The HLA DR/DQ haplotypes that account for 30 50% of genetic risk of type 1 diabetes are DR3 DQA1*0501*0201 (DR3) and DR4A DQA1*0301DQB1*0302 (DR4 ) [ 37, 42] There also exist s at least one protectiv e h aplotype, DRB1*1501DQB1*0602 [ 43, 44] albeit not absolute. MHC c lass II related loci are not the only regions of interest within the MHC. Fine mapping data from the Type 1 Diabetes Genetics Consortium indicates that MHC class I regions HLA A and HLA B are also independently associated with type 1 diabetes [ 45 ] Finally, c areful analysis reveals the likelihood that additional risk variants for type 1 diabetes exist within the extended MHC region, but outside of the class II region; clearly, further study is needed to fully elucidate the level of involvement of the extended MHC region in disease [ 35, 46 47 ] It is important to note that the strength of association between markers does not necessarily depend upon their map locations and so, the discussed markers may actually be somewhat distant from etiological loci [ 48] Further, interaction may be taking place between the HLA locus and nonHLA loci, as evidence suggests that risks at nonHLA loci may be reduced in the presence of high HLA related risk [ 49] Despite
19 the shortcomings, it does remain clear that genotyping in the HLA region continues to be an extremely useful marker for stratifying disease risk [ 50 ] IL 2 P athway IL 2 as a target of interest in type 1 diabetes research IL 2 has been known as an important factor for T cell proliferation for more than three decades [ 51 53] This critical role for IL 2 in T cell growth, combined with data as early as 1974 suggesting a role for cell me diated immunity and MHC involvement in type 1 diabetes mean that IL 2 has long been a target of interest in type 1 diabetes with deficient synthesis of IL2 observed in patients with type 1 diabetes as early as 1984 [ 54 ] Of the more than 60 known sus ceptibility genes for type 1 diabetes three lie within the IL2 pathway (IL2RA, PTPN2, and IL2), with one in particular, IL2RA, having an odds ratio of over 1.50 and multiple single nucleotide polymorphisms (SNPs) contributing to disease risk [ 28 29 49] It is likely that IL 2 levels a re carefully controlled for proper immune regulation, as a reduction as modest as twofold in IL2 levels has shown to predispo se non obese diabetic mice to autoimmune diabetes [ 55] Translation to the human system has proven to be a challenge, however; high doses of IL2 in NOD mice have been shown to accelerate autoimmune destruction, leading to concern about the potential for adverse outcomes in human patients under IL2 therapy [ 56] A recent study using IL2 in combination with Rapamycin (administered with the intent of prevent excessive immune activation) led to a transient decrease in c peptide levels, suggesting the possibility of harm to beta cell function and further underscoring the need for caution [ 57] Structure and Function of IL2 and its receptor Human IL 2 is a 15 KDa cytokine that serves as a key regulator of immune function through its secretion by CD4+ and CD8+ T cells, activated dendritic cell s, natural killer cells, and natural killer T
20 cells [ 53, 5860 ] The IL 2 receptor is composed of three subunits, an alpha chain (referenced as IL2r or CD25), a beta chain (referenced as IL2r or CD122) and a common gamma chain (IL2r or CD127). The beta and gamma chains together form an intermediate affinity receptor that is expressed on T cells, natural killer cells, and mon ocytes [ 61 ] Low to intermediate concentrations of IL2 signaling through the receptor will promote memory or effector phenotypes, while high conce ntrations can drive activation induced cell death in conventional T cells [ 62 ] The alpha chain in combination with the beta and gamma chains forms the high affinity IL 2 receptor, which is transiently expressed on T effector cells B cells, dendritic cells, natural killer cells, and eosinophils but which is only constitutively expressed on regulatory T cells [ 63 66 ] Mutations in the human CD25 gene can lead to severe a u toimmunity and immune dysfunction [ 67 68 ] The gene for IL2, located at 4q27, is composed four exons and codes for four alpha helices (Figure 1). The beta chain is shar ed between the IL2 receptor and the IL15 receptor The gamma chain, referred to as the common gamma chain, is found in receptors for IL 2, IL 4, IL 7, IL 9, IL 15, and IL 21 [ 69] IL 2 Is a Key Immunoregulatory Cytokine While early data undersc ored the relevance of IL 2 to effector T cell expansion (it was first known as T cell growth factor), data have subsequently demonstrated that mice deficient in IL2 or IL 2 receptor experience severe autoimmune reactions but retain their ability to mount an effective immune response once the autoimmunity has been dealt with [ 70 71] Immune dysfunction in IL2/IL 2 receptor deficiency is rescued by the introduction of purified
21 C D4+CD25+ cells. These observations suggest that IL 2 signaling is critical for the function of the regulator y T cells subset [ 72] As regulatory T cells do not manufacture their own IL2 the primary sources for IL 2 used in regulatory T cell maintenance are likely to be activated CD4+ T cells and dendritic cells [ 63 73 74] Further, IL 2 is known to inhibit its own production through STAT and Blimp 1 dependent signaling pathways [ 75, 76 ] IL 2 also appears to promote activation induced cell death after subsequent antigen receptor stimulation in T cells [ 77 ] These observations, taken together, suggest a powerful role for IL2 in re gulation, and a more redundant role in T cell growth and proliferation [ 53] Given its importance to immune regulation, the frequency with which it appears in association studies, and the diversity of potential targets within the pathway, the IL 2 pathway makes an excellent candidate for investigation in pursuit of biomarkers. En vironmental Influences on Type 1 Diabetes General B ackground Environmental factors make an attractive target for modulation in the interest of disease prevention, as the environmental component of disease may in most cases be more straightforwardly altered or compensated for than the genetic component [ 78 ] The incidence of diabetes varies over 100 fold globally, from 0.1/100,000 cases per year in China to 40.9 per 100,000 per year in Finland, with an average increase in incidence worldwide of 2.8% per annum [ 79 80] Evidence of north south gradients in incidence along with the presence of seasonal and temperature based variation in incidence all point to a nontrivial role for environment al factors in the pathogenesis of type 1 diabetes [ 81 83 ]
22 An ecological analysis has found associations between incidence of disease and gross domest ic product, milk consumption, and cof fee consumption, suggesting the potential that multiple factors correlating with the socioeconomic status may influence risk of diabetes ; one potential explanation for this observation is the hygiene hypothesis, in which children who are not exposed to immune challenge are more vulnerable to disease later in life [ 84 85 ] These observations are temper ed, however, by studies in which children born of parents from highrisk regions move to regions of more modest risk. Sardinia is known to be of remarkably high incidence (37 per 100,000 per year) and interestingly, children of Sardinian parents born in the Lazio region, in the mainland of Italy, had a type 1 diabetes incidence fourfold higher than their Lazioheritage peers [ 86 ] It is possible, however, that intergenerational environmental effec ts may be impacting this result, and other studies have demonstrated a marked increase in incidence when moving from low to high susceptibility regions [ 87, 88 ] Other studies have shown the converse; second generation immigrants to Sweden (which has an incidence of 29 per 100,000 per year) showed markedly decreased incidence compared to their Swedish peers, and even lower incidents if their parents were both from outside of Sweden. Results were similar for foreign children adopted by Swedish parents [ 89] To further elucidate potential environmental causes of type 1 diabetes a number of large collaborations have been undertaken, including the Baby Diabetes (BABY DIAB) study, the Diabetes Autoimmunity Study (DAISY), the Enviornmental Triggers of Diabetes Determinants in the Young (TEDDY) study, and the Trial to Reduce IDDM in the Genetically At Risk (TRIGR) study [ 21] While no environmental factors have thus
