Endocrine autoimmune disease: genetics become complex

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1 DOI: /j x REVIEW Endocrine autoimmune disease: genetics become complex Janneke Wiebolt *, Bobby P. C. Koeleman and Timon W. van Haeften * Department of Endocrinology, Department of Medical Genetics, Department of Endocrinology, University Medical Centre Utrecht, Utrecht, the Netherlands ABSTRACT The endocrine system is a frequent target in pathogenic autoimmune responses. Type 1 diabetes and autoimmune thyroid disease are the prevailing examples. When several diseases cluster together in one individual, the phenomenon is called autoimmune polyglandular syndrome. Progress has been made in understanding the genetic factors involved in endocrine autoimmune diseases. Studies on monogenic autoimmune diseases such as autoimmune polyglandular syndrome type 1, immunodysregulation, polyendocrinopathy, enteropathy, X-linked and primary immune deficiencies helped uncover the role of key regulators in the preservation of immune tolerance. Alleles of the major histocompatibility complex have been known to contribute to the susceptibility to most forms of autoimmunity for more than 3 decades. Furthermore, sequencing studies revealed three non-major histocompatibility complex loci and some disease specific loci, which control T lymphocyte activation or signalling. Recent genome-wide association studies (GWAS) have enabled acceleration in the identification of novel (non-hla) loci and hence other relevant immune response pathways. Interestingly, several loci are shared between autoimmune diseases, and surprisingly some work in opposite direction. This means that the same allele which predisposes to a certain autoimmune disease can be protective in another. Well powered GWAS in type 1 diabetes has led to the uncovering of a significant number of risk variants with modest effect. These studies showed that the innate immune system may also play a role in addition to the adaptive immune system. It is anticipated that next generation sequencing techniques will uncover other (rare) variants. For other autoimmune disease (such as autoimmune thyroid disease) GWAS are clearly needed. Keywords Autoimmune thyroid disease, complex genetics, genome-wide association studies, polyglandular syndrome, single nucleotide polymorphism, type 1 diabetes. Eur J Clin Invest 2010; 40 (12): Endocrine autoimmune disease Autoimmune diseases are chronic inflammatory diseases that results from the combination of a genetic susceptibility and environmental factors. Collectively they result in immune dysregulation through unknown mechanisms. Proper development and activation of the immune system requires a network of signalling events that translate information from the outside environment to intracellular targets to elicit an appropriate response. Imbalances in these signalling networks can lead to the expansion and activation of autoreactive lymphocytes directed to self-antigens, overproduction of cytokines and secretion of autoantibodies leading to the destruction of normal tissue. Autoimmune diseases may affect a particular organ or tissue or have a systemic manifestation (see Table 1). This review focuses on endocrine autoimmunity and its genetic background, in particular on type 1 diabetes (T1D) and autoimmune thyroid disease (AITD). Endocrine autoimmune disorders share many features. Evidence for a role of genetic factors in autoimmunity originates from the observation that family members of a patient with an autoimmune disease have an increased risk for this particular disease. Moreover, twin studies suggest genetic influences on the aetiology of autoimmune disease. Monozygotic (identical) twin pairs have high concordance rates. For example, the simultaneous occurrence of T1D is increased in monozygotic twins and ranges from 13 to 67Æ7%, compared to 0 12Æ4% in dizygotic twins and 0Æ5% in the general population [1]. These rates already point to a complex genetic basis. By contrast, some rare cases of major endocrine autoimmune disease can be caused by a single mutation in one gene, for example in Autoimmune Polyglandular Syndrome type 1 (APS-1) European Journal of Clinical Investigation Vol 40

2 GENETICS IN EOCRINE AUTOIMMUNE DISEASE Table 1 Tissue specific and multi tissue autoimmune diseases Tissue specific Diabetes mellitus type 1 Autoimmune hypothyroidism (Hashimoto) Multi tissue Systemic lupus erythematodus Dermatomyositis gene loci [among which the variable number of tandem repeats (VNTR) of the insulin gene (INS) and the thyroid-stimulating hormone (TSH)-Receptor gene]. Finally, although there still is a paucity of GWAS in AITD, recent GWAS findings (mainly in T1D) will be discussed, together with future perspectives. Addison s disease Celiac disease Crohn s disease Multiple sclerosis Goodpasture syndrome Rheumatoid arthritis Scleroderma Sjogren s syndrome Genetic studies Two common approaches for distinguishing genetic factors are the candidate gene approach and the model free mapping approach. Myasthenia gravis Vitiligo Hypophysitis Graves disease Ankylosing spondylitis The common autoimmune diseases have a complex genetic basis, which means that several genes and environmental factors are involved in the pathogenesis of the disease. Research of genetics in autoimmune disease began several decades ago with the study of the major histocompatibility complex (MHC). The human leucocyte antigen (HLA) class II loci on chromosome 6p21 contribute to T1D, Graves disease (GD), and Addison s disease (AD) [2]. Presently, we know that the HLA-genes account for over 40% of the genetic risk for diabetes type 1, however, it is neither sufficient nor necessary for the development of disease illustrated by the importance of other (genetic) factors. Therefore, the current focus lies on the identification of non- HLA risk loci. Following the emergence of genome wide association studies (GWAS) in 2006, an increase was seen in the rate of discovery of risk loci for many autoimmune diseases [3]. It became clear that many genetic loci unlinked to the MHC region, also influence T1D disease risk [3]. It is believed that these loci account for another 8% of disease risk in T1D. This review deals with the pathophysiology of autoimmunity in endocrine disease and with its genetic background. We will first give a short discussion of the technique of candidate gene studies versus genome wide association studies (GWAS), before describing monogenetic endocrine autoimmunity syndromes, which underscore the importance of genetically determined disturbances of the immune system. As polygenetic autoimmune disease