Endocrine autoimmune disease: genetics becomecomplexJanneke 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

ABSTRACTThe endocrine system is a frequent target in pathogenic autoimmune responses. Type 1 diabetes and autoim-mune thyroid disease are the prevailing examples. When several diseases cluster together in one individual, thephenomenon is called autoimmune polyglandular syndrome. Progress has been made in understanding thegenetic factors involved in endocrine autoimmune diseases. Studies on monogenic autoimmune diseases suchas autoimmune polyglandular syndrome type 1, immunodysregulation, polyendocrinopathy, enteropathy,X-linked and primary immune deficiencies helped uncover the role of key regulators in the preservation ofimmune tolerance. Alleles of the major histocompatibility complex have been known to contribute to the suscep-tibility to most forms of autoimmunity for more than 3 decades. Furthermore, sequencing studies revealed threenon-major histocompatibility complex loci and some disease specific loci, which control T lymphocyte activationor signalling. Recent genome-wide association studies (GWAS) have enabled acceleration in the identification ofnovel (non-HLA) loci and hence other relevant immune response pathways. Interestingly, several loci are sharedbetween autoimmune diseases, and surprisingly some work in opposite direction. This means that the sameallele which predisposes to a certain autoimmune disease can be protective in another. Well powered GWAS intype 1 diabetes has led to the uncovering of a significant number of risk variants with modest effect. These stud-ies showed that the innate immune system may also play a role in addition to the adaptive immune system. It isanticipated that next generation sequencing techniques will uncover other (rare) variants. For other autoimmunedisease (such as autoimmune thyroid disease) GWAS are clearly needed.

Keywords Autoimmune thyroid disease, complex genetics, genome-wide association studies, polyglandularsyndrome, single nucleotide polymorphism, type 1 diabetes.

Eur J Clin Invest 2010; 40 (12): 1144–1155

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 dys-

regulation through unknown mechanisms. Proper develop-

ment 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 autoim-

mune 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).

DOI: 10.1111/j.1365-2362.2010.02366.x

REVIEW

1144 European Journal of Clinical Investigation Vol 40

The common autoimmune diseases have a complex genetic

basis, which means that several genes and environmental fac-

tors 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 chromo-

some 6p21 contribute to T1D, Graves’ disease (GD), and Addi-

son’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 develop-

ment 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 associ-

ation 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 autoimmuni-

ty 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 syn-

dromes, which underscore the importance of genetically deter-

mined 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

gene loci [among which the variable number of tandem

repeats (VNTR) of the insulin gene (INS) and the thyroid-stim-

ulating 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.

Genetic studies

Two common approaches for distinguishing genetic factors are

the candidate gene approach and the model free mapping

approach.

Candidate gene studiesSeveral 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 tech-

nique 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 can-

didate gene studies are used when the effect size of the variant

is expected to be large.

Affected sib pair analysisThe 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 sis-

ters having diabetes type 1. The basis of the analysis is that sub-

jects 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.

GWASAs 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

Table 1 Tissue specific and multi tissue autoimmune diseases

Tissue specific Multi tissue

Diabetes mellitus type 1 Systemic lupus

erythematodus

Autoimmune hypothyroidism

(Hashimoto)

Dermatomyositis

Addison’s disease Goodpasture syndrome

Celiac disease Rheumatoid arthritis

Crohn’s disease Scleroderma

Multiple sclerosis Sjogren’s syndrome

Myasthenia gravis Ankylosing spondylitis

Vitiligo

Hypophysitis

Graves’ disease

GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE

European Journal of Clinical Investigation Vol 40 1145

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-ran-

dom association of alleles) between each other [4]. The signifi-

cance 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 pre-

disposing 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 300 000 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 limita-

tions. 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 architec-

ture 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 autoimmunitysyndromes

Autoimmune polyglandular syndrome type 1The monogenic APS-1 is of great interest as this disease repre-

sents 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 asso-

ciated 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 autore-

active T cells, mature and escape deletion in the thymus and

migrate into the periphery, where they are capable of destroy-

ing multiple specific tissues. Human studies of isolated autoim-

mune disorders, such as AD or autoimmune hypothyroidism,

occurring without evidence of other autoimmune disease did

not detect mutations in the AIRE gene [8].

IPEXAnother rare monogenic syndrome, the rare IPEX syndrome,

led to the unravelling of the importance of the transcription fac-

tor 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 dam-

pen 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 suppres-

sive action because of a mutation in the FOXP3 gene, activated T

cells and cytokine production are increased leading to autoim-

munity. 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 micro-

satellite 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 sus-

ceptibility 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 polyglandu-

lar syndromes (APS). Other forms of APS have been described

with higher frequencies than the rare syndrome of APS-1. Vari-

ous authors sometimes use strikingly different definitions for

the various polyglandular syndromes. This has led to some

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1146 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

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. Thereaf-

ter, in addition to APS-1 and APS-2, other autoimmune syn-

dromes have been defined. APS-3 was originally described as

thyroid autoimmunity occurring together with another autoim-

mune disease, but excluding AD and hypoparathyroidism.

APS-4 was defined as a combination of organ specific autoim-

mune diseases not included in types 1 through 3. Subsequent

studies pointed to the occurrence of other autoimmune mani-

festations (celiac disease, alopecia, vitiligo, autoimmune hepati-

tis, 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 auto-

immune 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 dis-

ease, 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 dis-

ease (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 pep-

tide of the target organ. The escape in the thymus of self-anti-

gen 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 chro-

mosome 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-

Th1

Th2 cell

IFNγand B cell

Th1cell

ILs

+

+Immuno-globulins

APC

Cytotoxic

T cellIFNγ and ILs+

Treg cell

CTLA4

Treg cellIL2-RA

FOXP3-

Figure 1 T cell differentiation and regula-tion. After contact with the antigen present-ing cell (APC), the T cell becomes activated.This cytotoxic T cell elicits cellular differen-tiation into T helper (Th) cells and regula-tory T cells (Treg), immunoglobulinsynthesis and cellular proliferation. TheTregs bring on the proper activation of Tcells and control the immune response.FOXP3: forkhead box P3, CTLA4: cytotoxicT lymphocyte associated protein 4, IL2-RA:interleukin 2 receptor a-subunit, ILs:interleukins, IFNc: interferon gamma.

GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE

European Journal of Clinical Investigation Vol 40 1147

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’ haplo-

types, 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 big-

gest 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 associ-

ated with autoimmune disease.

The PTPN22 molecule is involved in the activation of both

naı̈ve and activated T cells. The locus encodes for LYP, lym-

phoid 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]. Approxi-

mately 10% of healthy subjects in Northern European white

populations carry a polymorphism of the PTPN22 gene (argi-

nine to tryptophan at codon 620, 1858C fi T) which leads to a

gain of function mutation [25]. Paradoxically, this PTPN22

1858T 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 associ-

ation 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 develop-

ing both HT and T1D (50%) [27].

APC T cell

Peptide tiantigen

HLA2 TCR-CD3

CD3VAV

-

CD3ζ

ZAP-70LCK

+

LCKLYP

CSK-

CSK

CTLA4

CD28

B7-1

B7-2 X

sCTLA4-

Figure 2 An APC interacting with a T cell shows the role of key variant autoimmunity molecules. The APC presents a peptide anti-gen bound to the groove of the HLA class II molecule. This is recognized by the T cell receptor ⁄ CD3 complex. Before the T cell canbecome activated, a second signal must be released by the interaction of the costimulatory CD28 molecule with B7 molecules. TheCD28 molecule then enables T cell proliferation and activation. In the cytosol positively regulatory tyrosines on LCK, VAV, ZAP-70and CD3 zeta chains send out messages to receiver-molecules in the cytosol and nucleus. CTLA4 is an inhibitory molecule that canprovide a negative second signal, which causes the T cell to become quiescent or to apoptose. Soluble CTLA4 can play a role as anatural inhibitor of CD28 by binding with a higher affinity to B7 molecules and thereby stopping the costimulatory activation. LYPin complex with CSK, stops the regulatory tyrosines preventing further positive signalling.

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1148 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

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 associ-

ated with a variety of autoimmune conditions among which

AITD, T1D and AD. CTLA4 is a cell surface immunoglobulin-

like receptor involved in the regulation of T-lymphocyte activa-

tion. 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 compet-

ing with CD28 for binding to B7-1 and B7-2 or by direct sup-

pression of the T cell receptor signalling pathway (Fig. 2). This

causes the T cell to be quiescent or go into apoptosis. A circulat-

ing soluble form of the CTLA4 protein may also play a role as a

natural inhibitor of the CD28 ⁄ B7 complex by binding to B7 mol-

ecules [29]. Moreover, it is suggested that CTLA4 gene poly-

morphisms play a role in the early stage of T cell differentiation

and lineage commitment, with CTLA4 genotypes being corre-

lated with the number of circulating CD4, CD25+ T regulatory

lymphocytes [30]. Before GWAS by far the most consistent asso-

ciation 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 regu-

lating 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 candi-

date 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 determi-

nant 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 protec-

tive 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 recep-

tor (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 extracel-

lular 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 associ-

ated SNPs are associated with changes in the expression levels

of two truncated TSHR mRNA isoforms (ST4 and ST5). In thy-

roid 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 pro-

duction 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 pro-

posed to be an AITD susceptibility gene, but studies have not

shown convincing evidence for association with GD or autoim-

mune hypothyroidism [45]. An explanation for this might be

that the Tg gene is a huge gene and further work is to be per-

formed 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) inendocrine autoimmunity

GWAS in T1DIn the first GWAS study, Smyth et al. [48] discovered a locus in

the interferon-induced helicase (IFIH) region. Interferon-

induced helicase-1 (IFIH1), also known as the melanoma differ-

entiation-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

GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE

European Journal of Clinical Investigation Vol 40 1149

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-acti-

vated 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 trig-

ger 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 sequenc-

ing-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 con-

firmed by one of the largest GWAS, the Welcome Trust Case

Control Consortium study [52]. In the WTCCC study, under-

taken 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 associa-

tion 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 (TRAF-

type 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 con-

tains 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 lympho-

cytes 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 recog-

nition 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 AITDIn their GWAS on T1D, Todd et al. [53] also genotyped 13 T1D-

associated 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 TSH-

receptor 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 convinc-

ing evidence for HLA, CTLA4 and PTPN22. However, sugges-

tive 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 commonali-

ties, 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 com-

pared 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

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1150 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

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 pre-

viously mentioned GWAS outcomes have been summarized.

Comparisons between diseases

For years, our understanding of endocrine autoimmune disor-

ders 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 simi-

lar 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 rheuma-

toid arthritis, systemic lupus erythematodus and Crohn’s dis-

ease. 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, pro-

tects 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 consid-

ered 573 commonly measured SNPs and hypothesized to find

all the known autoimmune disease clustered similarly. How-

ever, 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 differ-

ent 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 indi-

viduals 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 bind-

ers which might load pathogenic peptides for one disease but

not for the other. Therefore SNPs in these binders may act dis-

ease-associated in one setting and disease-protective in another.

A complex picture arises regarding the differences and com-

monalities of T1D and celiac disease. It is known that celiac dis-

ease, 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 direc-

tion 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 tag-

ging 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 preva-

lent 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 gene-

gene interactions of HLA with non-HLA factors. The complex-

ity of the genetics is technically still very demanding. A first

step in following up on association results will therefore pre-

sumably lie in new technological developments, which hope-

fully will enlarge our insight which should ultimately translate

into new clinical applications.

Technological developmentsNew 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

GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE

European Journal of Clinical Investigation Vol 40 1151

Table 2 Susceptibility genes for type 1 diabetes (T1D) and autoimmune thyroid disease (AITD) identified and confirmed in recenthigh-powered genetic studies (see paragraph ‘Genome-wide association studies (GWAS) in endocrine autoimmunity’ for moredetails, references 49,52,53,54 and 56)

Candidate gene (non-HLA) Gene Symbol Chromosome Function

Minor allele

(OR)

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

2Æ0 1Æ2

Interferon-Induced Helicase-1 IFIH1 2q24 Receptor for double-stranded DNA from viral

infections

0Æ9 0Æ9

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

1Æ3 ND

SH2B adaptor protein 3 SH2B3 (LNK) 12q24 Regulation of T-cell receptor, growth factor and

cytokine receptor-mediated signalling

1Æ2 ND

TRAF-type zinc finger Domain

containing 1

TRAFD1 12q24 A negative feedback regulator that controls

excessive immune responses

1Æ3 ND

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 ND

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 ND

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 naı̈ve T and NK-T cell

differentiation and proliferation

1Æ2 1Æ1

C-type lectin domain family CLEC16A 16p13 Involved in cell adhesion and pathogen

recognition

0Æ8 ND

Fc receptor-like 3 FCRL3 1q23 Member of the immunoglobulin receptor

superfamily, contains immunoreceptor-

tyrosine activation and inhibitory motifs

ND 1Æ2

ND, not done.

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1152 ª 2010 The Authors. European Journal of Clinical Investigation ª 2010 Stichting European Society for Clinical Investigation Journal Foundation

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.

AetiologyIn 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 under-

standing 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 inter-

action 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 intron-

variants (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, well-

defined cohorts. Although in some diseases (T1D) such cohorts

do exist, in other areas such as AITD and especially of less pre-

valent 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 managementIt is of note that use of knowledge about the pathophysiology is

proven to be of use in preventive therapy. For example, treat-

ment with a monoclonal antibody to the T cell receptor compo-

nent 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 fur-

ther dissection of the biochemical pathways in which the prod-

ucts of risk loci are known to function can lead to new

management strategies.

Conclusion

Type 1 diabetes and AITD are relatively common diseases aris-

ing from the combined effects of an increasing number of

genetic and environmental (presumably viral) factors. Both can-

didate 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 sub-

tle 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 com-

mon 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 actu-

ally 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 link-

ing genotypes with phenotypes and moreover the impact of

environmental factors will be valuable in determining the aeti-

ology. 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, immu-

nosuppressive therapies and ⁄ or antigen-specific DNA vaccines

and antigenic peptides. As patients are carriers of different

GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE

European Journal of Clinical Investigation Vol 40 1153

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 Utr-

echt, 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 Nether-

lands (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.: +31 88 75 517 22; fax: +31 88 75 555 14;

e-mail: j.wiebolt@umcutrecht.nl

Received 15 April 2010; accepted 16 July 2010

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GENETICS IN ENDOCRINE AUTOIMMUNE DISEASE