23 far been definitively established as either necessary or sufficient for type 1 diabetes development much interest has developed in t wo primary areas: viral infection and nutritional factors. Viruses The seasonality of diabetes onset and temporal and spatial clustering suggest a role for infectious disease in diabetes pathogenesis [ 90] A viral role in pathogenesis iN could take place through encouragement of betacell directed autoimmunity (for example, through antigenic mimicry), t hrough direct beta cell killing, or via antigen release subsequent to killing (known as bystander effect) [ 91 ] To date, as many as fourteen viruses have been associated with disease pathogenesis in human and animal models [ 91] The most prominent of these have been enteroviruses in general and Coxsackievirus B4 (CVB4) in specific. Enterovirus RNA was detected in the blood of five of twelve French new onset type 1 diabetes patients as compared to none of the controls [ 92] CVB4 isolated from the pancreas of a type 1 diabetes patie nt was found to induce hyperglycemia and beta cell necrosis in laboratory mice, a result that was recapitulated in human pancreatic islet cells in vitro [ 93, 94] Cocksackie B4 P2 C protein is known to elicit immune response from PBMC that also respond to GAD peptides, suggesting the possibility of molecular mimicry between the two [ 95] It is clear that considerable evidence exists to suggest a potential viral role in type 1 diabetes. This evidence i s tempered by the knowledge that incidence of disease is higher in regions with higher socioeconomic status (and better sanitation and hygiene), and lower in areas with higher population density and household crowding; these observations are contrary to what we would expect if virus exposure was a
24 primary governing factor of disease progression [ 84, 96] The importance of viral involvement in disease pathogenesis will depend on how necessary viral infection is to the disease process; it is likely that infection is just one of several pathways by which antigen presenting cells may be exposed to beta cell antigen. Nutrition There has been much discussion regarding the relative influences of cows milk exposure and breastfeeding in the pathogenesis of type 1 diabetes Dietary exposure to cows milk proteins or infant formula may increase risk of autoimmunity, while greater duration of breastfeeding has been propose d to offer protection [ 97, 98] A recent, large meta analysis seems to have found broad support for the as sociation between duration of breastfeeding and protection from type 1 diabetes in the literature, possibly due to protection from enterovirus infection [ 99 100 ] Wheat gluten may also be an important contri butor to the pathogenic process, as comorbidity between type 1 diabetes and the autoimmune wheat gluten sensitivity known as coeliac disease is higher than would be expected at random and there are a number of genes that associate with risk to both conditions [ 101 ] In non obese diabetic (NOD) mice, a wheat gluten diet has a complex relationship with progression to type 1 diabetes, with both low and high levels of wheat gluten apparently protecting from disease [ 102 ] Exposure to a wheat gluten diet appears to promote an inflammatory, interferon gamma driven response in the NOD gut [ 103 ] Finally, introduction of glutencontaining food before three months of age in members of the BABYDIAB study cohort led to an increased risk of islet autoantibodies, with four of seventeen babies who received gluten affected, all of whom had the DRB1*03/04, DQB1*0302 high risk HLA genotype [ 104 ]
25 Vitamin D P athway Observations regarding the seasonality of diabetes onset and a northsouth gradient in type 1 diabetes incidence, particularly in Europe, led to interest in the role of the Vitamin D pathway in this disease [ 81 82 105 ] Vitamin D is received primarily through two means; through dietary sources (primarily fortified milk and fatty fishes), and through ultraviolent B driven synthesis in the skin (Figure 1 4) The vitamin D precursor is 7dehydrocholesterol which is converted into its active form via two hydroxylation steps, one in the liver (by CYP2R1) which produces 25h ydroxyvitamin D3 (25 (OH)D3) and the other in the kidney or in other cells like monocytes and macrophages (by CYB27B1) which produces the final active form, 1 25(OH)2D3 25 (OH)D3 is the primary circulating form, around 85% of which is bound to Vitamin D Binding Protein (VDBP), the balance of which is bound to albumin (~15 %) Vitamin D acts primarily through the nuclear Vitamin D receptor (VDR), which leads to signaling that regulates gene transcription [ 78 106 ] Gener ally, Vitamin D levels in the blood are measured via 25(OH)D3 assays, because 25(OH)D3 is found as much higher levels in the blood and is generally therefore easier to measure. Further, clinical observations suggest that patients with Vitamin D deficiency can still have normal measurements for 1 25(OH)2D3 [ 78, 107 ] Consensus on what constitutes a normal Vitamin D level remains elusive; different levels have been measured for optimal calcium absorption (34 ng/mL) [ 108 ] optimal neuromuscular performance (38 ng/mL) [ 109 ] and reduction of breast c ancer incidence (52 ng/mL) [ 110 ] All told, r ecommendations for adequacy range from the low 30s to 40 ng/mL [ 111 ] If we take deficiency to be serum levels of 25(OH)D3 below 20 ng/mL,
26 evidence suggests that between 30 and 50% of the global population is at risk of Vitamin D defic iency [ 112 ] This widespread deficiency is almost certainly of clinical importance. Most cell types express the vitamin D receptor and Vitamin D is involved in the transcriptional regulation of at least 229 genes [ 78 113 ] Vitamin D is known to be important in autophagy and the promotion of antimicrobial response [ 78, 114 115 ] T he Vitamin D receptor is found on antigen presenting cells and activated T cells [ 116 117 ] and the active form, 1 25(OH)2D3 is secreted by macrophages and dendritic cells 1 25(OH)2D3 appears to promote a tolerogenetic response, downregulating expression of MHC class II and Th1 cytokine interleukin12 while inducing Foxp3 expression [ 116 118120 ] Vitamin D also appears to act as a necessary component of Phospholipase C 1 induction, modulating TCR signaling and T cell activation, revealing a complex role for Vitamin D in both tolerance and TCR sensitivity [ 121] With respect to type 1 diabetes in particular, multiple steps in the Vitamin D pathway are implicated in multiple steps of the etiological pathway. A promoter polymorphism in CYB27B1, which performs the final hydroxylation step to convert Vitamin D to its active form, are associated with type 1 diabetes and other autoimmune conditions [ 122 ] Vitamin D deficient NOD mice demonstrate impaired glucose tolerance followed by a doubling of diabetes incidence [ 123 ] Cohort studies in the UK and in the US military have demonstrated association between Vi tamin D deficiency and type 1 diabetes [ 78 124 ] Studies in Florida have failed to recapitulate these results, possibly due to a masking of the effect by low levels of Vitamin D in both patient and control populations [ 125 ] VDR has been shown to bind intronically to PTPN2, a known
27 type 1 diabetes susceptibility regio n and data suggest an inductive effect [ 113 ] Studies have found association between polymorphisms for the gene encoding the principal transporter of Vitamin D, VDBP, and typ e 1 diabetes [ 126 127 ] Summary Current approaches for type 1 diabetes screening include HLA genotyping and autoantibody screening [ 29] For HLA genotyping, an HLA DR3/4 individual with an affected sibling has a 55% chance of becoming concordant for type 1 diabetes by age 12, and an 85% risk of islet autoimmunity by age 15 [ 29, 128 ] For autoantibody screening, the likelihood of progression to disease scales with the numb er of autoantibodies detected, with three or four islet autoantibody markers (GAD, IA 2A, IAA, and IA 2B) a ssociating with a risk of >60% over 5 year s. Specifically, IAA plus one additional marker associating with a risk of > 5 0 %, ICA plus one additional m arker associating with a risk of ~ 50%, any two assoc iating with a risk of > 2 5 %, with single markers alone ranging from 3 to 9% risk [ 129 130 ] Combining knowledge of family history with HLA genotype allows up to 1000fold risk stratification. Some have considered combining HLA genotype with islet autoantibody status for risk stratification, but HLA genotype partially determines autoantibody risk and so these are not independent measures [ 50, 131 ] While these approaches afford some means of prediction and screening, they are not perfect [ 1214 ] Researchers have observed that high risk HLA haplotypes are decreasing in their representation among new onset cases, suggesting that the interplay between genotype and environment in autoimmune diabetes is complex and dynamic [ 132 ] Thus, t here exists a need for additional reliable biomarkers of disease progression and treatment efficacy that may also serve as novel targets for therapeutic
28 intervention or tools for the personalization of t reatment [ 15 29] In terms of pure genetic/immunological pathways of interest, t he IL2 pathway serves as a remarkable candidate pathway, owing to its multiple representation in association studies for type 1 diabetes and the high degree of biological relevance of the pathway to autoimmune disease [ 29 49 63 ] With regard to the relati onship between disease state and environment, a compelling case exists for a more detailed understanding of the role of Vitamin D in autoimmune disease in general and type 1 diabetes in specific. With these foci in mind, we sought to identify and characterize biomarkers for type 1 diabetes
29 Figure 11 The Threshold Hypothesis T1D likely initiates as a function of the contributions of genetic and environmental risk factors with varying odds ratios. VNTR, variable number of tandem repeats. Reprinted from Diabetologia, 54(9), Wasserfall et al., The Threshold Hypothesis: Solving the Equation of Nurture vs Nature in Type 1 Diabetes, pp. 22322236, copyright 2011, with kind permission from Springer Science and Business Media.