is far more common, we will shortly turn to HLA loci and other gene loci (CTLA-4 and PTPN22 genes) influencing the immune system that were found before the advent of the genome wide association studies (GWAS). Next we will return to candidate studies that propose tissue specific Candidate gene studies Several candidate gene studies have been performed to identify genes involved in T1D. These studies test some of the genetic variants in a gene that is a strong candidate for being involved in the disease, for example the INS. A drawback of this technique is first of all the assumption that the candidate gene plays a role in the aetiology of the disease. Secondly, false positive associations can occur as a result of population stratification. This is because population subdivision permits marker allele frequencies to vary among segments of the population, as the results of genetic drift or founder effects. Generally spoken candidate gene studies are used when the effect size of the variant is expected to be large. Affected sib pair analysis The affected sib pair analysis is a model free linkage mapping approach, which requires no knowledge of the disease gene, mode of inheritance of the disease or the penetrance. This approach requires pairs of affected sibs, for example, two sisters having diabetes type 1. The basis of the analysis is that subjects concordant for a given genetic trait should show greater than expected concordance for marker alleles that are closely linked to the disease. If, there is an excess of alleles which the sibs share identical by descent at a certain locus, this is taken as evidence for linkage between the tested marker and the disease susceptibility locus. As affected sibling pairs are relatively rare in T1D, it seems plausible that the existing data from linkage studies have been collected from a rather unique subgroup of families with T1D. In general, linkage studies are the method of choice if the risk factors being sought have a large effect size but are relatively rare. GWAS As risk factors become more common and have smaller effect sizes, GWA studies emerge as a more powerful approach, which also does not require assumptions about the underlying model of disease risk. The human genome harbours around three billion base-pairs, which contain at least three million European Journal of Clinical Investigation Vol

3 J. WIEBOLT ET AL. common single nucleotide polymorphism (SNPs) according to the International HapMap Project. The HapMap project has demonstrated that approximately 80% of the human genome is made of linkage disequilibrium (LD) blocks that consist of strings of adjacent SNPs that show significant LD (i.e. non-random association of alleles) between each other [4]. The significance of the HapMap is that it now allows us to identify complex disease genes by indirect association using tag SNPs (representative SNPs tagging LD-blocks). If a tag SNP shows association with disease, it indicates that the gene variant predisposing to the disease is most likely located within the same block as the tag SNP. Thus, in GWAS a reasonable number of tag SNPs (more than per subject) can be used to screen the entire genome, alleviating the need to exhaustively type all genetic variation in the genome. It is important to realize that GWA studies also have limitations. GWA studies generally identify only common genetic variants. Hence the disease susceptibility alleles that have been identified so far are common in the general population, and show low penetrance and modest effect (OR of around 1Æ5 and lower) resulting in low predictive values (the so called common disease-common variant hypothesis). However, the architecture of complex diseases is expected to involve not only common variants with low penetrance, but also low-frequency variants (rare variants) with high penetrance, as well as structural variants such as insertion-deletion polymorphisms, VNTRs and variation in copy numbers. These can be missed by GWAS studies. Furthermore, some SNPs are not well characterized and therefore follow up is limited. Another limitation is that nearly all studies are performed in Caucasian populations and therefore represent a minority of the human population. Despite these drawbacks GWA studies have shown us new genes in general immune pathways of T cell differentiation, T cell signalling and the innate immune response. The challenge ahead is whether fine mapping and deep sequencing will confirm the new genes to be involved in disease pathogenesis. Specific (mono-) genetic autoimmunity syndromes Autoimmune polyglandular syndrome type 1 The monogenic APS-1 is of great interest as this disease represents a general loss of regulation of self-tolerance. APS-1 is an example of a specific rare monogenic syndrome generally seen at young age consisting of mucocutaneous candidiasis, AD and or hypoparathyroidism. Other autoimmune diseases associated with APS-1 include T1D, vitiligo, alopecia, autoimmune hepatitis, pernicious anaemia, primary hypothyroidism and hypergonadotropic hypogonadism [5]. The underlying genetic abnormalities in the APS-1 syndrome are mutations in the autoimmune regulator gene (AIRE gene) [6,7]. AIRE functions as a transcription factor in a specialized subset of cells in the thymus called medullary epithelial cells, and helps to promote the transcription of many self-antigen genes. Self-antigen expression within the thymus promotes the negative selection and deletion of autoreactive thymocytes that naturally develop in the thymus. In the absence of AIRE autoreactive T cells, mature and escape deletion in the thymus and migrate into the periphery, where they are capable of destroying multiple specific tissues. Human studies of isolated autoimmune disorders, such as AD or autoimmune hypothyroidism, occurring without evidence of other autoimmune disease did not detect mutations in the AIRE gene [8]. IPEX Another rare monogenic syndrome, the rare IPEX syndrome, led to the unravelling of the importance of the transcription factor Foxp3 (FOXP3, chromosome Xp11Æ23) [9]. Foxp3 is a member of the forkhead box (FOXP) family of transcription factors and is fundamental to the subset of regulatory T cells (Treg cells). These cells develop within the thymus and are thought to dampen the effects of activated T cells. Surface markers on these Treg cells include CD25, Cytotoxic T-Lymphocyte Associated antigen 4 (CTLA-4) and others. When these Treg cells lose their suppressive action because of a mutation in the FOXP3 gene, activated T cells and cytokine production are increased leading to autoimmunity. In T1D an initial association between FOXP3 