30 Figure 12 Non HLA asso ciated loci in type 1 diabetes. Reproduced with permission from the New England Journal of Medicine 360, Concannon et al., Genetics of Type 1a Diabetes, pp. 16461654 Copyright 2009 Massachusetts Medical Society.
31 Figure 13 CD4+ T cells recognize antigen in the context of MHC Class II. Copyright 2007 from Janeways Immunobiology, Seventh Edition by Murphy et al. Reproduced with adaptation by permission of Garland Science/Taylor & Francis LLC.
32 Figure 14 The Vitamin D/VDBP syste m Vitamin D3 is synthesized in the skin or absorbed through the intestine, then converted by CYP2R1 in the liver into 25(OH)D3 and converted by CYP27B1 in the kidneys or in macrophages Reprinted from Trends in Endocrinology and Metabolism, 16(6), Mathieu and Badenhoop, Vitamin D and type 1 Diabetes Melitus: State of the Art, pp. 261266, copyright 2005 with permission from Elsevier
33 CHAPTER 2 A SSOCIATION BETWEEN VITAMIN D BINDING PRO TEIN GENOTYPE AND LEVELS AND DISEASE STATE IN TYPE 1 DIABETES Introduction Various pathways and char acteristics of vitamin D metabolism, such as vitamin D analogues and polymorphisms in the vitamin D receptor as well as genes encoding specific vitamin D enzymes, have recently been associated with type 1 diabetes [ 133 135] R educed serum vitam in D concentrations have been associated with up to 3.5 times greater risk of progression to type 1 diabetes [ 78 124 134 136 ] but vitamin D deficiency is not uncommon [ 125 137 ] Vi tamin D therapy (active form) can modulate the development of disease in the nonobese diabetic mouse model of type 1 diabetes [ 138 139 ] and a variety of trials have tested whether vitamin D supplementati on has the capacity to modify the development of this disease [ 134 ] To that question, a metaanalysis of trials seeking such a therapeutic benefit suggests that vitamin D supplementation can reduce disease risk [ 140 141 ] Finally, Vitamin D may be involved in promoting an anti inflammatory phenotype through upregulation of FOXP3, a key signaling factor in the development of regulatory T cells, defects in which have been shown in recent years to have a crucial role in the etiology and progression of type 1 diabetes [ 63, 120 ] .1 Reprinted from Diabetes, 60, Blanton et al ., Reduced Serum Vitamin D Binding Protein Levels Are Associated With Type 1 Diabetes, pp. 25662570, copyright 2011, with kind permission from the American Diabetes Association.
34 This said, despite our current understanding of the vitamin D pathway, including its capacity to modulate the immune system [ 137 ] the causal relationship between impaired vitamin D constituents and the development of type 1 diabetes remains uncertain. This is larg ely due to the intricate nature of vitamin D metabolic processes, as well as the extensive biological effects exhibited by its components. Therefore, understanding the influence of the vitamin D pathway on the pathogenesis of type 1 diabetes requires a sy stematic examination into the distinct roles of its various components. One essential component of the vitamin D pathway is the polymorphic vitamin D binding protein (VDBP), also known as group specific component (Gc). Aside from its main function of vi tamin D transport and preservation, VDBP has been shown to scavenge actin, bind fatty acids, activate macrophages, stimulate osteoclasts, enhance chemotactic activity of C5derived peptides, and associate with immune cell surfaces, such as T and B cells [ 142] Even after ligand binding, 9899% of VDBP binding sites remain unoccupied, which suggests a function beyond vitamin D transport [ 142 ] While several studies have associated specific VDBP gene polym orphisms with the presence of diabetes (i.e., type 1 diabetes and type 2 diabetes) [ 126 127 ] we sought to confirm this association and identify differences in VDBP level s in patients with type 1 diabetes Methods Participants Banked serum samples from a total of 472 individuals in Florida who participated in studies on the natural history of type 1 diabetes were grouped into the following cohorts: controls (n=153, median age 21.0 years, range 5.056.0 years, 85 female), patients with type 1 diabetes (n=203, median age 14.5, range 4.062.6; 96 female), and
35 first degree relatives of those with type 1 diabetes (n=116, median age 21.0, range 1.062.6, 56 female). Of this stu dy group, DNA from 53 controls, 81 patients, and 38 relatives were further analyzed by SNP genotyping for VDBP polymorphisms (SNPs rs4588 and rs7041). Previously banked DNA samples from a second study cohort consisting of 1,502 patients and 1,880 healthy controls collected at the Georgia Health Sciences University, obtained from a national population from the U.S., were also genotyped. All samples were collected under informed consent with the approval of the University of Florida and Georgia Health Sciences Universitys Institutional Review Boards. VDBP levels VDBP levels were quantified in duplicate with a commercial EIA kit (ALPCO; Salem, NH) using 10 L of banked serum from each subject. Levels of VDBP were interpolated from a standard curve after reading the absorbance on a M5 Spectramax plate reader using Softmax Pro 4.8 software (Molecular Devices, Sunnyvale, CA). The intra and inter assay coefficients of variation for this assay were 5.0% and 12.7%, respectively. The published normal reference r ange for VDBP levels is 300600 g/mL [ 142 ] Correlation analysis was also performed for a subset of the VDBP serum samples (n=386), which had previously been measured for 25OH vitamin D levels [ 125 ] This subset included 152 controls, 141 type 1 diabetes patients, and 93 first degree relatives. SNP G enotyping For the initial University of Florida data set, 200ng of genomic DNA was used to amplify an 809 bp fragment with primers 5 CAAGTCTTATCACCATCCTG 3 and 5 GCCAAGTTACAATAACAC 3 as previously published [ 126 ] The amplicons were gel
36 purified using GENE CLEAN Turbo kit (MP Biomedicals; Aurora, OH) to ensure no inhibition of restriction enzymes. For verification of the rs4588 and the rs7041 SNPs, PCR products were digested with StyI and HaeIII respectively and the genotypes were determined by gel electrophoresis on a 1.52% agarose gel. For the data set collected under the auspices of the University of Georgia, the SNPs were genotyped using TaqMan PCR genotyping, with modifications, as previously described [ 143 ] All primers and probes used in this study were designed and validated by Applied Biosystems (Foster City, CA). Amplification reactions were performed in a 5 L final volume in optical 384well plates. PCR was carried out with 2 min at 50C, 10 min at 95C followed by 40 cycles of 15 sec at 95C and 1 min at 60C using an ABI9700 Real Time PCR system (Applied Biosys tems). To validate the TaqMan assays, five SNPs were also genotyped using standard amplified restriction fragment length polymorphism (ARFLP) analysis. Statistical Methods Analysis of multiple, unpaired group comparisons was achieved using the nonparamet ric Kruskal Wallis test. Dunn's post test was used for multiple testing corrections if the Kruskal Wallis test was significant. The association of age and disease duration with VDBP levels was analyzed by linear regression. To determine the relationship b etween VDBP levels and gender, the nonparametric MannWhitney test was used. All analyses were performed using GraphPad Prism software ver 5.00 (Software Inc.; San Diego, CA). The association between each VDBP SNP and type 1 diabetes was assessed by calc ulating the odds ratios (OR) separately for each genotype, as well as for total allelic frequency (i.e., heterozygous and homozygous minor allele combined). The Pearson's chi 2) and Fisher's exact tests were
37 used to test the differences in genotype and allele (respectively) distribution between patients and control subjects. Statistical significance was defined as p <0.05. We used the Breslow Day test to examine heterogeneity in the ORs between subsets stratified for age at onset, sex, and HLA risk status. Hardy Weinberg equilibrium (HWE) of the genotypic frequencies among cases and controls was examined separately. Results Levels of S erum VDBP A ssociate with T ype 1 D iabetes Serum VDBP levels (median, range, interquartile range [IQR]) for the three study groups were as follows: healthy controls (423.5 g/mL; 193.54345.0; 354.1586.7), first degree relatives (402.9 g/mL; 204.74850.0; 329.6492.4), and type 1 diabetes patient s (385.3 g/mL; 99.31305.0; 328.3473.0) (Fig. 2 1 ). Median VDBP serum levels were significantly lower in patients with type 1 diabetes than controls (p=0.003), type 1 diabetes patients. Due to a lack of availability, s erum VDBP levels were not measured for the Georgia samples. In finding VDBP levels were significantly lower in the presence of type 1 diabetes we then questioned whether the duration of disease influenced VDBP levels. Linear regression analysis indicated that disease duration did not associate with VDBP levels (p=0.516, r =0.003). Serum VDBP L evels A ssociate with G ender, but N ot A ge or S erum 25 OH V itamin D L evels It has previously been shown that gender influences VDBP levels [ 144 ] Therefore, we performed gender analysis with regard to VDBP levels to identify any correlations within our study participants (Fig. 2 2) The 472 study participants distributed into two near identical gender based cohorts of 238 females and 233 males.