and T1D (n = 363) could not be reproduced in an additional independent set of 826 T1D patients and 1459 controls [10]. In a study of AITD patients, the FOXP3 gene locus was analysed using four microsatellite polymorphisms flanking the FOXP3 gene locus. While no association was found between FOXP3 polymorphisms and AITD in the Japanese cohort, there was a significant association in the Caucasian cohort [11]. In another study in which joint susceptibility loci for T1D and AITD were studied, FOXP3 showed evidence for linkage in T1D, AITD and also in patients with both diseases [12]. The polymorphisms are thought to cause splicing downstream or reduce FOXP3 mrna stability, resulting in a less functional gene. Complex genetics in endocrine autoimmunity Autoimmune polyglandular syndromes (APS) The co-occurrence of various autoimmune diseases together in one person has led to the concept of autoimmune polyglandular syndromes (APS). Other forms of APS have been described with higher frequencies than the rare syndrome of APS-1. Various authors sometimes use strikingly different definitions for the various polyglandular syndromes. This has led to some 1146 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

4 GENETICS IN EOCRINE AUTOIMMUNE DISEASE confusion in the literature. The initial description of APS-2 consisted of AD with AITD [e.g. GD and Hashimoto s disease (HT)] and or T1D [13]. It generally occurs in middle aged women and has more variable disease manifestations. Thereafter, in addition to APS-1 and APS-2, other autoimmune syndromes have been defined. APS-3 was originally described as thyroid autoimmunity occurring together with another autoimmune disease, but excluding AD and hypoparathyroidism. APS-4 was defined as a combination of organ specific autoimmune diseases not included in types 1 through 3. Subsequent studies pointed to the occurrence of other autoimmune manifestations (celiac disease, alopecia, vitiligo, autoimmune hepatitis, pernicious anaemia and hypergonadotropic hypogonadism) in patients with one of these subtypes [14]. Of interest, family members of APS-2, APS-3 and APS-4 patients are frequently diagnosed with autoimmune disorders without the full blown picture of the same combination of autoimmune disease as the index patient. However, in sharp contrast to the diagnosis of APS-1 which can be made by virtue of the AIRE gene mutation, no specific gold standard diagnosis of the other proposed subtypes of APS (2, 3 and 4) is at hand. Therefore Robles et al. [2] have coined the APS-2 as a combination of at least two of the following three autoimmune diseases: T1D, AITD, and AD, which is supported by the notion that further dividing does not assist in understanding the pathogenesis of the various syndromes [15]. Other so called minor criteria, namely celiac disease, vitiligo, pernicious anaemia, myasthenia gravis, alopecia, hypergonadotropic hypogonadism and hypophysitis [14] are sometimes associated with these three major disease criteria. Although APS-1 and APS-2 show similarities in phenotype, AIRE gene mutations are lacking in isolated autoimmune disease (AITD, T1D and AD) and in APS-2 patients [8]. In the simplest model for understanding complex genetics of auto-immunity, the initial step is the loss of tolerance to a peptide of the target organ. The escape in the thymus of self-antigen specific T cells plays a key role in this model. Clones of effector CD4 T cells that recognize the MHC-peptide complex expand and specific cytokines favour inflammation. Type 1 helper (Th1) cell clones produce cytokines such as interferon-c. Type 2 helper (Th2) cells favour autoantibody-mediated disease by stimulating B lymphocytes (see Fig. 1). Genetic factors HLA. Certain HLA alleles, encoded within the MHC on chromosome 6p21 are overrepresented in patients who have T1D, AITD or AD. More than 90% of patients with T1D carry either MHC class II genes HLA-DR3, DQB1*0201 (also referred to as DR3-DQ2) or -DR4,DQB1*0302 (also referred to as DR4-DQ8), versus 40% of controls with either haplotype; furthermore, about 30% of patients have both haplotypes (DR3 4 heterozygotes), which confers the greatest susceptibility [16]. Moreover, MHC class I genes might play a role in T1D [17]. In white populations of European descent, the DR3 haplotype (HLA DRB1*0301- B cell + IFNγ and ILs Th2 cell Th1 cell + Immunoglobulins Figure 1 T cell differentiation and regulation. After contact with the antigen presenting cell (APC), the T cell becomes activated. This cytotoxic T cell elicits cellular differentiation into T helper (Th) cells and regulatory T cells (Treg), immunoglobulin synthesis and cellular proliferation. The Tregs bring on the proper activation of T cells and control the immune response. FOXP3: forkhead box P3, CTLA4: cytotoxic T lymphocyte associated protein 4, IL2-RA: interleukin 2 receptor a-subunit, ILs: interleukins, IFNc: interferon gamma. APC Cytotoxic T cell - IL2-RA + IFNγ and ILs CTLA4 Treg cell FOXP3 European Journal of Clinical Investigation Vol

5 J. WIEBOLT ET AL. DQB1*0201-DQA1*0501) is typically found in approximately 50% of individuals with GD, with a frequency of approximately 25 30% in the background population [18]. In patients with HT, HLA associations have been found with the HLA DR4 haplotypes, although less consistently than in GD [19]. In AD there is a strong association with DRB1*0301-DQA1*0501-DQB1*0201 [2,20]. As previously mentioned, the HLA system plays the biggest role in the aetiology of these auto-immune disorders [21], as in practically all autoimmune diseases. Non-HLA genes. Before GWAS studies PTPN22 and CTLA4 were the most important non-hla genes known to be associated with autoimmune disease. The PTPN22 molecule is involved in the activation of both naïve and activated T cells. The locus encodes for LYP, lymphoid tyrosine phosphatase, which is a negative regulator of the T cell antigen receptor signalling. LYP acts in complex with C-terminal Src kinase (CSK) to negatively regulate signalling from the T cell receptor. Specifically, LYP dephosphorylates positively regulatory tyrosines on LCK, VAV, ZAP-70 and CD3 zeta chains, thereby causing down-regulation of signals from the T cell receptor [22,23] (Fig. 2). PTPs are also needed to revert activated T cells to a resting phenotype [24]. Approximately 10% of healthy subjects in Northern European white populations carry a polymorphism of the PTPN22 gene (arginine to tryptophan at codon 620, 1858C fi T) which leads to a gain of function mutation [25]. Paradoxically, this PTPN T is associated with reduced T cell activation. The codon 620 tryptophan allele is overrepresented in