38 Se rum VDBP levels were significantly higher in females (433.4 g/mL; 99.324850.0; 359.4567.8) versus males (374.7 g/mL; 188.91602.0; 326.9449.9; p<0.0001) Gender distribution between type 1 diabetes patients, relatives, and controls was not significan tly different (p=ns), reducing the likelihood that group composition contributed to the aforementioned association between type 1 diabetes and serum VDBP levels. We next sought to determine whether age influenced serum levels of VDBP. Linear regression analysis revealed that age did not associate with VDBP levels in our study population (p=0.164, r =0.004) (Fig. 2 3) We previously noted that individuals with type 1 diabetes had insufficient serum levels of 25OH vitamin D though this finding was not sp ecific for those with the disease [ 125 ] To determine whether a correlation exists between serum 25OH vitamin D and VDBP levels, we analyzed VDBP levels on banked serum from a large subset ( n=386) of the 25 OH vitamin D cohort (Fig. 2 4) Interestingly, we found no association (p=0.557, r2=0.001) between these two analytes, irrespective of study group (152 controls, 141 patients, 93 relatives). VDBP G enotypes D o N ot A ssociate with T ype 1 D iabetes. The rs4588 and rs7041 VDBP genetic variants were analyzed in the type 1 diabetes patients and controls whose DNA had been banked at the Georgia Health Sciences University for studies regarding the genetics of this disease [ 145 ] Cases and controls were found to be in Hardy Weinberg equilibrium for the two SNPs analyz ed ( Table 21 ) There were no significant differences in the allele and genotype frequencies of the VDBP rs4588 and rs7041 genetic variants among patients with type 1 diabetes and controls ( Table 22 )
39 We next tested whether the association between these SNPs is dependent upon other covariates, such as gender of the subjects, age of disease onset (i.e. early onset being under 18 years of age), or HLA DQB1 genotypes (Table 23) No significant association was detected when patients were stratified by gender or age of disease onset. A heterogeneity test further showed no difference in odds ratios between males and females or between early and late onset subsets ( Table 24 ) We then determined whether the high risk HLA DQB1 genotype was associated with the SNPs. All subjects were classified into two subsets, a highrisk DQB1 genotype subset (i.e., 0201/0201, 0302/0302 or 0201/0302) and a low risk DQB1 genotype subset (i.e., all others). There was no significant association of the rs4588 and rs7041 SNPs in e ither the low or highrisk HLA DQB1 subsets after correction for multiple testing ( Table 23 ). Since the pvalues for these tests are heavily influenced by the smaller number of control subjects carrying the highrisk HLA genotypes, we performed heterogeneity tests to determine whether the odds ratios differed between the high and low risk subsets. We found no significant difference between the odds ratios of the HLA DQB1 risk subsets ( Table 24 ). Finally, we investigated the possibility of an association between genotype at rs4588 and rs7041 and levels of serum VDBP. No such association was observed (Fig 2 5). Discussion The major finding in our study adds further credence to the concept that the vitamin D pathway may play a significant role in the development of type 1 diabetes While previous studies have associated the rs4588 and rs7041 VDBP SNPs with the disease [ 126 127 ] we were unable to support that conclusion in this largescale study
40 and we were unable to associate levels of VDBP with genotype at either of these loci However, we were able to associate the phenotype of lower VDBP levels with type 1 diabetes While the exact consequence of this association remains unknown, the fact that VDBP has immunomodulatory characteristics and is responsible for transport of vitamin D metabolites supports, in theory, a model whereby the impact of reduced serum levels may be significant enough to lend itself, directly or indirectly, to the autoimmune dest ruction of pancreatic cells in the disease. Our findings also suggest another means by which VDBP levels are influenced, beyond the VDBP SNPs tested here, must exist and will certainly be subject to future investigations A recently published study assessing V DBP levels in 100 healthy, middleaged and older participants found that women had higher mean VDBP levels than men, yet no associations were observed between VDBP levels and age, body weight, BMI, fat mass, or fat percentage [ 144 ] While the aforementioned study measured VDBP levels among individuals greater than middleage, the majority of our samples derived from individuals much younger than middleage; however, we were able to confirm gender differences in the younger study cohort. Despite our having noted this interesting correlation, additional studies are required to address its biological significance. For example, it could be argued that that t he presence of reduced VDBP levels in the ty pe 1 diabetes study group may not have a biologically significant effect on the transport of vitamin D metabolites (i.e., reduced transport), since VDBP circulates at a much higher concentration than its ligands [ 146 ] Additionally, as mentioned previously, in a prior study, we found that 25OH vitamin D levels did not specifically associate with type 1 diabetes but were low in similar