patients who have T1D and GD (17% and 13%, respectively). However, the association of PTPN22 with HT is much weaker than the association with GD [26]. In another study in which the importance of PTPN22-variants regarding the co-occurrence of T1D and AITD was studied, T-allele carriers were more frequently present in the group with AITD + T1D (41%) than in controls (14%), or than in GD or T1D only (17% and 21%, respectively). T-allele carriers were reported to be at particularly high risk of developing both HT and T1D (50%) [27]. APC HLA2 Peptide antigen CD3 TCR CD3ζ VAV - + T cell - ZAP-70 LYP CSK LCK - B7-1 B7-2 X CTLA4 CD28 - sctla4 Figure 2 An APC interacting with a T cell shows the role of key variant autoimmunity molecules. The APC presents a peptide antigen bound to the groove of the HLA class II molecule. This is recognized by the T cell receptor CD3 complex. Before the T cell can become activated, a second signal must be released by the interaction of the costimulatory CD28 molecule with B7 molecules. The CD28 molecule then enables T cell proliferation and activation. In the cytosol positively regulatory tyrosines on LCK, VAV, ZAP-70 and CD3 zeta chains send out messages to receiver-molecules in the cytosol and nucleus. CTLA4 is an inhibitory molecule that can provide a negative second signal, which causes the T cell to become quiescent or to apoptose. Soluble CTLA4 can play a role as a natural inhibitor of CD28 by binding with a higher affinity to B7 molecules and thereby stopping the costimulatory activation. LYP in complex with CSK, stops the regulatory tyrosines preventing further positive signalling ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

6 GENETICS IN EOCRINE AUTOIMMUNE DISEASE Studies into the association between the PTPN22 gene and AD have shown conflicting results [26,28], possibly because of small numbers of analysed patients. CTLA-4 gene polymorphisms have been shown to be associated with a variety of autoimmune conditions among which AITD, T1D and AD. CTLA4 is a cell surface immunoglobulinlike receptor involved in the regulation of T-lymphocyte activation. When antigen presenting cells (APCs) present peptides to T cells within the peptide pockets of HLA class II molecules, costimulation is required. One costimulatory molecule is CD 28, which is activated by B7-1 and B7-2 molecules on the surface of APCs. CTLA4 suppresses T cell activation either by competing with CD28 for binding to B7-1 and B7-2 or by direct suppression of the T cell receptor signalling pathway (Fig. 2). This causes the T cell to be quiescent or go into apoptosis. A circulating soluble form of the CTLA4 protein may also play a role as a natural inhibitor of the CD28 B7 complex by binding to B7 molecules [29]. Moreover, it is suggested that CTLA4 gene polymorphisms play a role in the early stage of T cell differentiation and lineage commitment, with CTLA4 genotypes being correlated with the number of circulating CD4, CD25+ T regulatory lymphocytes [30]. Before GWAS by far the most consistent association reported is with AITD [31]. Although initial analyses gave inconsistent results, now the role of CTLA4 in T1D has been fully confirmed. More recently, Vella et al. [32] discovered a polymorphism in the CD25 gene which encodes the a-chain of the interleukin 2 receptor (IL2RA). IL2 is a powerful growth factor for both T and B cells. This receptor regulates lymphocytes through regulating the activity of Treg cells. Markers within this gene were found to be associated with T1D, with an OR of approximately 1Æ3 [32]. These findings have already been replicated in another T1D cohort [33] and a fine mapping study has placed the most associated SNP within its 5 regulatory region [34]. A study using GD probands has confirmed a modest effect, with an OR of 1Æ24 at the most associated marker [35]. In humans, a rare mutation of CD25 causes severe autoimmune disease [36]. Disease specific genes. Genes that encode proteins specific to the insulin-producing cells of the endocrine pancreas are candidate aetiological determinants for T1D. Consequently, variation at a tandem repeat polymorphism in the regulatory region of the INS has long been established as a susceptibility determinant with a modest effect in T1D [37]. The VNTR is located close to a DNA sequence that regulates INS expression. Based upon the number of repeats, the length of the VNTR can be divided into three classes: class I (570 bp), class II (1640 bp) and class III (2400 bp). Homozygosity for the short class I alleles confers a 2 5-fold increase risk for T1D. Disease protective class III alleles result in higher expression in the thymus and lower expression in the pancreas [38]. It is speculated that infants with this allele are better able to delete autoreactive T cells in the thymus because of the higher thymic expression of insulin that may favour deletion of activated T cells. Subjects having the shorter class I repeat length produce higher amounts of insulin (in pancreas beta cells) [39], which may increase the amount of self-antigen available for autoimmune recognition. In AITD, it is clear that the hallmark for GD is the TSH receptor (TSHR) gene. Although earlier studies gave inconsistent results [40], more recently consistent associations between the TSHR gene and GD were reported. The associated variants lie within the regulatory regions and those encoding the extracellular domain of the receptor. Intriguingly, all the associated TSHR SNPs are intronic [41]. It remains to be determined how the intronic SNPs in the TSHR gene could predispose to GD, but one attractive mechanism is by influencing the splicing of the TSHR gene. Brand et al. [42] suggested that highly associated SNPs are associated with changes in the expression levels of two truncated TSHR mrna isoforms (ST4 and ST5). In thyroid tissue expressing the associated genotype more isoforms were measured than full length TSHR. It is hypothesized that these shorter isoforms, if translated, could produce a soluble A-subunit of the TSHR. It has been suggested that this may initiate or exacerbate autoimmunity in GD. This is based on observations that TSHR autoantibodies preferentially target the extracellular A-subunit [43] and that intramuscular injections of A-subunits in a mouse model are required to induce the production of autoantibodies and hyperthyroidism [44]. Thus, the isoforms ST4 and ST5 would result in higher levels of soluble A-subunit expression in the periphery, therefore increasing the chances of autoantibodies production against the TSHR. Moreover, the thyroglobulin (Tg) gene has also been proposed to be an AITD susceptibility gene, but studies have not shown convincing evidence for association with GD or autoimmune hypothyroidism [45]. An explanation for this might be that the Tg gene is a huge gene and further work is to be performed on screening the enormous diversity of haplotypes. Two studies on the thyroid peroxidase (TPO) gene showed no evidence of association of the TPO gene with AITD [46,47]. Genome-wide association studies (GWAS) in endocrine autoimmunity GWAS in T1D In the first GWAS study, Smyth et al. [48] discovered a locus in the interferon-induced helicase (IFIH) region. Interferoninduced helicase-1 (IFIH1), also known as the melanoma differentiation-associated 5 (MDA-5) or Helicard gene, was identified as contributing susceptibility to T1D in this intensive study of 6500 nonsynonymous SNP markers. The maximally associated allele encodes an alanine to threonine change. The effect was European Journal of Clinical Investigation Vol

7 J. WIEBOLT ET AL. weak, with an OR < 1Æ2 for T1D in whites [49]. The IFIH1 gene is in a region of extended LD on chromosome 2, meaning that it is not yet certain whether IFIH1 is the susceptibility gene within the chromosome 2 genomic region. Based on its functionality, however, it is the strongest candidate within the region as the IFIH gene plays a role in the recognition of the RNA genomes of picornaviruses. The IFIH1 gene encodes a viral RNA-activated apoptosis protein, with a putative role in sensing and triggering clearance responses in virally infected cells [50]. A virus that has been proposed as a potential environmental trigger for T1D is coxsackievirus B4, an enterovirus belonging to the picornavirus family. Infections with enteroviruses are more common among newly diagnosed T1D patients and prediabetic subjects than in the general population. However suggestive this may seem to be, the precise causal role of this gene in T1D is uncertain, future functional experiments should test whether normal immune activation caused by enterovirus infection and mediated by IFIH1 protein may stimulate autoreactive T cells leading to T1D and whether blocking IFIH1 can disrupt this pathogenic mechanism. Finally, in a high-throughput sequencing-study of IFIH1 four rare variants were found that lowered T1D risk independently of each other (OR = 0Æ51 to 0Æ74) [51]. This finding further shows that association between IFIH1 and T1D is inevitable. Before the advent of GWAS, MHC class II locus, as well as the CTLA4, PTPN22, and the IL2RA genes were established to be associated with T1D. Presently, these genes have been confirmed by one of the largest GWAS, the Welcome Trust Case Control Consortium study [52]. In the WTCCC study, undertaken in the British population, seven common diseases were studied amongst which T1D. In studies in 2000 T1D cases and 3000 controls genotyped with a GeneChip (Affymetrix chip), they found seven novel regions with strong evidence of association on chromosome 12q13, 12q24, 16p13, 4q27, 12p13, 18p11 and 10p15. These regions represent functional candidates because of their presumed roles in immune signalling. These genes included ERBB3 (receptor tyrosine-protein kinase erbb-3 precursor) at 12q13, SH2B3 (SH2B adaptor protein 3, also known as LNK, lymphocyte adaptor protein), TRAFD1 (TRAFtype zinc finger domain containing 1) and PTPN11 (protein tyrosine phosphatase, non receptor type 11) at 12q24. The latter is particularly interesting as this is a member of the same family of regulatory phosphatases as PTPN22. Two genes, KIAA0350 and dexamethasone-induced transcript, were suggested at the 16p13 region. Another region found was on 4q27, which contains genes encoding both IL-2 and IL-21. Moreover, the study revealed CD 69 (CD 69 antigen p 60 an early T cell activation antigen) and CLEC (C-type lectin domain family) genes on 12p13, PTPN2 (protein tyrosine phosphatase, non receptor type 2) on 18p11 and CD25, encoding the high-affinity receptor for IL-2 on 10p15. Approximately at the same time, Todd et al. [53] reported a follow-up study in 4000 individuals with T1D, 5000 controls and 2977 family trios, in which the associations of 12q13, 12q24, 16p13 and 18p11 were confirmed. However, the SNPs on chromosome regions 4q27 and 12p13 (IL-2 and IL-21, CD 69 and CLEC) showed weak and no support for disease, respectively. In addition, evidence was obtained for association of the CD226 gene (a T lymphocyte costimulation gene) on chromosome 18q22 with T1D. A genome wide association scan in a large paediatric cohort from Canada, USA and including the Type 1 Diabetes Genetics Consortium Cohort also reported KIAA0350 (now renamed as CLEC16A) on chromosome 16 as a T1D locus [54]. This protein is almost exclusively expressed in dendritic cells, B lymphocytes and natural killer cells. This gene presumably encodes a protein of the previously mentioned calcium dependent, C-type lectin domain family. C-type lectins are known for their recognition of various carbohydrates and are crucial for processes that range from cell adhesion to pathogen recognition [55]. The same group confirmed ERBB3 as a T1D locus, previously reported by the WTCCC [56]. GWAS in AITD In their GWAS on T1D, Todd et al. [53] also genotyped 13 T1Dassociated SNPs in 2200 unrelated individuals with GD. They found some evidence of association for PTPN2 and CD226 on chromosome 18 (OR 1Æ1) and also for loci on 2q11, 4q27 and 5p13. All alleles were associated in the same direction except for the locus on 4q27 involving an interleukin 2 gene, which was associated with a reduced risk in GD while it augmented the susceptibility for T1D. A full genome-wide association analysis solely on AITD has not been published yet. However, a low resolution scan using a modest set of 14Æ500 SNP markers that encoded aminoacid changes in 1000 patients with GD and 1500 controls has been performed [57]. Association of AITD with loci in the TSHreceptor and in a cell surface immunoglobulin (Fc-) receptor (FCRL3) was confirmed. Another large screen on patients with AITD in which affected relative pairs were screened (n = 1119), there was no convincing evidence for HLA, CTLA4 and PTPN22. However, suggestive linkage on 18p11 (PTPN2), 2q36 and 11p15 (CD81 and IGF2) was detected [31]. Elevated logarithms of odds (LODs) were obtained for two additional regions for GD and four regions for HT. Although they likely share many commonalities, there can be difficulties in detecting loci when GD en HT patients are pooled together. Indeed, a recent study on HT has demonstrated different HLA class II associations when compared with GD [58]. These observations might advocate to set up separate GWAS studies for GD and HT. IFIH1 also has been under investigation in GD. A total of 602 GD patients and 446 controls were genotyped for IFIH1. The 1150 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