41 proportion among those with and without the disease [ 125 ] In the current investigation, we did not find a significant correlation between those previously measured 25OH vitamin D levels and serum VDBP in the same patients. This we interpret to imply that lower VDBP levels in type 1 diabetes are independent of 25OH vitamin D, which is one of its ligands. While our study is novel in its simultaneous assessment of 25OH vitamin D VDBP, and genetic polymorphisms, we would note a very recently published study wher e type 1 diabetes patients were noted to have exaggerated urinary loss of VDBP [ 147 ] However, the study did not find a significant difference in plasma VDBP levels, which may in part, be due to the smaller cohort size. Though we did not measure urine levels of VDBP in our study, it is possible that exaggerated VDBP urinary loss may be a factor contributing to lower serum VDBP in type 1 diabetes patients. Overall, our findings warrant f urther investigation into the role of VDBP, as well as the contribution of other vitamin D pathway components, in type 1 diabetes The various contributions of this pathway to innate immune function are the topic of much discussion and may be multifaceted, with each individuals risk being the sum of different pathways to disease; hence, the reason for the historical difficulty in describing a specific mechanisms for involvement of vitamin D in the pathogenesis of type 1 diabetes
42 Table 21. Hardy Weinberg equilibrium of patients and controls from Georgia samples Gene SNP Allele (Major>Minor) HWE Cases HWE Controls VDBP rs4588 C>A 0.2897 0.6740 VDBP rs7041 G>T 0.8386 0.4072
43 Table 22. Assocation analysis of VDBP SNPs rs7041 (G>T) and rs4588 (C>A) with type 1 diabetes. SNP Genotype Type 1 Diabetic Patients Controls Odds Ratio (95% CI) P rs7041 GG 441 (30.33%) 579 (31.67%) 1.00 (reference) GT 723 (49.72%) 884 (48.36%) 1.07 (0.92 1.26) 0.3774 TT 290 (19.94%) 365 (19.97%) 1.04 (0.86 1.27) 0.6755 GT + TT 1013 (69.67%) 1249 (68.33%) 1.07 (0.92 1.24) 0.4086 rs4588 CC 723 (50.45%) 929 (51.58%) 1.00 (reference) CA 578 (40.33%) 734 (40.76%) 1.01 (0.87 1.17) 0.8745 AA 132 (9.21%) 138 (7.66%) 1.23 (0.95 1.59) 0.1163 CA + AA 710 (49.55%) 872 (48.42%) 1.05 (0.91 1.20) 0.5235
44 Table 23. Association analysis of VDBP SNPs rs7041 (G>T) and rs4588 (C>A) after stratification for sex, onset of type 1 diabetes, and HLA risk SNP Subset Genotype Type 1 Diabetic Patients Controls Odds Ratio (95% CI) P rs7041 Early Onset GG 285 (30.94%) 579 (31.67%) 1.00 (reference) GT 474 (51.47%) 884 (48.36%) 1.09 (0.91 1.31) 0.3527 TT 162 (17.59%) 365 (19.97%) 0.90 (0.71 1.14) 0.3842 GT + TT 636 (69.06%) 1249 (68.33%) 1.03 (0.87 1.23) 0.6974 Late Onset GG 152 (29.23%) 579 (31.67%) 1.00 (reference) GT 245 (47.12%) 884 (48.36%) 1.06 (0.84 1.33) 0.6409 TT 123 (23.65%) 365 (19.97%) 1.28 (0.98 1.68) 0.0710 GT + TT 368 (70.77%) 1249 (68.33%) 1.12 (0.91 1.39) 0.2884 Male GG 212 (30.55%) 302 (31.10%) 1.00 (reference) GT 343 (49.42%) 483 (49.74%) 1.01 (0.81 1.27) 0.9193 TT 139 (20.03%) 186 (19.16%) 1.07 (0.80 1.41) 0.6629 GT + TT 482 (69.45%) 669 (68.90%) 1.03 (0.83 1.27) 0.8092 Female GG 229 (30.13%) 277 (32.32%) 1.00 (reference) GT 380 (50.00%) 401 (46.79%) 1.15 (0.92 1.44) 0.2329 TT 151 (19.87%) 179 (20.89%) 1.02 (0.77 1.35) 0.8870 GT + TT 531 (69.87%) 580 (67.68%) 1.11 (0.90 1.37) 0.3431 High Risk HLA GG 244 (33.15%) 58 (29.44%) 1.00 (reference) GT 346 (47.01%) 99 (50.25%) 0.83 (0.58 1.20) 0.3166 TT 146 (19.84%) 40 (20.30%) 0.87 (0.55 1.36) 0.5379 GT + TT 492 (66.85%) 139 (70.56%) 0.84 (0.60 1.19) 0.3228 Low Risk HLA GG 195 (27.50%) 520 (31.90%) 1.00 (reference) GT 373 (52.61%) 785 (48.16%) 1.27 (1.03 1.56) 0.0239 TT 141 (19.89%) 325 (19.94%) 1.16 (0.89 1.50) 0.2665 GT + TT 514 (72.50%) 1110 (68.10%) 1.24 (1.02 1.50) 0.0338 rs4588 Early Onset CC 472 (52.10%) 929 (51.58%) 1.00 (reference) CA 350 (38.63%) 734 (40.76%) 0.94 (0.79 1.11) 0.4612
45 Table 2 3. Continued. SNP Subset Genotype Type 1 Diabetic Patients Controls Odds Ratio (95% CI) P AA 84 (9.27%) 138 (7.66%) 1.20 (0.89 1.61) 0.2263 CA + AA 434 (47.90%) 872 (48.42%) 0.98 (0.83 1.15) 0.8004 Late Onset CC 244 (47.38%) 929 (51.58%) 1.00 (reference) CA 225 (43.69%) 734 (40.76%) 1.17 (0.95 1.43) 0.1401 AA 46 (8.93%) 138 (7.66%) 1.27 (0.88 1.82) 0.1964 CA + AA 271 (52.62%) 872 (48.42%) 1.18 (0.97 1.44) 0.0924 Male CC 340 (49.78%) 487 (50.78%) 1.00 (reference) CA 281 (41.14%) 401 (41.81%) 1.00 (0.82 1.23) 0.9718 AA 62 (9.08%) 71 (7.40%) 1.25 (0.87 1.81) 0.2324 CA + AA 343 (50.22%) 472 (49.22%) 1.04 (0.86 1.27) 0.6891 Female CC 383 (51.07%) 442 (52.49%) 1.00 (reference) CA 297 (39.60%) 333 (39.55%) 1.03 (0.84 1.27) 0.7855 AA 70 (9.33%) 67 (7.96%) 1.21 (0.84 1.73) 0.3105 CA + AA 367 (48.93%) 400 (47.51%) 1.06 (0.87 1.29) 0.5694 High Risk HLA CC 381 (52.62%) 98 (50.26%) 1.00 (reference) CA 272 (37.57%) 80 (41.03%) 0.87 (0.62 1.22) 0.4310 AA 71 (9.81%) 17 (8.72%) 1.07 (0.61 1.91) 0.8067 CA + AA 343 (47.38%) 97 (49.74%) 0.91 (0.66 1.25) 0.5569 Low Risk HLA CC 337 (48.01%) 829 (51.68%) 1.00 (reference) CA 304 (43.30%) 654 (40.77%) 1.14 (0.95 1.38) 0.1573 AA 61 (8.69%) 121 (7.54%) 1.24 (0.89 1.73) 0.2044 CA + AA 365 (52.00%) 775 (48.32%) 1.16 (0.97 1.38) 0.1041
46 Table 24. H eterogeneity tests to determine whether the odds ratios for homozygous genotypes significantly differ between stratified groups SNP Subset Genotype Analyzed Odds Ratio (95% CI) Heterogeneity rs7041 Early Onset GG > TT 0.90 (0.71 1.14) Late Onset GG > TT 1.28 (0.98 1.68) 0.0529 Male GG > TT 1.07 (0.80 1.41) Female GG > TT 1.02 (0.77 1.35) 0.8338 High Risk HLA GG > TT 0.87 (0.55 1.36) Low Risk GG > TT 1.16 (0.89 1.50) 0.2778 rs4588 Early Onset CC > AA 1.20 (0.89 1.61) Late Onset CC > AA 1.27 (0.88 1.82) 0.8084 Male CC > AA 1.25 (0.87 1.81) Female CC > AA 1.21 (0.84 1.73) 0.8891 High Risk HLA CC > AA 1.07 (0.61 1.91) Low Risk CC > AA 1.24 (0.89 1.73) 0.6713 Odds ratio of patients with type 1 diabetes to controls. Heterogeneity determined by Breslow Day test.
47 Figure 21. Serum levels of vitamin D binding protei n VDBP levels in controls (n=153), first degree relatives (n=116), and type 1 diabetic patients (n=203). Serum VDBP in males (n=233) and females (n=238), total of all study groups. Median with IQR shown.
48 Figure 22. Serum levels of vitamin D binding protein. Serum VDBP in males (n=233) and females (n=238), total of all study groups Median with IQR shown.
49 Figure 23. No association between V DBP levels and disease duration by linear regression analysis.
50 Figure 24. Linear regression of serum 25OH vitamin D levels and vitamin D binding protein levels. There was no significant correlation between these two parameters in the study cohort (n=386).