8 GENETICS IN EOCRINE AUTOIMMUNE DISEASE alanine-carrying allele at the IFIH1 codon 946 polymorphism was present in 66% of GD patient alleles compared to 57% of control subject alleles (OR 1Æ47) [59]. In Table 2, results of all previously mentioned GWAS outcomes have been summarized. Comparisons between diseases For years, our understanding of endocrine autoimmune disorders was mainly centred on the MHC genetic region which comprises the largest degree of risk of disease. Recent advances in genetics have shed new light on immune pathways and mechanisms that are involved in the pathophysiology of immune diseases. Rigorously powered studies have reinforced the notion that T cell response genes are involved in disease pathogenesis and that many autoimmune diseases share similar risk genes. In this paragraph, we explore if there are genes which are shared between autoimmune diseases but work in opposite direction. Previously we mentioned the locus on 4q27 involving the Interleukin 2 gene, which is associated with a reduced risk in GD while it augments the susceptibility for T1D. This finding raises questions because GD and T1D do cluster together, and again shows that the underlying genetics are truly complex. A few studies have confirmed loci shared between T1D, AITD and AD. We have seen that PTPN22 and CTLA4 genes are involved in T1D, AITD and AD risk. In addition, the PTPN22 gene is also associated with rheumatoid arthritis, systemic lupus erythematodus and Crohn s disease. Amazingly, in Crohn s disease, an autoimmune disease which is not clearly associated with T1D or AITD, the same coding SNP (R602W) in PTPN22 which predisposes to T1D, protects against Crohn s disease [60]. This might be an explanation for the fact that these diseases do not cluster together. Sirota et al. [61] also show that Crohn s disease does not relate to other autoimmune diseases by using a mathematical model. By using data of the WTCCC and adding independent GWAS studies, they compared genetic variation profiles of six autoimmune diseases as well as five non-autoimmune diseases. They considered 573 commonly measured SNPs and hypothesized to find all the known autoimmune disease clustered similarly. However, they found two separate classes of autoimmune disease, with rheumatoid arthritis and ankylosing spondylitis falling into one class and multiple sclerosis (MS) and AITD into the other; T1D was found to be similar to AITD but not to MS and therefore was difficult to classify. Crohn s disease was similar to none of the other five autoimmune diseases and was thus considered to be a separate entity. Thus, they suggested that the same allele can be associated with multiple phenotypes. A possible explanation for the same SNP allele being associated with different phenotypes is that it interacts differentially with genetic and environmental factors and therefore the biological context of the SNP varies in different individuals (with their specific environment, e.g. viruses, food, toxins). Moreover, they found certain alleles to be disease associated in one setting and disease protective in another. It is hypothesized that there are some loci which predispose individuals to disease in general, and other loci that determine which class or more specifically which disease an individual is more likely to develop. For example, there might be MHC binders which might load pathogenic peptides for one disease but not for the other. Therefore SNPs in these binders may act disease-associated in one setting and disease-protective in another. A complex picture arises regarding the differences and commonalities of T1D and celiac disease. It is known that celiac disease, vitiligo, pernicious anaemia, etc. are associated with T1D. Four alleles (RGS1 on chromosome 1q31, CTLA4 on 2q33, SH2B3 on 12q24 and PTPN2 on 18p11) showed the same direction of association in the two diseases. However, the minor alleles of the SNPs IL18RAP on chromosome 2q12 and TAGAP on 6q25 were negatively associated with T1D, whereas these minor alleles were positively associated with celiac disease [62]. The authors propose two hypotheses: the causal variants in these two regions may have opposite biological effects in T1D and celiac disease, or there may be different causal variants for each disease in each region with the typed marker SNPs tagging these causal variants. As they did not find evidence for a second locus, they favoured the possibility that the causal variants have opposite effects. Outlook into the future Taken together, autoimmune endocrine disease is highly prevalent and occurs at an increasing rate, with doubling of T1D over the last 30 years. Its pathophysiology involves interactions of T cells, B cells and specific cell types or tissues of the organ involved. Although HLA markers bear the largest part in the genetic predisposition to autoimmunity, non-hla factors have an additional influence. Future studies will hopefully lead to better understanding of these non-hla factors and of genegene interactions of HLA with non-hla factors. The complexity of the genetics is technically still very demanding. A first step in following up on association results will therefore presumably lie in new technological developments, which hopefully will enlarge our insight which should ultimately translate into new clinical applications. Technological developments New technological developments such as next-generation sequencing technologies can help us to identify the causative variants. Next generation sequencing (or high-throughput sequencing) aims at parallelizing the sequencing process, producing thousands or millions of sequences at once. In this European Journal of Clinical Investigation Vol