51 Figure 25. No statistically significant association between VDBP levels and genotype at rs7041 and rs4588.
52 CHAPTER 3 A SNP IN THE PROMOTER REGION OF THE INTE RLEUKIN 2 GENE IS ASSOCIATED WITH MODULATION OF HUMAN SERUM SCD25 LEVELS Introduction IL 2 is a key immunoregulatory cytokine. Originally thought to be important to T cell proliferation, it has since been found to be largely dispensable for that role, but indispensable in its role in maintaining populations of the anti inflammatory regulatory T cell. Regulatory T cell defects are powerfully implicated in the pathogenesis and progression of type 1 diabetes and so the IL2 pathway represents a key piece of the etiological puzzle of autoimmune diabetes. SNPs in promoter regions can affect gene sp licing, binding of transcription factors, abundance of messenger RNA, or the structure of noncoding RNAs [ 148 152 ] These polymorphisms can also have an impact in trans through effects on downstream genes [ 153 ] GWAS and linkage studies have long demonstrated the utility of SNPs are biomarkers of disease risk, possibl e targets for therapeutic intervention, and targets for the investigation of pathogenesis. Rs2069762 is a T>G SNP located 330 base pairs upstream of IL 2, in the promoter region [ 154 ] This SNP is located within a region shown to be important for the inducible expression of IL2, for when deletion of t he region from 289 to 361 bp upstream of IL2 occurs, IL2 expression is observed to be considerably inhibited [ 155 ] Rs2069762 has already been shown to modulate levels o f IL 2 in treated peripheral blood lymphocytes with a study in Maryland associating the G all ele with higher levels of IL 2 in CD3/CD28 72 hour bead stimulated invitro assays [ 152] Interestingly, this locu s is far less polymorphic in African American populations with a T/G distribution of 94%/6% (n=81) in African Americans and 74%/26% in Caucasians (n=150) [ 156 ]
53 It is important to note that association with disease does not necessarily mean that there are functional implications due to the associated SNP. rs2069762 is in linkage disequilibrium with 55 other SNPS in the region, and is likely in linkage disequilibrium with many other types of polymorphisms that could have functional relevance to disease. Disentangling the connection between these SNPs and disease will be a challenging process, for but now, rs2069762 could serve as a biomarker through its association with particular, disease relevant phenotypes. We were primarily interested in the effect of the rs2069762 polymorphism in the promoter of IL 2 on levels of IL2 in stimulated peripheral blood mononuclear cell populations, and of the effect of polymorphisms in the IL2 promoter on levels of downstream, immunologically relevant factor s such as soluble CD25 (sCD25). CD25, also known as IL2r is the high affinity subunit of the IL2 receptor encoded by a gene located on chromosome 10 in humans It is transiently expressed on many cell types, includi ng T effector cells, B cells, dendritic cells, natural killer cells, and eosinophils but is only constituitively express on regulatory T cells [ 6366 ] IL2r mutation or knockout can lead to severe autoimmunity, suggesting an important role for the high affinity IL2 receptor component in immune regulation [ 67 68] Interestingly, CD25 does not exist exclusively as a membrane bound receptor component. Instead, it can be cleaved ( releasing the extracellular domain and reducing the protein in size from 55 KDa to 45 Kda) and can take a soluble form (sCD25) that may have important immune effects [ 157 ] This shedding is associated with activation and proliferation [ 157159] and appears to occur in all cells that express CD25 [ 158 160, 161 ] In vitro studies suggest that the primary source of sCD25 is activated
54 effector T cells, as these cells are far more likely than regulator y T cells to shed sCD25 into the culture medium after activation [ 159 ] Hypotheses for the role of sCD25 are many and varied. It has been proposed that the cleaved sCD25 is simply a byproduct of a cleavage process regulating the amount of membrane bound CD25. However, it is known that sCD25 can bind the IL2 ligand, albeit with affinity orders of magnitude lower than the complete receptor [ 161 162 ] Given this, functions could include presentation of IL2 to the IL 2 receptor in trans, the soaking up of free IL 2 to deprive effector T cells or regulator T cells of the cytokine or the preservation of IL2 bioavailability through keeping it free fro m forming complexes macroglobulin [ 162 163 ] S erum sCD25 levels range between 1 and 2 ng/mL in healthy individuals [ 164 ] High sCD25 expression appears to be associated with a number of pathologies, including infection, leukemia and lymphomas, rheumatoid arthritis, type 1 diabetes celiac disease, multiple sclerosis, Graves disease, and S jogrens syndrome. In many cases, sCD25 levels correlated positively with disease activity [ 161, 165169 ] In the case of celiac, sCD25 level elevation reliably accompanied gluten challenge and remitted in the absence of gluten, making sCD25 a noteworthy potential marker of immune activation [ 169 ] Studies of the effects of sCD25 on the immune process reveal complex results and its role remains a source of controversy. In spite of demonstrating higher levels of in vivo sCD25 secretion as compared to controls, PHA stimulated PBMCs from patients with type 1 diabe tes were observed to produce lower levels of sCD25 than those of healthy controls in vitro [ 161 166 170 ] sCD25 has been found in some studies to
55 inhibit IL 2 driven STAT5 signaling in a fashion similar to anti IL 2 mAb, while at the same time promoting T cell activation and expansion [ 171 ] Other studies have found Stat5 signaling (and Foxp3 expression) to be enhanced by sCD25 in the presence of IL2 [ 172 ] sCD25 appears to enhance the suppressive effects of regulatory T cell s in a dose dependent fashion at high doses possibly by decreasing CD25 receptor expression, but may have no effect when administered alone or at physiologic doses [ 158 159 173 ] At lower doses that do n ot affect regulatory T cell suppression, sCD25 alone may still be able to decrease proliferation in effector T cells though these findings conflict with earlier, contrary reports [ 159 171 ] Results of in vitro studies using sCD25 have been found to be highly context dependent, with m easures of proliferation, sCD25 expression, and IL2 signaling activity changing depending upon the timing of measurement, what culture medium is used, whether Il 2 is present, and whether the medium is serum free or contains serum [ 159, 172 ] Extensive biological variation in sCD25 levels is undoubtedly also present, as sCD25 levels have been observed to vary according to circadian rhythms and could also vary according to other factors such as blood glucose levels [ 174 ] Brusko et al recently hypothesized that the role of sCD25 may be to interrupt the negative feedback loops by which the IL2 pathway downregulates inflammatory activity (through promotion of regulatory T cell activity and sensitization of effector T cells to AICD) [ 159 ] How sCD25 carries out this role may be dependent upon the immunochemical milieu in which sCD25 is being expressed. Further study is needed to fully understand the role of sCD25 in immune response [ 159 ]
56 Given that IL 2 itself is a key regulator of immune response, and given that IL2 expression has been shown to influence sCD25 expression, v ariation in the IL2 promoter region could play a crucial role in multiple facets of the immune dysfunction that leads to autoimmune diabetes [ 175 ] Therefore, we hypothesized that levels of IL 2 and soluble CD25 would be different between individuals based upon their genoty pe at the rs2069762 locus. Methods Participants Human subjects consisted of those with type 1 diabetes relatives of those with type 1 diabetes and healthy controls. Peripheral blood was obtained via venipuncture after informed consent and in accordanc e with approv ed protocols. Fresh PBM C, DNA and serum were obtain ed from peripheral blood. DNA and peripheral blood were stored at 20 degrees. SNP Genotyping DNA for SNP typin g was extracted using the QiaAmp Blood Mini commercial kit (Qiagen; Venlo, Net herlands) according to manufacturer specification and using the Qiacube instrument. SNP genotype for all subjects were determined using a commerical (Life Technologies; Carlsbad CA) Taqman SNP typing kits on a Roche (Penzberg, Germany) Lightcycler 480 ins trument, according to manufacturer directions. Cell Culture Experiments Freshly isolated human PBMC were plated at 106/mL, 100 microliters per well, in 96 well round bottomed plates. Cells were cultured with 5 ug/mL CD3 and 2.5 ug/mL CD28 or 2.5 ug/mL CD3 and 1.25 ug/mL CD28 or a mitogenic stimulus, PHA at 1 ug/mL
57 for a period of 24 or 48 hours. Supernatants were then separated by centrifugation and frozen at 20 until analysis by ELISA. The culture medium was RPMI 1640 ( Corning Cellgro Manassas, VA) wit h 10% FBS (Hyclone), 50 g/mL penicillin/streptomycin, 2 mM l gutamine, 1% sodium pyruvate, 5 mM HEPES, and 50 g/mL betamercaptoethanol. Incubation of cells took place in a humidified incubator, 37 C, 5% CO2. IL 2 Protein Detection by ELISA IL 2 protein was detected using the eBioscience Ready Set Go IL2 ELISA according to manufacturer specifications in 96 well flat bottomed plates. Based on preliminary experiments, standards from 2 ng/mL through 31 g /mL gave a linear range, and we used this standard curve to measure IL2 in our test samples. Dilutions took place in R PMI 1640, formulated as specified in Cell Culture Experiments, above. Samples were analyzed in duplicate. sCD25 Protein Detection by ELISA sCD25 was measured using the BD OptEIA kit (BD Pharmingen) according to the manufacturers specifications. Any necessary dilutions were performed in PBS with 10% FBS. Measurements were conducted in duplicate. Statistical Methods Data analyses were performed in GraphPad Prism (San Diego, CA). Oneway ANOVA with Dunnets correction for multiple testing were performed for all analyses with the exception of the genotype frequency by disease state analysis, which was performed via a Chi squared test and age and disease duration correlations, which we re calculated using the Spearmans R method.
58 Results r s20697 62 Genotype Frequenc i es by Disease State No significant association was observed between genotype at rs2069762 and disease state (between type 1 diabetes, relatives, and controls) ( 2 = 2.2, df=4) (Table 3 1) Allele frequencies were 0.337 G and 0.663 T (Table 32). IL 2 Levels in Cell Culture and rs2069762 In order to investigate the potential effect of the IL2 promoter SNP rs2069762 on IL 2 levels, human PBMCs from a mixed populati on of type 1 diabetes patients, relatives, and controls were cultured under differential stimulation conditions for either 24 or 48 hours (Figure 3 1) For samples cultured under anti CD3/antiCD28 at 2.5 ug/mL and 1.25 ug/mL for 24 hours (4 GG patients, 22 GT patients, 18 TT patients) (Figure 3 1A) GG patients trended toward much lower expression levels of IL2 (median 23.67 pg/mL) than either TT patients (median 69.62 pg/mL) or GT patients (median 111.5 pg/mL) (p=ns). For samples cultured under anti CD3/ anti CD28 at 2.5 ug/mL and 1.25 ug/mL for 48 hours ( 1 GG patients, 1 7 GT patients, 1 5 TT patients) (Figure 3 1 B ) a similar trend was observed, with the GG patient again trending toward extremely low levels of IL2 expression (36.59 pg/mL) as compared to T T patients (45.22 pg/mL) or GT patients (82.37 pg/mL) (p=ns). Under anti CD3/anti CD28 at 2.5 ug/mL and 1.25 ug/mL at either 24 or 48 hours, extremely high outliers were observed. Culturing under anti CD3/anti CD28 at 5 ug/mL and 2.5 ug/mL for 24 hours (Fi gu re 3 1C ) (4 GG patients, 12 GT patients, 10 TT patients), a similar pattern of expression was observed to that at the lower anti CD3/antiCD28 stimulation, with the GG group
59 (median 22.82 pg/mL) falling substantially below either the GT (69.71 pg/mL) or T T (73.27 pg/mL) groups. Medians were comparable to those at the lower stimulation, but the upper limit of expression was substantially lower at the higher stimulation. In the case of anti CD3/anti CD28 culture at 5 ug/mL and 2.5 ug/mL for 48 hours (3 GG p atients, 9 GT patients, 7 TT patients) (Figure 31 D ) the pattern continued, with the GG group (median below limit of detection, mean 12.43 pg/mL) again falling below either the GT (median below limit of detection, mean 40.38 pg/mL) or TT (median 50.82 pg/mL, mean 111.1 pg/mL) groups. We again observed decreased maximum levels of expression as compared to the lower stimulation condition. We additionally cultured PBMCs in PHA at 1 ug/mL to examine the effect on IL2 production when stimulation was not pr ocessed through the T cell receptor (Figure 3 1F) At 24 hours (4 GG, 12 GT, 10TT) (Figure 31E ) and 48 hours (4 GG, 9 GT, 10 TT), IL 2 expression was modest and there were not noticeably different trends between genotypes. sCD25 Levels in Human Serum and rs2069762 We next investigated whether genotype at rs2069762 correlated with levels of sCD25 in 181 (16 GG, 83 GT, 82 TT) human subject serum samples (Figure 3 2) We found that the presence of a G allele at rs2069762 seemed to correlate with higher leve ls of sCD25 (GG median = 2213 pg/mL, GT median 2098 pg/mL, TT median 1752 pg/mL). The GT/TT difference was statistically significant with a pvalue of 0.0082. Normal range for sCD25 levels are between 1 and 2 g/mL. sCD25 Levels by Disease State We sough t to determine whether levels of serum sCD25 in our population correlated with disease state, as has been observed in other studies (Figure 3 3) In
60 133 subjects (31 controls, 53 relatives, 97 patients with type 1 diabetes ), we found statistically significant differences (p<0.0001) between controls (median = 1384 pg/mL) and relatives (median = 2009 pg/mL) as well as between controls and patients with type 1 diabetes (median = 2077 pg/mL) with disease and relative status associating with higher levels of s CD25. We additionally investigated whether a correlation existed between levels of sCD25 and number of autoantibodies (Figure 3 4). W e found no significant difference in sCD25 levels between those with no autoantibodies, one autoantibody, and two autoantibodies. GAD and IA 2 were considered for this analysis. Associations with Age and Type 1 Diabetes Duration There was a statistically significant association between age and disease state in type 1 diabetes in our sample population, with patients being significantly younger than either first degree relatives or controls, likely due to sampling bias (p<0.0001) (Figure 3 5 ). We observed a statistically significant correlation between age and sCD25 levels (Spearman r= 0.31, p<0.0001) (Figure 3 6 ). N o significant association was observed for either sCD25 by type 1 diabe tes duration (Figure 37 ) or rs2069762 genotype by age ( Figure 38 ). Discussio n Here we sought to determine an association between rs2069762 and disease as well as between rs2069762 and disease related phenotypes (IL2 expression and expression of the secreted IL2 receptor component soluble CD25) Previous, unpublished data from other groups suggest that the G allele is protective with an odds ratio of 0.89. rs2069762 G has also been observed to afford resistance to new onset diabetes after transplantation (NODAT) in renal transplantation [ 176 ] We observed no association was observed between genotype at rs2069762 and disease state. It is
61 probable that our sample size of 297 individuals was inadequate to detect a difference, owing to the modest effect size of the SNP. The allele frequencies observed in our population for the rs2069762 were not out of line with prior expectations [ 152 ] While we obtained no statistically significant results in our correlations between stimulated IL2 samples and genotype at rs2069762, marked trends were observed suggested than under anti CD3/antiCD28 stimulation, presence of the G allele seems to drive a trend toward lower levels of IL2 expression. These findings directly conflict with a previous study by Hoffman et. al that associated the G allele with higher IL2 expression levels [ 152 ] It is possible that the level of mode of stimulation is different, as these prior studies used a 3:1 bead stimulus rather than our solu ble stimulus; it is known that the effect of IL2 on immune cell populations can differ depending on the level and context of exposure [ 63 ] The observed effect may also be due to the fact that the Hoffman study used peripheral blood lymphocytes instead of peripheral blood mononuclear cells; the exclusion of monocytes and macrophages may have had an impact on the outcome. Interestingly, higher levels of stimulation through CD3 and CD28 seemed to inhibit the max imum expression of IL2, with maxima in the lower stimulation conditions being considerably higher than in the high stimulation conditions. High levels of stimulation may be driving cells into anergy or may be pushing an earlier peak of IL2 expression, such that the 24 and 48 hour time points now catch declining expression levels. It is important to note, however, that while the range was altered, the medians were similar between the two stimulation levels, so the effect may only apply to outlying samples.
62 We additionally used a T cell receptor independent stimulus, PHA. The trend toward suppression of IL2 expression observed in the G genotype seemed to be dependent upon signaling through the T cell receptor. Circumvention of the T cell receptor throug h use of PHA produced levels of IL2 expression that were modest and uniform across groups in comparison to what was observed with anti CD3 and anti CD28 stimulation. For our investigation of rs2069762 and its association with serum levels of soluble CD25, we found that presence of the G allele seemed to be associated with higher levels of expression. This result seems counterintuitive if the G allele is protective, as the unpublished OR of 0.89 would suggest; high sCD25 expression is generally associated with inflammation and disease (even in these same samples (Figure 33) ) and the current best model for the role of sCD25 would suggest that it functions in disrupting the negative feedback loops by which IL2 expression reins itself in [ 159 ] Our observation of a correlation between sCD25 a nd disease state led us to question the role of age in our results. While onset of type 1 diabetes may occur at any age, the primary peaks of onset are between 5 and 7 years of age and during puberty. Because parents of children within these age groups are more likely to bring their children in to participate in studies, sampling bias effects cause type 1 diabetes to be associated with young age in our sample set with a pvalue <0.0001 ( Figure 35 ). We investigated the correlation between soluble CD25 and age, and observed that a correlation exists (Figure 36 ). However, we observed no correlation between sCD25 and disease duration (Figure 37 ). These results, and the lack of a correlation with
6 3 autoantibody presence (Figure 3 4), raise the possibility that our correlation of sCD25 with disease state is confounded by an association between sCD25 and age. Additionally, there remains the possibility of confounding by other unmeasured metabolic factors such as blood glucose and circadian rhythm. However, w e lack sufficient sample sizes to determine with certainty what role such potential confounding relationships play in our analysis; further study will be needed to verify that observed correlations between sCD25 and disease state are not confounded by association s between sCD25 and age or other factors A lack of correlation between age and genotype at rs2069762 suggests that we did not recruit an unusual number of patients of any genotype in any age group (F igure 3 8 ) and that our association between gen otype at rs2069762 and levels of serum sCD25 is not confounded by age. Our results would suggest that the relationship between sCD25, rs2069762, and disease state in type 1 diabetes is complex, that this complexity cannot be reduced to methodological probl ems related to culture conditions (as our investigation was done in serum), and more work needs to be done in elucidating the role of the soluble IL2 receptor alpha subunit before definitive conclusions can be made as to its role in the etiology or progression of type 1 diabetes It should also be noted that groups were within the normal physiologic range for sCD25 expression, so the biological relevance of this finding is unclear. Rs2069762 may be associated with factors that play an important role in the etiology or progression of autoimmune diabetes Further studies are nee ded to ascertain its utility as a meaningful biomarker. For IL 2, more in depth comparison s and
64 titrations of bead stimulations and soluble stimulations in larger sample groups might help to clarify discrepancies between our study and previous work. Once the relationship between re2069762 and IL2 expression levels is definitively worked out, it may lend some insight into the interaction between rs2069762 and sCD25 levels. For soluble CD25, it would be most beneficial to definitively establish a connection between genotype at rs2069762 and disease state. Once this has been worked out, we can determine whether our result; that the G allele is associated with higher levels of sCD25, is truly counter intuitive and if so, begin to determine why this is the case. Further functional studies using sCD25 may lend insight. At low levels, it has been observed that sCD25 does not augment regulatory T cell mediated suppression of T effector proliferation but does affect proliferation directly, but at high levels, i t appears to impact suppression [ 158 159 173 ] sCD25 has been associated with both upregulation and downregulation of T cell signaling factor STAT5 [ 171 172 ] Its effects are highly context dependent; presence or absence of IL2, choice of culture medium, and presence or absence of various cell subsets have all been shown or speculated to play a role in the downstream effects of sCD25 [ 159 ] These results add additional layer to the complex story of the IL2/IL2R pathway in type 1 diabetes
65 Table 31. rs2069762 Genotype by Disease State (Counts) T1D Relativ e Controls GG 10 9 12 31 GT 55 45 38 138 TT 49 44 35 128 Totals 114 98 85 297
66 Table 32. rs2069762 Allele Frequencies Count Freq G 200 0.3367 T 394 0.6633
67 Figure 31 IL 2 production measured by ELISA in stimulated PBMCs by rs2069762 genotype. (A) IL 2 levels at 24 hours with 2 anti CD28 stimulation. (B) ILCD28 (C) IL CD28. (D) IL anti CD28. (E) IL PHA (F) IL
68 Figure 32 sCD25 levels by rs2069762 genotype. (p=0.0082)
69 Figure 33 Soluble CD25 levels by disease state in type 1 diabetes (p<0.0001)
70 Figure 34 sCD25 by autoantibody positivity (GAD and IA 2) (p=ns).
71 Figure 35 Disease state by age in type 1 diabetes (p<0.0001).
72 Figure 3 6 Soluble CD25 levels by age in type 1 diabetes. (p<0.0001)
73 Figure 37 Soluble CD25 levels by disease duration in type 1 diabetes. (p<0.001 )
74 Figure 38 Genotype by age in type 1 diabetes ( p= ns)
75 CHAPTER 4 IMPLICATIONS AND FUTURE DIRECTIONS We sought t o identify biomarkers that would inform our understanding of the etiology or aid with treatment of type 1 diabetes To this end, we investigated two pathways known to be relevant to autoimmune type 1 diabetes: the Vitamin D pathway and the IL2/IL2R pathway. In each case, our findings were informative and form a strong basis for future investigations. In the case of the Vitamin D pathway, we found that VDBP SNPs rs4588 and rs7041 did not have any correlation with disease. We did, however, find an association between lower VDBP levels and type 1 diabetes This, in spite of the fact that, in our patient population, Vitamin D levels were low in all studied groups and consequently, no dis tinctions in Vitamin D levels were observed between the groups. VDBP exists in levels far in excess of those necessary to bind Vitamin D ; 98 99% of VDBP binding sites remain unbound [ 142 ] This and the diverse immunologic al activity of VDBP suggest that it may play an important role in the immunobiology of type 1 diabetes independent of its connection to Vitamin D. It is also possible that interaction between Vitamin D and VDBP independent of SNPs rs4588 and rs7041 may be important to type 1 diabetes It is unclear whether the lower VDBP levels observed in those with type 1 diabetes are a cause of autoimmunity, an effect of immune disregulation, or simply share common causative factors with disease. We have identified a potentially important role for VDBP as a marker in autoimmune diabetes; f urther investigation of the more than 120 known polymorphisms at the VDBP locus and their relationship to disease state may help to elucidate the importance of this pathway to the eti ology of type 1 diabetes
76 The IL 2/IL 2 receptor pathway is heavily implicated in the etiology of type 1 diabetes with polymorphisms in both IL2 and the IL2 receptor being association with susceptibility. We sought to characterize the association between rs2069762, a T>G SNP 330 bp upstream of IL 2 in the promoter region, and disease relevant phenotypes. Our failure to find an association between rs2069762 and disease state stands in contrast to previous finding suggesting an OR of 0.89 for the G allel e. It is possible that our sample size was too small to detect a difference. Our data trended toward lower IL2 expression in the presence of the G allele. While not statistically significant, these data are contrary to previous findings suggesting higher IL 2 expression in the presence of the G allele; the differences may be a result of the cell subsets used in the experiments (the previous work excluded monocytes and macrophages) or the culture conditions (the previous work used beads rather than solubl e stimulus) [ 152 ] More study will be needed to definitively resolve this conflict. We observed an association between rs2069762 and serum levels of sCD25, with the presence of the G allele being associated with higher levels of sCD25. This would seem to contrast with previous data on rs2069762; the G allele is generally associated with protection, while high sCD25 expression is generally associated with inflammati on and disease. Because the impact of sCD25 expression is so hig hly context dependent, varying based on cell subsets present, levels of sCD25 present, and possibly levels of IL 2 expression, it is likely that we are observing the end result of a highly complex set of interactions. sCD25 can promote regulatory T cell m ediated suppression or have no impact at all, can promote or inhibit Stat5 expression, and can inhibit T effector proliferation when expressed alone. Perhaps high levels of sCD25 observed in
77 inflammation and disease represent a failed attempt at counter r egulation that, for whatever reason, is more effective in those with the G allele at rs2069762. While SNPs have been known to have functional effects on their associated proteins, and rs2069762 is in the promoter region, it lies upstream of the majority of the transcription factor binding sites. It is unclear what, if any, functional impact this SNP may have, and any hypotheses about functional impact outside of mere association would be speculation at this point. Future investigations with larger samples sizes could confirm the observed trend in IL2 expression related to rs2069762. With regard to sCD25, a key component will be determining, in a larger sample population, what, if any association rs2069762 has with disease state; from there, we may have m ore basis for understanding the possible relevance of the association between levels of sCD25, the rs2069762 SNP, and disease state in type 1 diabetes These biomarkers provide novel insight into two pathways implicated in autoimmune diabetes. The mechani sm of the association between VDBP and disease and rs2069762 polymorphism and sCD25 levels require further study. More detailed understanding of the Vitamin D and IL2 pathways may be inf ormative for our understanding of disease etiology and progression i n type 1 diabetes
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93 BIOGRAPHICAL SKETCH Dustin Blanton was born to Cecil C. and Garnette Blanton in Ft. Worth, Texas. He grew up in Branford Florida from the age of two through the age of eighteen, graduating from Branford High School. In June of 2005, he married his wife, Lori. He graduated with a Bachelor of Science in Interdisciplinary Studies: Biology in 2006, completing a senior honors thesis under the supervision of Dr. Charles F. Baer. He subsequently taught high school for two years at Bradford High School in Starke, Florida. Upon completion of his second year teaching high school and following a suggestion from Dr. Baer, he applied to the Genetics and Genomics Graduate program at the University of Florida and was enrolled in August of 2008. He began work under the mentorship of Drs. Mark Atkinson and Desmond Schatz in early 2009. He has mentore d six undergraduate and postgraduate students during his time in the laboratory. Upon completion of this work, he hopes to pursue a career in post secondary education.