9 J. WIEBOLT ET AL. Table 2 Susceptibility genes for type 1 diabetes (T1D) and autoimmune thyroid disease (AITD) identified and confirmed in recent high-powered genetic studies (see paragraph Genome-wide association studies (GWAS) in endocrine autoimmunity for more details, references 49,52,53,54 and 56) Minor allele (OR) Candidate gene (non-hla) Gene Symbol Chromosome Function T1D AITD Cytotoxic T-Lymfocyte Associated protein 4 CTLA4 2q33 Regulation of T-lymphocyte activation 1Æ2 1Æ5 Protein Tyrosine Phosphatase Non-receptor 22 PTPN22 (LYP) 1p13 Lymphoid-specific intracellular phosphatase involved in regulating the T-cell receptor signalling pathways 2Æ0 1Æ7 Interleukin 2 Receptor, a-chain IL2RA 10p15 Element of the high-affinity IL2 receptor, involved in IL2 signalling, present on many T cell subsets, regulator of Treg cells Interferon-Induced Helicase-1 IFIH1 2q24 Receptor for double-stranded DNA from viral infections Receptor tyrosine-protein kinase erbb-3 precursor ERBB3 12q13 A member of the epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, which can lead to the activation of pathways leading to cell proliferation or differentiation SH2B adaptor protein 3 SH2B3 (LNK) 12q24 Regulation of T-cell receptor, growth factor and cytokine receptor-mediated signalling 2Æ0 0Æ9 1Æ3 1Æ2 1Æ2 0Æ9 TRAF-type zinc finger Domain containing 1 TRAFD1 12q24 A negative feedback regulator that controls excessive immune responses 1Æ3 Protein Tyrosine Phosphatase Non-receptor 11 PTPN11 12q24 Plays a regulatory role in cell signalling events, such as mitogenic activation, metabolic control, transcription regulation and cell migration 1Æ3 Interleukin 2 (Interleukin 21) IL2 (-IL 21) 4q27 IL2: T-cell growth factor; activation and proliferation of NK cells, monocytes, macrophages; differentiation of B cells. IL21: Amplification of Th response 1Æ1 Protein Tyrosine Phosphatase Non-receptor 2 PTPN2 18p11 Signalling molecule that regulates a variety of cellular processes including cell growth, differentiation, mitotic cycle and oncogenic transformation 1Æ3 1Æ1 CD226 molecule CD226 18q22 A glycoprotein expressed on the surface of NK cells, platelets, monocytes and T cells, involved in naïve T and NK-T cell differentiation and proliferation C-type lectin domain family CLEC16A 16p13 Involved in cell adhesion and pathogen recognition Fc receptor-like 3 FCRL3 1q23 Member of the immunoglobulin receptor superfamily, contains immunoreceptortyrosine activation and inhibitory motifs, not done. 1Æ2 0Æ8 1Æ1 1Æ ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

10 GENETICS IN EOCRINE AUTOIMMUNE DISEASE manner, one can rapidly process thousands of samples which are needed in GWAS studies. Above all, it lowers the cost of DNA sequencing. Furthermore, will functional studies of gene products enable us to dissect gene function and their effect on disease. Aetiology In the near future, additional GWAS studies may unveil other genes involved in autoimmune disease. Deep sequencing may lead to identification of causative genes. Genes (or gene regions) associated with one autoimmune disease may be studied in another autoimmune disease which may lead to further understanding of the roles of the SNPs involved in the disease process. More perplexing is the finding that sometimes a certain gene variant has an opposite effect in two diseases, for example, the previously mentioned SNP on 4q27 involving the Interleukin 2 gene, leading to AITD actually protects for T1D. Dissection of these genes might shed a light on why two autoimmune diseases sometimes occur together in one person, while other patients are affected by only one of these autoimmune diseases. The recent finding that the innate immune system may also be involved in autoimmune disease opens new venues. The identification of IFIH1, a helicase possibly involved in the interaction of T cells with viruses may be a starting point for further research into interactions of the immune system in a host with a specific genetic make-up with viruses and or other antigens. The recent progress into the world of micro-rnas may open new paths to the understanding of the association of intronvariants (e.g. the Tg gene) with autoimmune disease. Although the current understanding of genetic disease in general and of autoimmune endocrine disease in particular heavily depends on work in Caucasians, studies in other ethnic groups may unravel other genetic risk factors and underlying mechanisms. Future studies will ultimately always depend on large, welldefined cohorts. Although in some diseases (T1D) such cohorts do exist, in other areas such as AITD and especially of less prevalent diseases such as AD, they are practically inexistent. It will take a large effort and good collaboration between groups of scientists, preferably in a number of countries, to set up large well-defined cohorts in various ethnicities necessary for future genetic studies. Disease management It is of note that use of knowledge about the pathophysiology is proven to be of use in preventive therapy. For example, treatment with a monoclonal antibody to the T cell receptor component CD3 has long-term effects by inducing a slight reduction of the loss of insulin secretion in patients with newly diagnosed diabetes [63]. Moreover, an IL-2 antibody (Zenapax, Biogen and PDL Biopharma) is currently under trial in a phase 2 study in patients with T1D and in patients with MS [64]. Especially further dissection of the biochemical pathways in which the products of risk loci are known to function can lead to new management strategies. Conclusion Type 1 diabetes and AITD are relatively common diseases arising from the combined effects of an increasing number of genetic and environmental (presumably viral) factors. Both candidate gene and GWAS approaches have just begun to unravel multiple pathways that operate at many different layers of the immune system, including HLA class II and I molecules, T cell receptors, T and B cell activation, innate pathogen-viral responses, chemokine and cytokine signalling and T regulatory and antigen-presenting cell functions. It is likely that these subtle defects are working in concert to drive disease pathogenesis. Next to the predominant effect of HLA class II and I effects, SNPs in PTPN22 and CTLA4 have been found to be associated with several autoimmune diseases, while VNTR class I alleles of the INS is an example of a tissue specific risk factor for T1D; intronic SNPs in the TSH gene have been proposed to be risk factors for GD possibly by influencing splicing. Recently GWAS in T1D has led to the uncovering of a limited number of common variants with modest effect. Full GWAS for AITD are so far lacking. Future studies should improve the identification of causative genes. Fine mapping can determine if the associated SNP actually is the causal variant. It is known that disease-associated SNPs can be hundreds of kb away from the gene(s) they act on. One attractive area that also should be explored is deep sequencing to search for rare variants (rather than common SNP variants) that may exert large effects that have not yet been appreciated. Interestingly, shared genetic pathways may have different effects in different autoimmune disorders. According to the perception that sometimes causal variants have opposite effects, one might advocate the existence of a general immune related profile, rather than a disease-related profile. Then linking genotypes with phenotypes and moreover the impact of environmental factors will be valuable in determining the aetiology. Moreover, gene gene interactions could play a role by turning genes off or on. Moving forward, the study of the immunology and genetics of endocrine autoimmune disease will likely provide new insights. The challenge ahead is to translate these insights in clinical relevance. In particular more data are needed on the interaction between the genetic disease variation present in a patient and his or her ability to respond to, for example, immunosuppressive therapies and or antigen-specific DNA vaccines and antigenic peptides. As patients are carriers of different European Journal of Clinical Investigation Vol

11 J. WIEBOLT ET AL. numbers and types of disease variation, it can be anticipated that they will react differently on treatment and have different disease course and complication accordingly. Further research may clarify whether the use of genetic data for personalized medicine is truly feasible. Address Department of Endocrinology, University Medical Centre Utrecht, Utrecht, the Netherlands (J. Wiebolt); Section Research, Department of Medical Genetics, University Medical Centre Utrecht, Str.0.308, PO Box 85060, 3508 AB Utrecht, the Netherlands (B. P. C. Koeleman); Department of Endocrinology, University Medical Centre Utrecht, L00.407, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands (T. W. van Haeften). Correspondence to: J. Wiebolt, MD, University Medical Centre Utrecht, L00.407, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands. Tel.: ; fax: ; Received 15 April 2010; accepted 16 July 2010 References 1 Huber A, Menconi F, Corathers S, Jacobson EM, Tomer Y. Joint genetic susceptibility to type 1 diabetes and autoimmune thyroiditis: from epidemiology to mechanisms. Endocr Rev 2008;29: Robles DT, Fain PR, Gottlieb PA, Eisenbarth GS. The genetics of autoimmune polyendocrine syndrome type II. Endocrinol Metab Clin North Am 2002;31:353 vii. 3 Lettre G, Rioux JD. Autoimmune diseases: insights from genomewide association studies. Hum Mol Genet 2008;17:R Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007;449: Husebye ES, Perheentupa J, Rautemaa R, Kampe O. Clinical manifestations and management of patients with autoimmune polyendocrine syndrome type I. J Intern Med 2009;265: Kumar PG, Laloraya M, She JX. Population genetics and functions of the autoimmune regulator (AIRE). Endocrinol Metab Clin North Am 2002;31: Hubert FX, Kinkel SA, Crewther PE, Cannon PZ, Webster KE, Link M et al. Aire-deficient C57BL 6 mice mimicking the common human 13-base pair deletion mutation present with only a mild autoimmune phenotype. J Immunol 2009;182: Meyer G, Donner H, Herwig J, Bohles H, Usadel KH, Badenhoop K. Screening for an AIRE-1 mutation in patients with Addison s disease, type 1 diabetes, Graves disease and Hashimoto s thyroiditis as well as in APECED syndrome. Clin Endocrinol (Oxf) 2001;54: Wildin RS, Ramsdell F, Peake J, Faravelli F, Casanova JL, Buist N et al. X-linked neonatal diabetes mellitus, enteropathy and endocrinopathy syndrome is the human equivalent of mouse scurfy. Nat Genet 2001;27: Bjornvold M, Amundsen SS, Stene LC, Joner G, hl-jorgensen K, Njolstad PR et al. FOXP3 polymorphisms in type 1 diabetes and coeliac disease. J Autoimmun 2006;27: Ban Y, Tozaki T, Tobe T, Ban Y, Jacobson EM, Concepcion ES et al. The regulatory T cell gene FOXP3 and genetic susceptibility to thyroid autoimmunity: an association analysis in Caucasian and Japanese cohorts. J Autoimmun 2007;28: Villano MJ, Huber AK, Greenberg DA, Golden BK, Concepcion E, Tomer Y. Autoimmune thyroiditis and diabetes: dissecting the joint genetic susceptibility in a large cohort of multiplex families. J Clin Endocrinol Metab 2009;94: Neufeld M, Maclaren NK, Blizzard RM. Two types of autoimmune Addison s disease associated with different polyglandular autoimmune (PGA) syndromes. Medicine (Baltimore) 1981;60: Betterle C, Dal PC, Mantero F, Zanchetta R. Autoimmune adrenal insufficiency and autoimmune polyendocrine syndromes: autoantibodies, autoantigens, and their applicability in diagnosis and disease prediction. Endocr Rev 2002;23: Michels AW, Eisenbarth GS. Autoimmune polyendocrine syndrome type 1 (APS-1) as a model for understanding autoimmune polyendocrine syndrome type 2 (APS-2). J Intern Med 2009;265: Erlich H, Valdes AM, Noble J, Carlson JA, Varney M, Concannon P et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes 2008;57: Nejentsev S, Howson JM, Walker NM, Szeszko J, Field SF, Stevens HE et al. Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A. Nature 2007;450: Farid NR, Sampson L, Noel EP, Barnard JM, Mandeville R, Larsen B et al. A study of human leukocyte D locus related antigens in Graves disease. J Clin Invest 1979;63: Tandon N, Zhang L, Weetman AP. HLA associations with Hashimoto s thyroiditis. Clin Endocrinol (Oxf) 1991;34: Weetman AP, Zhang L, Tandon N, Edwards OM. HLA associations with autoimmune Addison s disease. Tissue Antigens 1991;38: Zhernakova A, van Diemen CC, Wijmenga C. Detecting shared pathogenesis from the shared genetics of immune-related diseases. Nat Rev Genet 2009;10: Gjorloff-Wingren A, Saxena M, Williams S, Hammi D, Mustelin T. Characterization of TCR-induced receptor-proximal signaling events negatively regulated by the protein tyrosine phosphatase PEP. Eur J Immunol 1999;29: Mustelin T, Abraham RT, Rudd CE, Alonso A, Merlo JJ. Protein tyrosine phosphorylation in T cell signaling. Front Biosci 2002;7:d Iivanainen AV, Lindqvist C, Mustelin T, Andersson LC. Phosphotyrosine phosphatases are involved in reversion of T lymphoblastic proliferation. Eur J Immunol 1990;20: Vang T, Congia M, Macis MD, Musumeci L, Orru V, Zavattari P et al. Autoimmune-associated lymphoid tyrosine phosphatase is a gain-of-function variant. Nat Genet 2005;37: Kahles H, Ramos-Lopez E, Lange B, Zwermann O, Reincke M, Badenhoop K. Sex-specific association of PTPN T with type 1 diabetes but not with Hashimoto s thyroiditis or Addison s disease in the German population. Eur J Endocrinol 2005;153: Dultz G, Matheis N, Dittmar M, Rohrig B, Bender K, Kahaly GJ. The protein tyrosine phosphatase non-receptor type 22 C1858T polymorphism is a joint susceptibility locus for immunthyroiditis and autoimmune diabetes. Thyroid 2009;19: Roycroft M, Fichna M, McDonald D, Owen K, Zurawek M, Gryczynska M et al. The tryptophan 620 allele of the lymphoid tyrosine phosphatase (PTPN22) gene predisposes to autoimmune Addison s disease. Clin Endocrinol (Oxf) 2009;70: ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation