U.S. flag

An official website of the United States government

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Anaya JM, Shoenfeld Y, Rojas-Villarraga A, et al., editors. Autoimmunity: From Bench to Bedside [Internet]. Bogota (Colombia): El Rosario University Press; 2013 Jul 18.

Cover of Autoimmunity

Autoimmunity: From Bench to Bedside [Internet].

Show details

Chapter 18Non-HLA genes and autoimmune diseases

, , and .

Introduction

Autoimmune diseases (ADs) are responsible for a substantial amount of disability and morbidity worldwide. Although the epidemiology varies according to individual conditions, collectively autoimmune prevalence is at least 5% in the general population and is one of the major causes of premature mortality in young and middle-aged women (1).

ADs encompass a broad range of phenotypic manifestations and severity. The pathogenesis is considered to be multifactorial, and several of the features suggest shared etiologic factors (see Chapter 14). Most ADs are characterized by female predominance, and many are associated with the production of autoantibodies. A variety of pathogenic mechanisms are ultimately triggered during the progression of ADs, and dysregulations involving major cell signaling pathways and inflammatory responses are consistent features in most ADs (2,3). ADs can be categorized into two types of disorders. First, systemic ADs, such as systemic lupus erythematosus (SLE), in which the loss of immune tolerance is directed towards systemic antigens and disease manifestations can occur at a variety of different sites in the body. Second, organ-specific ADs, in which the immune response is predominantly or exclusively directed towards tissue-specific elements [e.g., type 1 diabetes (T1D) targets the pancreas, autoimmune thyroid disease (AITD) attacks the thyroid gland].

The inheritance pattern of ADs is polygenic; this indicates that multiple genes are involved in defining their development and outcome. Although the exact number of risk loci is not known for many ADs, the numbers are likely in the 100s for each. The human leukocyte antigen (HLA) region typically confers the strongest association with ADs discovered to date. However, other genes, both located within and outside of the HLA region, are risk factors for these diseases.

Recent advances in genomics have led to increased understanding of the molecular underpinnings of complex diseases. For instance, the technological and manufacturing advances made in the early 2000s led to the use of microarrays to conduct large-scale, mostly unbiased surveys of the human genome such as genome-wide association studies (GWAS) (BOX 1) to determine which genetic factors influence the onset and development disease. However, due to their multifactorial and polygenic nature and accompanied by a differential penetrance, genetic heterogeneity among populations, and the influence of environmental factors (4,5), untangling the genetic determinants defining their outcome and onset has proven to be extremely challenging. Data showing the existence of different ADs within a single family or within the same individual suggest a combination of genetic defects that may predispose individuals to different ADs sharing common pathogenic pathways (6,7). This chapter reviews the reported non-HLA shared genes, based on the plausibility of their functional or biological mechanisms, that affect the susceptibility to the most common ADs.

Shared genetic variants among ADs

GWAS has opened up a new horizon on the genetics of complex diseases by defining the genomic regions harboring disease risk alleles that display association at convincing levels of statistical significance (BOX 1) (8,9). In this regard, cohort studies have identified associations with common genetic markers across the entire human genome that satisfy stringent statistical criteria and have been replicated across multiple cohorts (Figure 1).

Figure 1. Frequency of autoimmune diseases with significant reported genetic variants (p<1x10-5) in genome-wide association studies (GWAS) curated from the (NHGRI, http://www.genome.gov/gwastudies/) and the database of genotypes and phenotypes (dbGAP, http://www.ncbi.nlm.nih.gov/gap), both accessed in September of 2012. For the NHGRI, a total of 8964 genetic variants were encountered, out of which 917 were significant variants associated with autoimmune disease susceptibility; while in dbGAP out of 31246 reported variants, 690 were mutually exclusive from the NHGRI for a grand total of 1607 genetic variants related to genes associated in a GWAS for any population.

Figure 1

Frequency of autoimmune diseases with significant reported genetic variants (p<1x10-5) in genome-wide association studies (GWAS) curated from the (NHGRI, http://www.genome.gov/gwastudies/) and the database of genotypes and phenotypes (dbGAP, http://www.ncbi.nlm.nih.gov/gap), (more...)

Perhaps nowhere have such studies been more fruitful than in ADs: more than 150 genetic loci have been shown to be associated with one or more autoimmune disorders (Figure 2). Although in most cases, the precise causal alleles or genes driving these associations have not been identified, some associated loci can be implicated with particular functional pathways including the intracellular signaling networks that drive the activation of T and B cells, signaling by cytokines and cytokine receptors, and pathways that mediate innate immunity and microbial responses (Table 1).

Figure 2. Weighted list created from the reported significant mapped genes in the current genome-wide association studies (GWAS) curated from the (NHGRI, http://www.genome.gov/gwastudies/) and the database of genotypes and phenotypes (dbGAP, http://www.ncbi.nlm.nih.gov/gap), both accessed in September of 2012.

Figure 2

Weighted list created from the reported significant mapped genes in the current genome-wide association studies (GWAS) curated from the (NHGRI, http://www.genome.gov/gwastudies/) and the database of genotypes and phenotypes (dbGAP, http://www.ncbi.nlm.nih.gov/gap), (more...)

Table 1A. AD susceptibility loci involved in immune signaling (including the MHC region).

Table 1A

AD susceptibility loci involved in immune signaling (including the MHC region).

Table 1B. AD susceptibility loci involved in T cell differentiation.

Table 1B

AD susceptibility loci involved in T cell differentiation.

Table 1C. AD susceptibility loci involved in innate immunity.

Table 1C

AD susceptibility loci involved in innate immunity.

Table 1D. Rare or low frequency alleles associated with AD susceptibility.

Table 1D

Rare or low frequency alleles associated with AD susceptibility.

The results of several GWAS show that genetic variations in multiple genes are associated with each AD and that the associations are modest. The majority of GWAS have focused on case series of European ancestry, but studies of other populations show that some associations are observed across populations, and such associations point to pathways that may be particularly important in disease pathogenesis. Multiple ADs appear to have overlapping genetic associations and risk alleles, which suggested that common pathogenic mechanisms underpinning the diseases must be present (5,10-13). In addition, there is evidence that loci predisposing to one disease can have effects on the risk of a second disease (14) although the risk allele for one disease may not be the same for the second (15).

Each new genetic finding can suggest multiple hypotheses that need to be incorporated into an overall scheme of pathogenesis. Ongoing research points to some expected shared biology (16). However, the relative risk of each locus may differ between diseases. Before we can fully understand the relationships between ADs, we must first identify all risk loci for each disease, an effort which is still underway. Compelling and interesting observations have emerged implicating several genes with shared etiology that comprise the well-described examples for the major histocompatibility complex (MHC) (17) and non-MHC genes such as, PTPN22, which is associated with T1D, RA, SLE and AITD but not multiple sclerosis (MS) (18). Other examples include CTLA4, STAT4, TNFAIP3, and SH2B3, etc.

Many of the recently identified AD loci are involved in pathways related to B cell or T cell activation and differentiation, innate immunity, and regulation of cytokine signaling (7,19). This expected commonality has motivated several meta-analyses across pairs of diseases to establish their shared genetic basis. Approaches in such diseases as celiac disease (CD) and rheumatoid arthritis (RA) (20), T1D (14), and inflammatory bowel disease (IBD) (21) have revealed overlapping loci. However, these observations could potentially underestimate the actual extent of commonality as the lack of statistical power would inflate type 1 error for the associations found to genome-wide significance [i.e., 5x10-8]. In addition, modeling and simulation analyses estimate that, in several diseases where GWAS have been successful, further loci with low effect sizes remain to be discovered (22). This problem is exacerbated when considering independent discoveries across diseases since power would be multiplicative across studies. Therefore, estimates of the true extent of genetic sharing are probably underestimated by either simple overlaps or pairwise meta-analysis.

The main objective in genetic mapping studies is to identify the genetic variants and/or haplotypes affecting genetic susceptibility. Any associated marker in a locus may simply be genetically tagging the real causal variant, thus, statistical significance is not enough evidence to infer causality of variants. Another goal is to identify specific causal genes in regions when the associated region for a given trait encompasses multiple ADs. This requires additional refinement before inferences on genetic mechanisms and etiological causes of disease can be made (23). As an approach to be able to underpin these goals, part of the AD community developed shared resources, e.g., the ImmunoChip, a common platform for fine mapping AD-associated loci (24,25) as well as computational approaches to select the likeliest candidate genes from regions of association (26-28). Moreover, across the studied ADs, the application of a range of bioinformatics algorithms has generated plausible hypotheses about the causal genes and tissues underlying disease pathogenesis, motivated and functional experiments designed to test these hypotheses (29-31). In order to confront this critical aim of identifying pathways either shared across diseases or unique to specific ones, it is essential to develop network models for commonalities and to consider how genetic association data might be used to distinguish such models.

Currently, genomic technologies have been particularly attractive for acquiring, defining, and building network maps as they are amenable to automation. A limiting factor in annotating these networks is the careful acquisition of samples (i.e., rigorous standards in statistical experimental design, cell isolation, flow sorting, and sample preparation) required to gain cell-specific annotation. Parallel high-throughput gene expression studies are currently under way. Other types of information regarding the state of the DNA [e.g., DNase I hypersensitivity (32), nucleotide methylation status by sequencing (33), chromatin immunoprecipitation and sequencing (34), etc] are equally valuable and helpful are for capturing different types of information that could be used for deciphering the pathogenicity of the associated disease pathways.

Along with this extensive amount of information, the issue of interpretation comes into play. For example, several correlated alleles appear to confer risk of some diseases but are protective in others (15,35) and it remains unclear how this evidence should be incorporated into a pathway view of disease. Under a shared pathway architecture causal variants in each disease perturb a limited number of cellular processes. Thus pathway enrichment analysis (36,37) and functional genomics datasets can be queried to reveal pathway components that are preferentially encoded in associated loci. These approaches have shown that this cumulative burden hypothesis is true (28), which substantiates the argument that susceptibility alleles accumulate and perturb pathways to influence risk (38). These approaches can be expanded to incorporate genetic data from multiple diseases in much the same fashion (39).

Available genetic information points out that nearly half of the loci of an individual disease identified through GWAS have also been identified as influencing the risk of more than one additional disease. The argues for a genetic basis to co-morbidity. Moreover, there are examples of several variants with differing risk profiles depending on the disease. Support for the idea of common patterns of association and shared biological processes is obtained by loci clustered over a pattern of diseases, as they affect and harbor genes encoding for interacting proteins at a much higher rate than by chance. These results suggest that multi-phenotype mapping will identify the molecular mechanisms underlying co-morbid, immune-mediated inflammatory and autoimmune diseases.

Shared genetic factors

Extensive clinical and epidemiologic observations have shown that multiple ADs can occur in the same individual or in closely related family members. This clustering of multiple diseases appears more frequently than would be expected if the phenotypes were independent. Familial approaches have documented the clustering of certain ADs among the relatives of individuals who have RA, MS, SLE, T1D and other diseases (42-48) (see chapter 17).

The role of common variants versus rare variants in mediating susceptibility to common diseases has reemerged as a controversial topic (49,50). The controversy arises predominantly from the fact that the sum of the risk attributable to all of the loci identified can only account for a small fraction of the genetic heritability exhibited by many common diseases. This is often referred to as “missing heritability.” This has led to the possibility that rare variants with strong functional effects actually contribute significantly to the overall heritability of common diseases, which still needs to be validated and completely supported. In this regard, until recently rare variants were not regularly included in GWAS arrays, and several studies using re-sequencing of only the exons of each protein coding gene, called the exome, have identified a few rare mutations or copy number variations that contribute to the pathogenesis of ADs (51-57).

Recent reviews have summarized emerging work that identifies both genetic loci that are shared across the spectrum of ADs and the biological pathways whose involvement is implicated by these shared loci (3,19,51,58). The extent to which immune-related signaling and/or other pathways are implicated for each of these disorders varies and suggests that most of these pathways contribute or play a role to a variable degree in most of these disorders. The latter underscores the fact that most of these loci can be mapped to a few shared biological pathways.

Box Icon

Box 1

Genome wide association studies (GWAS).

Table 1 illustrates some of the susceptibility loci/alleles identified by genetic studies in ADs thus far, either by candidate gene and/or GWAS approaches. These associated loci have been organized on the functional role that their top positional candidate plays in the immune system. Although the adaptive immune system has long been a focus of attention, innate immune mechanisms are now viewed as main players in the pathogenesis of autoimmune-related disorders. Even further, the concept of quantitative thresholds for immune-cell signaling has emerged in the past decade as a potential way of understanding how multiple genetic factors of relatively small effect sizes may combine to create a state of susceptibility to autoimmune activation. The new genetic findings also emphasize that the identification of the environmental components that interact with host genetic factors will be critical in developing a deeper understanding of autoimmunity as well as new approaches to prevention, diagnosis, and treatment.

The immune system is in a constant struggle to maintain a balance between immunity (i.e., elimination of foreign pathogens) and tolerance (i.e., lack of response to self-tissue). When these regulatory immune response mechanisms fail, inflammatory destruction might occur. The following section describes evidence for genes associated with and between ADs (Table 1). Putative immune functions for each gene are given, and each is classified below into a few broad categories for clarity.

Genes modulating adaptive immunity

Variations in the properties of the antigen receptor pathways of T and B cells have long been postulated to be key elements in genetic predisposition to ADs. The activation of autoreactive T and B lymphocyte clones is the essence of autoimmunity. As shown in Table 1, several AD susceptibility genes that impact the adaptive immune system have been identified thus far. These susceptibility alleles are anticipated to modulate the development, activation, and regulation of a variety of immune cell lineages.

Genes impacting T cell activation and signaling

The differentiation of T cells into functional subsets is a major element in the diversification and regulation of adaptive immune responses. Defects in this process or imbalances between the populations have been linked to the development of ADs. The differentiation of naïve T cells into functional subsets is controlled by a variety of cell intrinsic (i.e., receptor specificity) and extrinsic (i.e., cytokines and cell–cell interactions) factors. The activation signals generated by the innate immune system significantly impact T cell differentiation and, as discussed above, variations in signals from the innate immune system can significantly impact T cell function. Additionally, T cell intrinsic molecular pathways that interpret signals from the innate immune system can also impact T cell differentiation.

PTPN22 (Protein tyrosine phosphatase, non-receptor type 22) encodes the protein tyrosine phosphatase, LYP, that functions as a negative regulator of T and B cell responses by dephosphorylating key downstream signaling molecules [e.g., lymphocyte-specific protein tyrosine kinase (LCK), protein-tyrosine kinase fyn (FYN) and ζ-chain (TCR)-associated protein kinase 70 kDa (ZAP70)] (59). A missense mutation at rs2476601 results in a change from arginine to tryptophan at position 620 (i.e., R620W). The functional consequences of this substitution appear to be a decreased ability to bind C-terminal Src tyrosine kinase, an important negative regulator of lymphocyte-specific protein tyrosine kinase (60,61). The consequences of this substitution are controversial, with decreased activation through both the BCR and TCR reported by some (62-64) and increased TCR signaling reported by others (65). The 620W allele has been associated with risk for SLE, T1D (60), and RA (61), whereas in IBD it is protective (66). In addition, there is evidence that this allele is not associated with other ADs, such as CD (67) and MS (18). Likewise, a rare missense substitution (R263Q) in PTPN22 was shown to reduce phosphatase activity and was associated with protection from SLE (68).

CTLA4 (cytotoxic T-lymphocyte-associated protein 4) is a key negative regulatory molecule that impacts antigen-driven activation of T cells. CTLA4 polymorphisms are reported to be associated with T1D (69), IBD (70), RA (71), CD (72), MS (73), and SLE (74). This gene maps to a region in strong LD with CD28 and ICOS, both of which also have important regulatory roles in adaptive immunity. A recent study reported the association of both genes with RA (75). However, the strong LD in the CD28/CTLA4/ICOS gene cluster makes it difficult to identify the true causal locus. In many respects, it is probably most accurate to interpret the association of SNPs from this LD block as representing the functional consequences of carrying a CD28/CTLA4/ICOS haplotype rather than focusing completely on one member of the cluster until more data becomes available to further dissect this association.

SH2B3 (SH2B adaptor protein 3), which encodes for the negative regulator of T cell receptor signaling, LNK (lymphocyte adaptor protein), harbors a non-synonymous variant, particularly associated with T1D (76) and CD (77) but also SLE. Mice genetically deficient for SH2B3 are hypersensitive to stimulation with multiple cytokines (78). SH2B3 also functions as a regulator of T cell signaling as overexpression of SH2B3 inhibits the activation of nuclear factor of activated T cells (NFAT) following TCR stimulation in vitro (79). Variants that affect SH2B3 function could, therefore, alter the signaling thresholds through many different receptors on cells of both the lymphoid and myeloid lineage. A non-synonymous SNP that leads to a R262W substitution in SH2B3 is associated with SLE, T1D, and CD (14,80) and occurs in the pleckstrin homology domain, which is known to be important for targeting the protein to the plasma membrane (14,81,82).

Similarly, TAGAP (a T cell activation GTPase-activating protein) is associated with CD (80), T1D (14), and RA (83). ICOSLG, which encodes a B7-related peptide involved in T cell activation and differentiation and binds to ICOS expressed on the surface of T cells, has been associated with IBD, CD, and T1D (84-86). All of these genes modulate antigen-driven T cell activation in a manner that potentiates susceptibility to multiple ADs.

CD226 is a type I transmembrane receptor of the immunoglobulin superfamily, mainly expressed on the surface of lymphocytes (87). CD226 induces protein kinase C (PKC) and Src family kinase Fyn upon binding to its ligands (88) and is involved in T cell activation and differentiation (89). A missense variant in the gene (Gly307Ser) is associated with T1D, MS, AITD, RA, Wegener’s granulomatosis, and SLE (82,90-93). The risk allele reduces the expression of CD226 in T and NK T cells (93).

The TNFSF4 [tumor necrosis factor (ligand) superfamily, member 4] binds to the surface of antigen-presenting cells by its receptor (TNFRSF4). TNFSF4-mediated signals inhibit IL-10-driven expression of regulatory T cell functions and in vitro production of IL-17 (94). Genetic variants in the promoter of TNFSF4 define a haplotype associated with SLE (95). In addition, the risk haplotype led to the increased expression of the TNFSF4 transcript as well as cell surface protein expression of TNFSF4 when compared to non-risk alleles in lymphoblastoid cell lines (96). Moreover, TNFSF4 and TNFRSF9 are involved in T cell activation and are implicated in CD (86).

Susceptibility genes impacting B cell activation

Human genetic diversity approaches have identified a variety of polymorphisms in genes potentially impacting B cell activation. Among these, BANK1 (B cell scaffold protein with ankyrin repeats 1) encodes a gene that is active in the transmission of BCR signaling. BANK1 promotes the protein tyrosine kinase (LYN)-mediated tyrosine phosphorylation of IP(3)R (inositol 1,4,5-trisphosphate receptor), thus affecting B cell receptor-induced calcium mobilization from intracellular calcium reservoirs (97). Potentially functional BANK1 variations are reported to be associated with SLE in Scandinavian (98), European, American, and Chinese populations (99-101).

Multiple members of the Src family of tyrosine kinases have polymorphisms associated with susceptibility to AD. LYN is associated with antigen receptor signaling in B cells and is associated with SLE (102,103). BLK (B lymphoid tyrosine kinase) encodes another Src family tyrosine kinase that also plays a role in B cell signal transduction. The variants rs2248932 and/or rs13277113 associate BLK with SLE (103,104), RA (105), ankylosing spondylitis (AS) (106), and scleroderma (SSc) (107). The risk allele of the SNP, rs13277113, is associated with low mRNA expression levels of BLK and high mRNA expression levels of FAM167A (104). Interestingly, BLK expression levels are downregulated by epigenetic factors like exposure to high amounts of interferon and infection with Epstein-Barr virus (108).

CD40 (CD40 molecule, TNF receptor superfamily member 5) plays a crucial role in the activation and differentiation of B lymphocytes. CD40 is associated with susceptibility to RA (109), MS, and IBD (110). KIF5A and PIP4K2C are in tight LD and are located on chr.12q13. PIP4K2C encodes a phosphatidylinositol-5-phosphate 4-kinase that is expressed in B cells and is predicted to be involved in phosphatidylinositol signaling. KIF5A encodes a member of the kinesin family with no obvious role in the immune system. The KIF5A/PIP4K2C LD block is a susceptibility locus for RA (109), T1D (11), and MS (111), although the functional mechanisms involved are unclear. ETS1 is a transcription factor in the ETS family that regulates differentiation of terminal B cells and Th17 cells (112). Distinct common variants within ETS1 have been associated with SLE and CD (86,113).

Finally, IL10 (interleukin-10) is an important immunoregulatory cytokine that downregulates the immune response by reducing T cell function and MHC Class II expression in antigen-presenting cells. IL-10 levels were found to be dysregulated in SLE patients (114). Specific variations in IL10 are inconsistently associated with SLE (115). However, this locus has been identified as a risk factor for IBD (116) and T1D (117).

Genes affecting Th1 and Th2 cells

The contribution of different subsets of T-helper cells to the pathogenesis of inflammatory diseases is the subject of much research and debate (118). CD4+ Th1 cells drive the cell-mediated immune responses that lead to tissue damage and particular IgG responses thought to play a role in many inflammatory diseases, whereas CD4+ Th2 cells drive the production of certain antibodies (i.e., IgE) that predominantly underlie allergic responses (119,120).

IL18RAP, STAT1-STAT4, STAT3, and IL12A impact the differentiation of Th1 and Th2 cells, and all have polymorphisms associated with ADs. rs917997 is correlated with alterations in expression of IL18RAP and is associated with susceptibility to IBD. Interestingly, the same SNP is associated with T1D, yet the same risk allele is protective for IBD (35). rs7574865 from STAT4 is associated with RA (121), SLE (103), T1D (122), and IBD (123). STAT1, which is adjacent to and in moderate LD with STAT4, is associated with MS (124) and SLE (125). Likewise, STAT3 is associated with IBD (126) and MS (127).

IL12B encodes the p40 subunit of the heterodimeric cytokines IL-12 and IL-23. IL-12 is composed of a bundle of four alpha helices. It is a heterodimeric cytokine encoded by two separate genes, IL-12A (p35) and IL-12B (p40). IL12B variants are associated with T1D (128), MS (129), psoriasis (PSO) (130), and IBD (131). IL-13 and IL-4 are located directly adjacent to each other in a common LD block. IL-13 is involved in Th2 effector functions and can inhibit Th17 differentiation, while IL-4 is critical for Th2 differentiation. An IL-13 promoter variant is associated with PSO, and the protective allele results in enhanced IL-13 expression in Th2 cells (132).

PRKCQ (protein kinase C, theta) is predominantly expressed in hematopoietic cells and is involved in TCR regulation (133). Mice deficient in PRKCQ show impaired differentiation of T-helper subsets, particularly in Th2- and Th17-mediated inflammatory responses (134). rs4750316 is located in an intergenic region on chr.10p15 proximal to PRKCQ and is associated with RA (135). On the other hand, rs947474, in the same gene is reported to be independently associated with T1D (136). CD58 and CD6 encode co-stimulatory molecules involved in T cell receptor signaling and differentiation. These molecules are associated with MS and RA (83).

Genes affecting Th17 cells

In recent years, the characterization of novel subsets of T-helper cells, most notably regulator T cells (Treg; see below) and Th17 cells, has led to a major paradigm shift in T cell biology, and these T-helper cell subsets have been shown to play an important role in the pathogenesis of ADs. Elevated IL-17 levels are reported in the serum of patients with active SLE (137), MS (138), and RA (139). Moreover, IL-17-producing T Cells are observed in inflammatory infiltrates of SLE, MS, and RA patients. In PSO, activated IFN-γ-producing T cells and IL-17 are detected in the skin and play an important role in disease pathogenesis. A key factor in the survival and expansion of Th17 cells is stimulation by IL-23 (140). A missense variant, rs11209026 (R381Q), in the receptor for IL-23 strongly associates with IBD (141), PSO (142), AS (143), and AITD (144). Lastly, IL-17-producing T cells express CCR6, which encodes a member of the G protein-coupled chemokine receptor family and has emerged as a predisposing genetic factor for IBD in a recent meta-analysis of GWAS (126). Similarly, a functionally disruptive 32bp indel in CCR5 associates with protection from T1D, RA, and CD (126). Polymorphisms in the CCR3 and CCR4 chemokine receptors are also associated with CD (86).

Genes affecting regulatory T cells (Treg cells)

Treg cells are involved in the maintenance of immunological tolerance and lymphoid homeostasis (145). Their deficiency can result from decreased production of the IL-2 (146). IL-2 is often absent in RA synovium (147), and severe autoimmunity develops in knockout mice deficient for IL-2, IL-2RA, and IL-2RB, presumably due to defective regulatory T cell production (148). Genetic variants within the LD block encompassing the KIAA1109/Tenr/IL-2/IL-21 genes have been associated with CD (149), T1D (82), RA (150), IBD (151), PSO (152), and SLE (153). Given the strong LD, it is difficult to define a true candidate gene; however, IL-2 and IL-21 appear to be the plausible casual genes based on their functions in adaptive immunity (154).

IL2RA variants are associated with RA (155), T1D (117) and MS (156), and IBD (157), presenting allelic heterogeneity among diseases. Likewise, IL2RB is associated with RA (158) and T1D (136). Finally, IL7RA variations mediate reduced splicing of the transmembrane domain, decreasing soluble forms of IL-7RA, and are associated with IBD (159) and MS (160). IL7RA along with IL7 and IL2, helps maintain a healthy T effector cell:Treg cell balance (161). All of these variations are postulated to modulate AD susceptibility through their impact on Treg cell differentiation and maintenance.

TNF receptor superfamily genes associated with ADs

GWAS approaches have led to the association of several TNF superfamily members with ADs. TNFSF15, expressed predominantly on endothelial cells, has been shown to be upregulated on macrophages and CD4+/CD8+ lymphocytes of the intestinal lamina propria of IBD patients (162), with a SNP haplotype associated with in multiple populations (163). TNFRSF14, another member of TNF-receptor superfamily, interacts with TRAF proteins (164) and may indirectly affect NF-kB-mediated inflammation. This gene is associated with RA and CD (165). Moreover, TNFRSF6B, encoding a decoy receptor that prevents FasL-induced apoptosis, is associated with IBD (85). Increases in TNFRSF6B protein are observed in IBD (166) and RA (167), suggesting an impact in susceptibility. TNFRSF1A harbors a variant leading to an amino acid substitution, R92Q, which has been identified as a susceptibility locus for MS that correlates strongly with episodic multi systemic inflammation (168,169).

TNFAIP3 encodes the protein A20, an ubiquitin-modifying protein that is strongly induced in cells following TNF stimulation. This molecule is an inhibitor of NF-kB and plays a key role in limiting the severity of inflammatory processes (170). Several TNFAIP3 variations are associated with RA, IBD, SLE, PSO, and CD (13,165,171). A recent meta-analysis confirmed the strongest association with severity of SLE (172,173).

Innate immunity genes

The innate immune system plays a crucial role in driving the activation of the immune response. Functions of the innate immune system include: (a) detection of infectious agents; (b) initiation of both local and systemic inflammatory responses by the production of cytokines; (c) attraction of effector cells into infected tissues via the production of chemokines; and (d) initiation of the adaptive immune response. There exists the possibility that exposure of a dysregulated innate immune system to environmental stimuli might initiate the development of autoimmune phenomena. Several studies have implicated viral or microbial infections with the initiation of ADs, although these studies are inconsistent (174). Studies in mice have established an important role for commensal gut flora in the development of arthritis (175) and IBD (176), and, more recently, in modulating susceptibility to T1D in the NOD mouse (177). The precise interactions involved are still unclear, although signaling through toll-like receptor (TLR) pathways appears to be crucial. Further analysis of the genes and molecular pathways within the innate immune system identified by GWAS studies may provide important insights into the events that trigger autoimmunity in genetically predisposed individuals.

The shared autoimmune loci in innate immunity are: TNIP1 [(associated with psoriasis (178)], IRF8 [(associated with MS (168) and SLE (179)], TYK2 [associated with MS (181) and T1D (182)] and TNFAIP3 discussed elsewhere in this chapter. A missense allele in IFIH1 is associated with risk for T1D (182), AITD (183), and SLE (115). IFIH1 (also called MDA5) is a cytoplasmic RNA sensor that promotes IFN-I production when activated by viruses. As the innate immune response to viral infection is hypothesized to play a role in the pathogenesis of multiple autoimmune diseases, the inappropriate activation of nucleic acid sensors such as TLRs and IFIH1 may contribute to a general predisposition towards autoimmunity (184). IFIH1 is associated with T1D, SLE, and AITD (56). A missense allele (R32Q) of CFB, an activator of the alternative complement pathway, is associated with protection from age-related macular degeneration (AMD) and SLE (185). MIF is an immunoregulatory cytokine that functions in both innate and adaptive immunity and is expressed by many immune cells such as monocytes, macrophages, and T and B lymphocytes. Polymorphisms in MIF have been associated with multiple autoimmune and inflammatory diseases [(reviewed in (186)].

Genes impacting the pathogen recognition receptor (PRR) pathways

The detection of microbial infections is predominantly mediated by the recognition of pathogen-associated molecular patterns (PAMPs) by the TLR and the NOD-like receptor (NLR) PRR families. Signaling through either the TLR or NLR pathways results in the secretion of pro-inflammatory cytokines such as IL-6, TNFα, IL1, and the Type I (interferon alpha/beta) and Type II (interferon gamma) interferons (IFN). Levels of these cytokines (and many others) are commonly increased in the active stages of ADs and are generally considered to play an important role in a variety of elements of disease pathogenesis.

Genetic polymorphisms throughout the TLR and NLR pathways are associated with susceptibility to ADs. Variations in TLR7/8, TLR4, and NOD2 are associated with ADs (85,86,187). Polymorphisms in TLR7/8 are associated with SLE. Genetic studies of IBD have associated a missense variant in TLR4 with early onset of disease (85). Multiple variations in the NOD2 gene are associated with susceptibility to IBD (85). Finally, multiple variants of the CLEC16A (C-type lectin domain family 16 member A) gene, which is predicted to play a role in sugar binding, are associated with T1D (188) and MS (189). All of these variations occur in PRR family receptors and presumably impact susceptibility to AID by modulating the ability of the innate immune system to identify environmental stimuli.

Innate system transcription factors associated with autoimmune susceptibility

Signaling through PRR pathways leads to the activation of multiple cellular functions and the secretion of a variety of cytokines and chemokines. These receptors are expressed in a variety of immune cell lineages, and the consequences of their signaling are dependent in part on the specific cells involved. The nine members of the interferon regulatory factor (IRF) family of transcription factors play crucial roles in mediating transcriptional activation following signaling through the TLR pathway. Genetic variations in IRF4, IRF5, IRF7, and IRF8 are associated with susceptibility to various ADs (179). IRF5 is strongly associated with SLE (190), RA (191), Sjögren’s syndrome (SS) (192), IBD (193), MS (194), and primary biliary cirrhosis (PBC) (195).

As noted above, interferon pathways mediate both autoimmunity and viral defense (196). Genetic associations exist that lead to the increased expression of IRF5 in SLE (197) and RA (155). IRF5 broadly regulates innate immune responses through toll-like receptors (198) and type 1 interferons.

NF-kB, a central regulator of immune responses and inflammation, is a key player in innate immune responses. Though variations in NF-kB have not been associated with ADs, a variety of NF-kB-interacting and regulatory molecules do affect susceptibility. c-Rel, involved in T and B Cell activation, is associated with CD (86) and RA (115). UBE2L3 (ubiquitin-conjugating enzyme E2L 3 isoform1) encodes a protein involved in ubiquitination, and its overexpression leads to quicker degradation of the NF-kB precursor and a diminished innate immune response. This gene is associated with SLE (199), CD (86), RA (155), and IBD (200).

Apoptosis/autophagy/immune-complex clearance

Further implicating a primary role for innate immunity, variants of autophagy genes (e.g., ATG16L1) that target intracellular components, including microbes, to lysosomes have also been associated with IBD (201). Another autophagy gene, LRRK2 (leucine-rich repeat kinase 2), has been identified as an IBD susceptibility locus (126). The associated variant (G2019S) is known to alter neurite length and autophagic vacuole size (202). GWAS reported an association between autophagy ATG5 (APG5 autophagy 5-like) gene and SLE. The associated SNP (rs6568431) lies in an intergenic region between PRDM1 (PR domain containing 1, also known as BLIMP1) and ATG5. Since both genes are viable candidate genes for modulating SLE, the causative gene for this disease association remains to be elucidated (103). MST1 encodes macrophage-stimulating protein (MSP) that regulates macrophage chemotaxis and activation and affects innate immune responses to several bacterial ligands. This gene is associated with IBD (203) along with AITD, RA, SLE, and T1D. Finally, CRP (pentraxin C-reactive protein) is a complement activator and an important innate immune modulator involved in the clearance of cellular debris and apoptotic bodies. Variants in the promoter of CRP have been associated with SLE and CRP levels in SLE patients (204).

Increases in the prevalence of IBD during the past century may well reflect corresponding changes in the composition of the intestinal microbiota resulting from changes in hygiene, such as eradication of intestinal parasites (205). However, the role of the intestinal microbiome is probably not limited to the intestinal immune system. Mouse models of autoimmune diabetes suggest that host differences in the capacity to sense intestinal microbes (177), and the specific composition of the intestinal microbiota modulate susceptibility to diabetes. The dynamic cross-talk between the host immune response and the intestinal microbiota will be an important focus of future research.

Rare variants associated with AD susceptibility

A current listing of rare alleles with a major effect on ADs obtained both in classic studies and more recently via targeted resequencing studies is provided in Table 1. Classic prototypes of rare alleles with major effects on autoimmunity are the deficiencies in components of the complement system. Deficiencies in C2, C4A, C4B, and C1q result in highly penetrant susceptibility to SLE (206). The mechanisms by which these deficiencies mediate a dramatic increase in AD susceptibility are unknown.

Copy number variations (CNV) have also been associated with strong relative risk effects in ADs. CNV of both C4 and FCGR3B, coding for FcγRIIIb, are associated with susceptibility to SLE (207). Other examples of CNV effects associated with AD susceptibility are the beta-defensins. These are small, secreted, antimicrobial peptides, that are encoded by DEFB genes, which show association between higher genomic copy number and the risk of PSO (53).

Next-generation sequencing technologies are currently being used to disentangle rare variants (i.e., frequency <1%). For this purpose, recent analyses in 480 T1D patients and 480 controls identified four rare variants in IFIH1 associated with the disease (56). Likewise, TREX1 encodes for a major 3’ - 5’ DNA exonuclease that may be responsible for a proofreading function during genome replication. TREX1 deficiency has been associated with Aicardi-Goutières syndrome (208), characterized by high type 1 IFN levels. Several rare variants are associated with SLE and SS. The precise mechanisms by which these deficiencies increase disease risk remain unknown.

Translational autoimmunity

Drastic advances on human “-omics” are giving rise to new possibilities in medicine and terms such as clinical bioinformatics (209) and translational bioinformatics (210). All these options lead to one common premise: ways of mining meaningful information from the vast amount of -omics data being generated. In this sense, application of comprehensive molecular information to clinical settings is been referred to as “genomic medicine” (211) with the ultimate goal to nurture, improve, and develop personalized medicine (PM) approaches. A genomic medicine approach will always require participation at a multidisciplinary research expertise level. These valuable advances will strengthen the overall approach to population and individual genetic susceptibility (212) and promise the ability to manage each patient as a biological individual. This will lead to changing paradigms and increasing efficiency and will foster a PM approach as an added plug-in capable of assisting in better prevention, detection, and classification of disease.

Last but not least, the protection of human participants, whether patients, unaffected family members, or unrelated population controls, has to be ensured. These individuals are the key component of genomic research, and their legal rights need to be protected if we wish to continue on with genomic science and to eventually apply genomic-based medicine for the good of humankind. More importantly, we shall not forget the sometimes understated premise that, “...we should not only be interested in the human genome but also in the human beings that carry it” (213).

References

1.
Jacobson DL, Gange SJ, Rose NR, Graham NM. Epidemiology and estimated population burden of selected autoimmune diseases in the United States. Clin Immunol Immunopathol. 1997;84:223–43. [PubMed: 9281381]
2.
Baranzini SE. The genetics of autoimmune diseases: a networked perspective. Curr Opin Immunol. 2009;21:596–605. [PubMed: 19896815]
3.
Zhernakova A, van Diemen CC, Wijmenga C. Detecting shared pathogenesis from the shared genetics of immune-related diseases. Nat Rev Genet. 2009;10:43–55. [PubMed: 19092835]
4.
Bias WB, Reveille JD, Beaty TH, Meyers DA, Arnett FC. Evidence that autoimmunity in man is a Mendelian dominant trait. Am J Hum Genet. 1986;39:584–602. [PMC free article: PMC1684061] [PubMed: 3098096]
5.
Wandstrat A, Wakeland E. The genetics of complex autoimmune diseases: non-MHC susceptibility genes. Nat Immunol. 2001;2:802–9. [PubMed: 11526390]
6.
Invernizzi P. Future directions in genetic for autoimmune diseases. J Autoimmun. 2009;33:1–2. Non-HLA genes and autoimmune diseases. Chapter 18 297. [PubMed: 19410428]
7.
Gregersen PK, Olsson LM. Recent advances in the genetics of autoimmune disease. Annu Rev Immunol. 2009;27:363–91. [PMC free article: PMC2992886] [PubMed: 19302045]
8.
Hindorff LA, Sethupathy P, Junkins HA, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106:9362–7. [PMC free article: PMC2687147] [PubMed: 19474294]
9.
Altshuler D, Daly M. Guilt beyond a reasonable doubt. Nat Genet. 2007;39:813–5. [PubMed: 17597768]
10.
nvernizzi P, Gershwin ME. The genetics of human autoimmune disease. J Autoimmun. 2009;33:290–9. [PubMed: 19682858]
11.
Fung EY, Smyth DJ, Howson JM, et al. Analysis of 17 autoimmune disease-associated variants in type 1 diabetes identifies 6q23/TNFAIP3 as a susceptibility locus. Genes Immun. 2009;10:188–91. [PubMed: 19110536]
12.
Remmers EF, Plenge RM, Lee AT, et al. STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus. N Engl J Med. 2007;357:977–86. [PMC free article: PMC2630215] [PubMed: 17804842]
13.
Plenge RM, Cotsapas C, Davies L, et al. Two independent alleles at 6q23 associated with risk of rheumatoid arthritis. Nat Genet. 2007;39:1477–82. [PMC free article: PMC2652744] [PubMed: 17982456]
14.
Smyth DJ, Plagnol V, Walker NM, et al. Shared and distinct genetic variants in type 1 diabetes and celiac disease. N Engl J Med. 2008;359:2767–77. [PMC free article: PMC2840835] [PubMed: 19073967]
15.
Sirota M, Schaub MA, Batzoglou S, Robinson WH, Butte AJ. Autoimmune disease classification by inverse association with SNP alleles. PLoS Genet. 2009;5:e1000792. [PMC free article: PMC2791168] [PubMed: 20041220]
16.
Eaton WW, Rose NR, Kalaydjian A, Pedersen MG, Mortensen PB. Epidemiology of autoimmune diseases in Denmark. J Autoimmun. 2007;29:1–9. [PMC free article: PMC2717015] [PubMed: 17582741]
17.
Fernando MM, Stevens CR, Walsh EC, et al. Defining the role of the MHC in autoimmunity: a review and pooled analysis. PLoS Genet. 2008;4:e1000024. [PMC free article: PMC2291482] [PubMed: 18437207]
18.
Criswell LA, Pfeiffer KA, Lum RF, et al. Analysis of families in the multiple autoimmune disease genetics consortium (MADGC) collection: the PTPN22 620W allele associates with multiple autoimmune phenotypes. Am J Hum Genet. 2005;76:561–71. [PMC free article: PMC1199294] [PubMed: 15719322]
19.
Rai E, Wakeland EK. Genetic predisposition to autoimmunity--what have we learned? Semin Immunol. 2011;23:67–83. [PubMed: 21288738]
20.
Zhernakova A, Stahl EA, Trynka G, et al. Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci. PLoS Genet. 2011;7:e1002004. [PMC free article: PMC3044685] [PubMed: 21383967]
21.
Festen EA, Goyette P, Green T, et al. A meta-analysis of genome-wide association scans identifies IL18RAP, PTPN2, TAGAP, and PUS10 as shared risk loci for Crohn’s disease and celiac disease. PLoS Genet. 2011;7:e1001283. [PMC free article: PMC3029251] [PubMed: 21298027]
22.
Stahl EA, Wegmann D, Trynka G, et al. Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis. Nat Genet. 2012;44:483–9. [PMC free article: PMC6560362] [PubMed: 22446960]
23.
Cantor RM, Lange K, Sinsheimer JS. Prioritizing GWAS results: A review of statistical methods and recommendations for their application. Am J Hum Genet. 2010;86:6–22. [PMC free article: PMC2801749] [PubMed: 20074509]
24.
Cortes A, Brown MA. Promise and pitfalls of the Immunochip. Arthritis Res Ther. 2011;13:101. [PMC free article: PMC3157635] [PubMed: 21345260]
25.
Trynka G, Hunt KA, Bockett NA, et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat Genet. 2011;43:1193–201. [PMC free article: PMC3242065] [PubMed: 22057235]
26.
Wang K, Li M, Bucan M. Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet. 2007;81:1278–83. [PMC free article: PMC2276352] [PubMed: 17966091]
27.
Raychaudhuri S, Plenge RM, Rossin EJ, et al. Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions. PLoS Genet. 2009;5:e1000534. [PMC free article: PMC2694358] [PubMed: 19557189]
28.
Rossin EJ, Lage K, Raychaudhuri S, et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet. 2011;7:e1001273. [PMC free article: PMC3020935] [PubMed: 21249183]
29.
Dendrou CA, Plagnol V, Fung E, et al. Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource. Nat Genet. 2009;41:1011–5. [PMC free article: PMC2749506] [PubMed: 19701192]
30.
Kofler DM, Severson CA, Mousissian N, De Jager PL, Hafler DA. The CD6 multiple sclerosis susceptibility allele is associated with alterations in CD4+ T cell proliferation. J Immunol. 2011;187:3286–91. [PubMed: 21849685]
31.
Xavier RJ, Huett A, Rioux JD. Autophagy as an important process in gut homeostasis and Crohn’s disease pathogenesis. Gut. 2008;57:717–20. [PMC free article: PMC2735854] [PubMed: 18272545]
32.
Hesselberth JR, Chen X, Zhang Z, et al. Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nat Methods. 2009;6:283–9. [PMC free article: PMC2668528] [PubMed: 19305407]
33.
Meissner A, Mikkelsen TS, Gu H, et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature. 2008;454:766–70. [PMC free article: PMC2896277] [PubMed: 18600261]
34.
Robertson G, Hirst M, Bainbridge M, et al. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods. 2007;4:651–7. [PubMed: 17558387]
35.
Wang K, Baldassano R, Zhang H, et al. Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects. Hum Mol Genet. 2010;19:2059–67. [PMC free article: PMC2860894] [PubMed: 20176734]
36.
Segrè AV, DIAGRAM Consortium; MAGIC investigators. et al. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 2010;6:pii:e1001058. [PMC free article: PMC2920848] [PubMed: 20714348]
37.
Eleftherohorinou H, Wright V, Hoggart C, et al. Pathway analysis of GWAS provides new insights into genetic susceptibility to 3 inflammatory diseases. PLoS One. 2009;4:e8068. [PMC free article: PMC2778995] [PubMed: 19956648]
38.
Cotsapas C, Hafler DA. Immune-mediated disease genetics: the shared basis of pathogenesis. Trends Immunol. 2013;34:22–6. [PubMed: 23031829]
39.
Cotsapas C, Voight BF, Rossin E, et al. Pervasive sharing of genetic effects in autoimmune disease. PLoS Genet. 2011;7:e1002254. [PMC free article: PMC3154137] [PubMed: 21852963]
40.
Raychaudhuri S. Recent advances in the genetics of rheumatoid arthritis. Curr Opin Rheumatol. 2010;22:109–18. [PMC free article: PMC3121048] [PubMed: 20075733]
41.
Manolio TA, Collins FS, Cox NJ, et al. Finding the missing heritability of complex diseases. Nature. 2009;461:747–53. [PMC free article: PMC2831613] [PubMed: 19812666]
42.
Barcellos LF, Kamdar BB, Ramsay PP, et al. Clustering of autoimmune diseases in families with a high-risk for multiple sclerosis: a descriptive study. Lancet Neurol. 2006;5:924–31. [PubMed: 17052659]
43.
Somers EC, Thomas SL, Smeeth L, Hall AJ. Autoimmune diseases co-occurring within individuals and within families: a systematic review. Epidemiology. 2006;17:202–17. [PubMed: 16477262]
44.
Michou L, Rat AC, Lasbleiz S, Bardin T, Cornélis F. Prevalence and distribution of autoimmune diseases in 368 rheumatoid arthritis families. J Rheumatol. 2008;35:790–6. [PubMed: 18381797]
45.
Alarcón-Segovia D, Alarcón-Riquelme ME, Cardiel MH, et al. Familial aggregation of systemic lupus erythematosus, rheumatoid arthritis, and other autoimmune diseases in 1,177 lupus patients from the GLADEL cohort. Arthritis Rheum. 2005;52:1138–47. [PubMed: 15818688]
46.
Anaya JM, Tobon GJ, Vega P, Castiblanco J. Autoimmune disease aggregation in families with primary Sjogren’s syndrome. J Rheumatol. 2006;33:2227–34. [PubMed: 17086607]
47.
Anaya JM, Castiblanco J, Tobón GJ, et al. Familial clustering of autoimmune diseases in patients with type 1 diabetes mellitus. J Autoimmun. 2006;26:208–14. [PubMed: 16503115]
48.
Prahalad S, Shear ES, Thompson SD, Giannini EH, Glass DN. Increased prevalence of familial autoimmunity in simplex and multiplex families with juvenile rheumatoid arthritis. Arthritis Rheum. 2002;46:1851–6. [PubMed: 12124869]
49.
Schork NJ, Murray SS, Frazer KA, Topol EJ. Common vs. rare allele hypotheses for complex diseases. Curr Opin Genet Dev. 2009;19:212–9. [PMC free article: PMC2914559] [PubMed: 19481926]
50.
Goldstein D.B. Common genetic variation and human traits. N Engl J Med. 2009;360:1696–8. [PubMed: 19369660]
51.
McKinney C, Merriman ME, Chapman PT, et al. Evidence for an influence of chemokine ligand 3-like 1 (CCL3L1) gene copy number on susceptibility to rheumatoid arthritis. Ann Rheum Dis. 2008;67:409–13. [PubMed: 17604289]
52.
Lee YH, Bae SC, Song GG. Association between the chemokine receptor 5 delta32 polymorphism and rheumatoid arthritis: a meta-analysis. Mod Rheumatol. 2013;23:304–10. [PubMed: 22638733]
53.
Hollox EJ, Huffmeier U, Zeeuwen PL, et al. Psoriasis is associated with increased beta-defensin genomic copy number. Nat Genet. 2008;40:23–5. [PMC free article: PMC2447885] [PubMed: 18059266]
54.
McCarroll SA, Huett A, Kuballa P, et al. Deletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn’s disease. Nat Genet. 2008;40:1107–12. [PMC free article: PMC2731799] [PubMed: 19165925]
55.
Glocker EO, Kotlarz D, Boztug K, et al. Inflammatory bowel disease and mutations affecting the interleukin-10 receptor. N Engl J Med. 2009;361:2033–45. [PMC free article: PMC2787406] [PubMed: 19890111]
56.
Nejentsev S, Walker N, Riches D, Egholm M, Todd JA. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science. 2009;324:387–9. [PMC free article: PMC2707798] [PubMed: 19264985]
57.
Lee-Kirsch MA, Gong M, Chowdhury D, et al. Mutations in the gene encoding the 3’-5’ DNA exonuclease TREX1 are associated with systemic lupus erythematosus. Nat Genet. 2007;39:1065–7. [PubMed: 17660818]
58.
Lettre G, Rioux JD. Autoimmune diseases: insights from genome-wide association studies. Hum Mol Genet. 2008;17:R116–21. [PMC free article: PMC2782355] [PubMed: 18852199]
59.
Cloutier JF, Veillette A. Association of inhibitory tyrosine protein kinase p50csk with protein tyrosine phosphatase PEP in T cells and other hemopoietic cells. EMBO J. 1996;15:4909–18. [PMC free article: PMC452228] [PubMed: 8890164]
60.
Bottini N, Musumeci L, Alonso A, et al. A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes. Nat Genet. 2004;36:337–8. [PubMed: 15004560]
61.
Begovich AB, Carlton VE, Honigberg LA, et al. A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis. Am J Hum Genet. 2004;75:330–7. Non-HLA genes and autoimmune diseases. Chapter 18 299. [PMC free article: PMC1216068] [PubMed: 15208781]
62.
Arechiga AF, Habib T, He Y, et al. Cutting edge: the PTPN22 allelic variant associated with autoimmunity impairs B cell signaling. J Immunol. 2009;182:3343–7. [PMC free article: PMC2797545] [PubMed: 19265110]
63.
Rieck M, Arechiga A, Onengut-Gumuscu S, Greenbaum C, Concannon P, Buckner JH. Genetic variation in PTPN22 corresponds to altered function of T and B lymphocytes. J Immunol. 2007;179:4704–10. [PubMed: 17878369]
64.
Vang T, Congia M, Macis MD, et al. Autoimmune-associated lymphoid tyrosine phosphatase is a gain-of-function variant. Nat Genet. 2005;37:1317–9. [PubMed: 16273109]
65.
Zikherman J, Hermiston M, Steiner D, Hasegawa K, Chan A, Weiss A. PTPN22 deficiency cooperates with the CD45 E613R allele to break tolerance on a non-autoimmune background. J Immunol. 2009;182:4093–106. [PMC free article: PMC2765978] [PubMed: 19299707]
66.
Velaga MR, Wilson V, Jennings CE, et al. The codon 620 tryptophan allele of the lymphoid tyrosine phosphatase (LYP) gene is a major determinant of Graves’ disease. J Clin Endocrinol Metab. 2004;89:5862–5. [PubMed: 15531553]
67.
Rueda B, Núñez C, Orozco G, et al. C1858T functional variant of PTPN22 gene is not associated with celiac disease genetic predisposition. Hum Immunol. 2005;66:848–52. [PubMed: 16112033]
68.
Orrú V, Tsai SJ, Rueda B, et al. A loss-of-function variant of PTPN22 is associated with reduced risk of systemic lupus erythematosus. Hum Mol Genet. 2009;18:569–79. [PMC free article: PMC2722189] [PubMed: 18981062]
69.
Howson JM, Walker NM, Smyth DJ, Todd JA. Type I Diabetes Genetics Consortium. Analysis of 19 genes for association with type I diabetes in the Type I Diabetes Genetics Consortium families. Genes Immun. 2009;10:S74–84. [PMC free article: PMC2810493] [PubMed: 19956106]
70.
Machida H, Tsukamoto K, Wen CY, et al. Association of polymorphic alleles of CTLA4 with inflammatory bowel disease in the Japanese. World J Gastroenterol. 2005;11:4188–93. [PMC free article: PMC4615440] [PubMed: 16015687]
71.
Plant D, Flynn E, Mbarek H, et al. Investigation of potential non-HLA rheumatoid arthritis susceptibility loci in a European cohort increases the evidence for nine markers. Ann Rheum Dis. 2010;69:1548–53. [PMC free article: PMC2938898] [PubMed: 20498205]
72.
Haimila K, Einarsdottir E, de Kauwe A, et al. The shared CTLA4-ICOS risk locus in celiac disease, IgA deficiency and common variable immunodeficiency. Genes Immun. 2009;10:151–61. [PubMed: 19020530]
73.
Yousefipour G, Erfani N, Momtahan M, Moghaddasi H, Ghaderi A. CTLA4 exon 1 and promoter polymorphisms in patients with multiple sclerosis. Acta Neurol Scand. 2009;120:424–9. [PubMed: 19737153]
74.
Gough SC, Walker LS, Sansom DM. CTLA4 gene polymorphism and autoimmunity. Immunol Rev. 2005;204:102–15. [PubMed: 15790353]
75.
Kim YO, Kim HJ, Kim SK, Chung JH, Hong SJ. Association of the CD28/CTLA4/ICOS polymorphisms with susceptibility to rheumatoid arthritis. Clin Chem Lab Med. 2010;48:345–53. [PubMed: 20113255]
76.
Cooper JD, Walker NM, Smyth DJ, et al. Follow-up of 1715 SNPs from the Wellcome Trust Case Control Consortium genome-wide association study in type I diabetes families. Genes Immun. 2009;10:S85–94. [PMC free article: PMC2805462] [PubMed: 19956107]
77.
Zhernakova A, Elbers CC, Ferwerda B, et al. Evolutionary and functional analysis of celiac risk loci reveals SH2B3 as a protective factor against bacterial infection. Am J Hum Genet. 2010;86:970–7. [PMC free article: PMC3032060] [PubMed: 20560212]
78.
Velazquez L, Cheng AM, Fleming HE, et al. Cytokine signaling and hematopoietic homeostasis are disrupted in Lnk-deficient mice. J Exp Med. 2002;195:1599–611. [PMC free article: PMC2193556] [PubMed: 12070287]
79.
Li Y, He X, Schembri-King J, Jakes S, Hayashi J. Cloning and characterization of human Lnk, an adaptor protein with pleckstrin homology and Src homology 2 domains that can inhibit T cell activation. J Immunol. 2000;164:5199–206. [PubMed: 10799879]
80.
Hunt KA, Zhernakova A, Turner G, et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat Genet. 2008;40:395–402. [PMC free article: PMC2673512] [PubMed: 18311140]
81.
van Heel DA, Franke L, Hunt KA, et al. A genome-wide association study for celiac disease identifies risk variants in the region harboring IL2 and IL21. Nat Genet. 2007;39:827–9. [PMC free article: PMC2274985] [PubMed: 17558408]
82.
Todd JA, Walker NM, Cooper JD, et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet. 2007;39:857–64. [PMC free article: PMC2492393] [PubMed: 17554260]
83.
Raychaudhuri S, Thomson BP, Remmers EF, et al. Genetic variants at CD28, PRDM1 and CD2/CD58 are associated with rheumatoid arthritis risk. Nat Genet. 2009;41:1313–8. [PMC free article: PMC3142887] [PubMed: 19898481]
84.
Todd J.A. Etiology of type 1 diabetes. Immunity. 2010;32:457–67. [PubMed: 20412756]
85.
Henderson P, van Limbergen JE, Wilson DC, Satsangi J, Russell RK. Genetics of childhood-onset inflammatory bowel disease. Inflamm Bowel Dis. 2011;17:346–61. [PubMed: 20839313]
86.
Dubois PC, Trynka G, Franke L, et al. Multiple common variants for celiac disease influencing immune gene expression. Nat Genet. 2010;42:295–302. [PMC free article: PMC2847618] [PubMed: 20190752]
87.
Bachelet I, Munitz A, Mankutad D, Levi-Schaffer F. Mast cell costimulation by CD226/CD112 (DNAM-1/Nectin-2): a novel interface in the allergic process. J Biol Chem. 2006;281:27190–6. [PubMed: 16831868]
88.
Bottino C, Castriconi R, Pende D, et al. Identification of PVR (CD155) and Nectin-2 (CD112) as cell surface ligands for the human DNAM-1 (CD226) activating molecule. J Exp Med. 2003;198:557–67. [PMC free article: PMC2194180] [PubMed: 12913096]
89.
Shibuya K, Shirakawa J, Kameyama T, et al. CD226 (DNAM-1) is involved in lymphocyte function-associated antigen 1 co-stimulatory signal for naive T cell differentiation and proliferation. J Exp Med. 2003;198:1829–39. [PMC free article: PMC2194159] [PubMed: 14676297]
90.
Wieczorek S, Hoffjan S, Chan A, et al. Novel association of the CD226 (DNAM-1) Gly307Ser polymorphism in Wegener’s granulomatosis and confirmation for multiple sclerosis in German patients. Genes Immun. 2009;10:591–5. [PubMed: 19536154]
91.
Qiu ZX, Zhang K, Qiu XS, Zhou M, Li WM. CD226 Gly307Ser association with multiple autoimmune diseases: a meta-analysis. Hum Immunol. 2013;74:249–55. [PubMed: 23073294]
92.
Hafler JP, Maier LM, Cooper JD, et al. CD226 Gly307Ser association with multiple autoimmune diseases. Genes Immun. 2009;10:5–10. [PMC free article: PMC2635550] [PubMed: 18971939]
93.
Löfgren SE, Delgado-Vega AM, Gallant CJ, et al. A 3’-untranslated region variant is associated with impaired expression of CD226 in T and natural killer T cells and is associated with susceptibility to systemic lupus erythematosus. Arthritis Rheum. 2010;62:3404–14. [PubMed: 20669283]
94.
Li J, Li L, Shang X, et al. Negative regulation of IL-17 production by OX40/OX40L interaction. Cell Immunol. 2008;253:31–7. [PubMed: 18501882]
95.
Delgado-Vega AM, Abelson AK, Sánchez E, et al. Replication of the TNFSF4 (OX40L) promoter region association with systemic lupus erythematosus. Genes Immun. 2009;10:248–53. [PMC free article: PMC3867640] [PubMed: 19092840]
96.
Cunninghame Graham DS, Graham RR, Manku H, et al. Polymorphism at the TNF superfamily gene TNFSF4 confers susceptibility to systemic lupus erythematosus. Nat Genet. 2008;40:83–9. [PMC free article: PMC3705866] [PubMed: 18059267]
97.
Yokoyama K, Su Ih IH, Tezuka T, et al. BANK regulates BCR-induced calcium mobilization by promoting tyrosine phosphorylation of IP(3) receptor. EMBO J. 2002;21:83–92. [PMC free article: PMC125810] [PubMed: 11782428]
98.
Kozyrev SV, Abelson AK, Wojcik J, et al. Functional variants in the B Cell gene BANK1 are associated with systemic lupus erythematosus. Nat Genet. 2008;40:211–6. [PubMed: 18204447]
99.
Suarez-Gestal M, Calaza M, Endreffy E, et al. Replication of recently identified systemic lupus erythematosus genetic associations: a case-control study. Arthritis Res Ther. 2009;11:R69. [PMC free article: PMC2714115] [PubMed: 19442287]
100.
Guo L, Deshmukh H, Lu R, et al. Replication of the BANK1 genetic association with systemic lupus erythematosus in a European-derived population. Genes Immun. 2009;10:531–8. [PMC free article: PMC2736873] [PubMed: 19339986]
101.
Zhang Z, Zhu KJ, Xu Q, et al. The association of the BLK gene with SLE was replicated in Chinese Han. Arch Dermatol Res. 2010;302:619–24. [PubMed: 20130895]
102.
Lu R, Vidal GS, Kelly JA, et al. Genetic associations of LYN with systemic lupus erythematosus. Genes Immun. 2009;10:397–403. [PMC free article: PMC2750001] [PubMed: 19369946]
103.
International Consortium for Systemic Lupus Erythematosus Genetics (SLEGEN). Harley JB, Alarcón-Riquelme ME, et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat Genet. 2008;40:204–10. [PMC free article: PMC3712260] [PubMed: 18204446]
104.
Hom G, Graham RR, Modrek B, et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J Med. 2008;358:900–9. [PubMed: 18204098]
105.
Ito I, Kawasaki A, Ito S, et al. Replication of association between FAM167A(C8orf13)-BLK region and rheumatoid arthritis in a Japanese population. Ann Rheum Dis. 2010;69:936–7. [PubMed: 19740902]
106.
Yin H, Borghi MO, Delgado-Vega AM, Tincani A, Meroni PL, Alarcón-Riquelme ME. Association of STAT4 and BLK, but not BANK1 or IRF5, with primary antiphospholipid syndrome. Arthritis Rheum. 2009;60:2468–71. [PubMed: 19644876]
107.
Ito I, Kawaguchi Y, Kawasaki A, et al. Association of the FAM167A-BLK region with systemic sclerosis. Arthritis Rheum. 2010;62:890–5. [PubMed: 20131239]
108.
Portis T, Dyck P, Longnecker R. Epstein-Barr Virus (EBV) LMP2A induces alterations in gene transcription similar to those observed in Reed-Sternberg cells of Hodgkin lymphoma. Blood. 2003;102:4166–78. [PubMed: 12907455]
109.
Raychaudhuri S, Remmers EF, Lee AT, et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat Genet. 2008;40:1216–23. [PMC free article: PMC2757650] [PubMed: 18794853]
110.
Blanco-Kelly F, Matesanz F, Alcina A, et al. CD40: novel association with Crohn’s disease and replication in multiple sclerosis susceptibility. PLoS One. 2010;5:e11520. [PMC free article: PMC2902513] [PubMed: 20634952]
111.
Cohen JE, Boitsova S, Itshayek E. Cerebral venous sinus thrombosis. Isr Med Assoc J. 2009;11:685–8. [PubMed: 20108557]
112.
Moisan J, Grenningloh R, Bettelli E, Oukka M, Ho IC. Ets-1 is a negative regulator of Th17 differentiation. J Exp Med. 2007;204:2825–35. [PMC free article: PMC2118518] [PubMed: 17967903]
113.
Yang W, Shen N, Ye DQ, et al. Genome-wide association study in Asian populations identifies variants in ETS1 and WDFY4 associated with systemic lupus erythematosus. PLoS Genet. 2010;6:e1000841. [PMC free article: PMC2820522] [PubMed: 20169177]
114.
López P, Gutiérrez C, Suárez A. IL-10 and TNFalpha genotypes in SLE. J Biomed Biotechnol. 2010;2010:838390. [PMC free article: PMC2896901] [PubMed: 20625422]
115.
Gateva V, Sandling JK, Hom G, et al. A large-scale replication study identifies TNIP1, PRDM1, JAZF1, UHRF1BP1 and IL10 as risk loci for systemic lupus erythematosus. Nat Genet. 2009;41:1228–33. [PMC free article: PMC2925843] [PubMed: 19838195]
116.
Franke A, Balschun T, Karlsen TH, et al. Sequence variants in IL10, ARPC2 and multiple other loci contribute to ulcerative colitis susceptibility. Nat Genet. 2008;40:1319–23. [PubMed: 18836448]
117.
Barrett JC, Clayton DG, Concannon P, et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet. 2009;41:703–7. [PMC free article: PMC2889014] [PubMed: 19430480]
118.
Steinman L. A brief history of T(H)17, the first major revision in the T(H)1/T(H)2 hypothesis of T cell-mediated tissue damage. Nat Med. 2007;13:139–45. [PubMed: 17290272]
119.
Mosmann TR, Cherwinski H, Bond MW, Giedlin MA, Coffman RL. Two types of murine helper T cell clone. I. Definition according to profiles of lymphokine activities and secreted proteins. J Immunol. 1986;136:2348–57. [PubMed: 2419430]
120.
Coffman RL, Carty J. A T cell activity that enhances polyclonal IgE production and its inhibition by interferon-gamma. J Immunol. 1986;136:949–54. [PubMed: 2934482]
121.
Lee HS, Remmers EF, Le JM, Kastner DL, Bae SC, Gregersen PK. Association of STAT4 with rheumatoid arthritis in the Korean population. Mol Med. 2007;13:55–60. [PMC free article: PMC2014726] [PubMed: 17932559]
122.
Lee HS, Park H, Yang S, Kim D, Park Y. STAT4 polymorphism is associated with early-onset type 1 diabetes, but not with late-onset type 1 diabetes. Ann N Y Acad Sci. 2008;1150:93–8. [PubMed: 19120275]
123.
Martínez A, Varadé J, Márquez A, et al. Association of the STAT4 gene with increased susceptibility for some immunemediated diseases. Arthritis Rheum. 2008;58:2598–602. [PubMed: 18759272]
124.
Fortunato G, Calcagno G, Bresciamorra V, et al. Multiple sclerosis and hepatitis C virus infection are associated with single nucleotide polymorphisms in interferon pathway genes. J Interferon Cytokine Res. 2008;28:141–52. [PubMed: 18338947]
125.
Kawasaki A, et al. Role of STAT4 polymorphisms in systemic lupus erythematosus in a Japanese population: a case-control association study of the STAT1-STAT4 region. Arthritis Res Ther. 2008;10(5):R113. [PMC free article: PMC2592800] [PubMed: 18803832]
126.
Barrett JC, Hansoul S, Nicolae DL, et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet. 2008;40:955–62. [PMC free article: PMC2574810] [PubMed: 18587394]
127.
Jakkula E, Leppä V, Sulonen AM, et al. Genome-wide association study in a high-risk isolate for multiple sclerosis reveals associated variants in STAT3 gene. Am J Hum Genet. 2010;86:285–91. [PMC free article: PMC2820168] [PubMed: 20159113]
128.
Yang JM, Nagasaka S, Yatagai T, et al. Interleukin-12p40 gene (IL-12B) polymorphism and Type 1 diabetes mellitus in Japanese: possible role in subjects without having high-risk HLA haplotypes. Diabetes Res Clin Pract. 2006;71:164–9. [PubMed: 16005098]
129.
Hall MA, McGlinn E, Coakley G, et al. Genetic polymorphism of IL-12 p40 gene in immune-mediated disease. Genes Immun. 2000;1:219–24. [PubMed: 11196715]
130.
Cargill M, Schrodi SJ, Chang M, et al. A large-scale genetic association study confirms IL12B and leads to the identification of IL23R as psoriasis-risk genes. Am J Hum Genet. 2007;80:273–90. [PMC free article: PMC1785338] [PubMed: 17236132]
131.
Brand S. Crohn’s disease: Th1, Th17 or both? The change of a paradigm: new immunological and genetic insights implicate Th17 cells in the pathogenesis of Crohn’s disease. Gut. 2009;58:1152–67. [PubMed: 19592695]
132.
Cameron L, Webster RB, Strempel JM, et al. Th2 cell-selective enhancement of human IL13 transcription by IL13-1112C>T, a polymorphism associated with allergic inflammation. J Immunol. 2006;177:8633–42. [PubMed: 17142763]
133.
von Essen M, Nielsen MW, Bonefeld CM, et al. Protein kinase C (PKC) alpha and PKC theta are the major PKC isotypes involved in TCR down-regulation. J Immunol. 2006;176:7502–10. [PubMed: 16751397]
134.
Tan SL, Zhao J, Bi C, et al. Resistance to experimental autoimmune encephalomyelitis and impaired IL-17 production in protein kinase C theta-deficient mice. J Immunol. 2006;176:2872–9. [PubMed: 16493044]
135.
Hinks A, Eyre S, Ke X, et al. Overlap of disease susceptibility loci for rheumatoid arthritis and juvenile idiopathic arthritis. Ann Rheum Dis. 2010;69:1049–53. [PMC free article: PMC2935325] [PubMed: 19674979]
136.
Cooper JD, Smyth DJ, Smiles AM, et al. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci. Nat Genet. 2008;40:1399–401. [PMC free article: PMC2635556] [PubMed: 18978792]
137.
Wang Y, Ito S, Chino Y, et al. Laser microdissection-based analysis of cytokine balance in the kidneys of patients with lupus nephritis. Clin Exp Immunol. 2010;159:1–10. [PMC free article: PMC2802690] [PubMed: 19807734]
138.
Montes M, Zhang X, Berthelot L, et al. Oligoclonal myelin-reactive T Cell infiltrates derived from multiple sclerosis lesions are enriched in Th17 cells. Clin Immunol. 2009;130:133–44. [PMC free article: PMC6961709] [PubMed: 18977698]
139.
Cope AP, Schulze-Koops H, Aringer M. The central role of T cells in rheumatoid arthritis. Clin Exp Rheumatol. 2007;25:S4–11. [PubMed: 17977483]
140.
Paradowska-Gorycka A, Grzybowska-Kowalczyk A, Wojtecka-Lukasik E, Maslinski S. IL-23 in the pathogenesis of rheumatoid arthritis. Scand J Immunol. 2010;71:134–45. [PubMed: 20415779]
141.
Dubinsky MC, Wang D, Picornell Y, et al. IL-23 receptor (IL-23R) gene protects against pediatric Crohn’s disease. Inflamm Bowel Dis. 2007;13:511–5. [PMC free article: PMC2169293] [PubMed: 17309073]
142.
Hüffmeier U, Lascorz J, Böhm B, et al. Genetic variants of the IL-23R pathway: association with psoriatic arthritis and psoriasis vulgaris, but no specific risk factor for arthritis. J Invest Dermatol. 2009;129:355–8. [PubMed: 18800148]
143.
Karaderi T, Harvey D, Farrar C, et al. Association between the interleukin 23 receptor and ankylosing spondylitis is confirmed by a new UK case-control study and meta-analysis of published series. Rheumatology (Oxford). 2009;48:386–9. [PubMed: 19189980]
144.
Ban Y, Tozaki T, Taniyama M, et al. Association studies of the IL-23R gene in autoimmune thyroid disease in the Japanese population. Autoimmunity. 2009;42:126–30. [PubMed: 19021011]
145.
Feuerer M, Hill JA, Mathis D, Benoist C. Foxp3+ regulatory T cells: differentiation, specification, subphenotypes. Nat Immunol. 2009;10:689–95. [PubMed: 19536194]
146.
Humrich JY, Morbach H, Undeutsch R, et al. Homeostatic imbalance of regulatory and effector T cells due to IL-2 deprivation amplifies murine lupus. Proc Natl Acad Sci U S A. 2010;107:204–9. [PMC free article: PMC2806746] [PubMed: 20018660]
147.
McInnes IB, Schett G. Cytokines in the pathogenesis of rheumatoid arthritis. Nat Rev Immunol. 2007;7:429–42. [PubMed: 17525752]
148.
Malek TR. The biology of interleukin-2. Annu Rev Immunol. 2008;26:453–79. Non-HLA genes and autoimmune diseases. Chapter 18 301. [PubMed: 18062768]
149.
Adamovic S, Amundsen SS, Lie BA, et al. Association study of IL2/IL21 and FcgRIIa: significant association with the IL2/IL21 region in Scandinavian coeliac disease families. Genes Immun. 2008;9:364–7. [PubMed: 18418394]
150.
Teixeira VH, Pierlot C, Migliorini P, et al. Testing for the association of the KIAA1109/Tenr/IL2/IL21 gene region with rheumatoid arthritis in a European family-based study. Arthritis Res Ther. 2009;11:R45. [PMC free article: PMC2688193] [PubMed: 19302705]
151.
Festen EA, Goyette P, Scott R, et al. Genetic variants in the region harbouring IL2/IL21 associated with ulcerative colitis. Gut. 2009;58:799–804. [PMC free article: PMC2757103] [PubMed: 19201773]
152.
Liu Y, Helms C, Liao W, et al. A genome-wide association study of psoriasis and psoriatic arthritis identifies new disease loci. PLoS Genet. 2008;4:e1000041. [PMC free article: PMC2274885] [PubMed: 18369459]
153.
Sawalha AH, Kaufman KM, Kelly JA, et al. Genetic association of interleukin-21 polymorphisms with systemic lupus erythematosus. Ann Rheum Dis. 2008;67:458–61. [PubMed: 17720724]
154.
Monteleone G, Pallone F, MacDonald TT. Interleukin-21: a critical regulator of the balance between effector and regulatory T Cell responses. Trends Immunol. 2008;29:290–4. [PubMed: 18440864]
155.
Stahl EA, Raychaudhuri S, Remmers EF, et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat Genet. 2010;42:508–14. [PMC free article: PMC4243840] [PubMed: 20453842]
156.
Maier LM, Lowe CE, Cooper J, et al. IL2RA genetic heterogeneity in multiple sclerosis and type 1 diabetes susceptibility and soluble interleukin-2 receptor production. PLoS Genet. 2009;5:e1000322. [PMC free article: PMC2602853] [PubMed: 19119414]
157.
Franke A, McGovern DP, Barrett JC, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet. 2010;42:1118–25. [PMC free article: PMC3299551] [PubMed: 21102463]
158.
Barton A, Thomson W, Ke X, et al. Rheumatoid arthritis susceptibility loci at chromosomes 10p15, 12q13 and 22q13. Nat Genet. 2008;40:1156–9. [PMC free article: PMC2662493] [PubMed: 18794857]
159.
Imielinski M, Baldassano RN, Griffiths A, et al. Common variants at five new loci associated with early-onset inflammatory bowel disease. Nat Genet. 2009;41:1335–40. [PMC free article: PMC3267927] [PubMed: 19915574]
160.
Zuvich RL, McCauley JL, Oksenberg JR, et al. Genetic variation in the IL7RA/IL7 pathway increases multiple sclerosis susceptibility. Hum Genet. 2010;127:525–35. [PMC free article: PMC2854871] [PubMed: 20112030]
161.
Tang Q, Adams JY, Penaranda C, et al. Central role of defective interleukin-2 production in the triggering of islet autoimmune destruction. Immunity. 2008;28:687–97. [PMC free article: PMC2394854] [PubMed: 18468463]
162.
Bamias G, Martin C 3rd, Marini M, et al. Expression, localization, and functional activity of TL1A, a novel Th1-polarizing cytokine in inflammatory bowel disease. J Immunol. 2003;171:4868–74. [PubMed: 14568967]
163.
Yamazaki K, McGovern D, Ragoussis J, et al. Single nucleotide polymorphisms in TNFSF15 confer susceptibility to Crohn’s disease. Hum Mol Genet. 2005;14:3499–506. [PubMed: 16221758]
164.
Marsters SA, Ayres TM, Skubatch M, Gray CL, Rothe M, Ashkenazi A. Herpesvirus entry mediator, a member of the tumor necrosis factor receptor (TNFR) family, interacts with members of the TNFR-associated factor family and activates the transcription factors NF-kappaB and AP-1. J Biol Chem. 1997;272:14029–32. [PubMed: 9162022]
165.
Coenen MJ, Trynka G, Heskamp S, et al. Common and different genetic background for rheumatoid arthritis and coeliac disease. Hum Mol Genet. 2009;18:4195–203. [PubMed: 19648290]
166.
Funke B, Autschbach F, Kim S, et al. Functional characterisation of decoy receptor 3 in Crohn’s disease. Gut. 2009;58:483–91. [PubMed: 19039087]
167.
Bamias G, Siakavellas SI, Stamatelopoulos KS, Chryssochoou E, Papamichael C, Sfikakis PP. Circulating levels of TNF-like cytokine 1A (TL1A) and its decoy receptor 3 (DcR3) in rheumatoid arthritis. Clin Immunol. 2008;129:249–55. [PubMed: 18757243]
168.
De Jager PL, Jia X, Wang J, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41:776–82. [PMC free article: PMC2757648] [PubMed: 19525953]
169.
Kümpfel T, Hoffmann LA, Rübsamen H, et al. Late-onset tumor necrosis factor receptor-associated periodic syndrome in multiple sclerosis patients carrying the TNFRSF1A R92Q mutation. Arthritis Rheum. 2007;56:2774–83. [PubMed: 17665448]
170.
Coornaert B, Carpentier I, Beyaert R. A20: central gatekeeper in inflammation and immunity. J Biol Chem. 2009;284:8217–21. [PMC free article: PMC2659177] [PubMed: 19008218]
171.
Graham RR, Cotsapas C, Davies L, et al. Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus. Nat Genet. 2008;40:1059–61. [PMC free article: PMC2772171] [PubMed: 19165918]
172.
Bates JS, Lessard CJ, Leon JM, et al. Meta-analysis and imputation identifies a 109 kb risk haplotype spanning TNFAIP3 associated with lupus nephritis and hematologic manifestations. Genes Immun. 2009;10:470–7. [PMC free article: PMC2714405] [PubMed: 19387456]
173.
Adrianto I, Wen F, Templeton A, et al. Association of a functional variant downstream of TNFAIP3 with systemic lupus erythematosus. Nat Genet. 2011;43:253–8. [PMC free article: PMC3103780] [PubMed: 21336280]
174.
Bach JF. The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med. 2002;347:911–20. [PubMed: 12239261]
175.
Wu HJ, Ivanov II, Darce J, et al. Gut-residing segmented filamentous bacteria drive autoimmune arthritis via T helper 17 cells. Immunity. 2010;32:815–27. [PMC free article: PMC2904693] [PubMed: 20620945]
176.
Macfarlane S, Steed H, Macfarlane GT. Intestinal bacteria and inflammatory bowel disease. Crit Rev Clin Lab Sci. 2009;46:25–54. [PubMed: 19107650]
177.
Wen L, Ley RE, Volchkov PY, et al. Innate immunity and intestinal microbiota in the development of Type 1 diabetes. Nature. 2008;455:1109–13. [PMC free article: PMC2574766] [PubMed: 18806780]
178.
Nair RP, Duffin KC, Helms C, et al. Genome-wide scan reveals association of psoriasis with IL-23 and NF-kappaB pathways. Nat Genet. 2009;41:199–204. [PMC free article: PMC2745122] [PubMed: 19169254]
179.
Lessard CJ, Adrianto I, Ice JA, et al. Identification of IRF8, TMEM39A, and IKZF3-ZPBP2 as susceptibility loci for systemic lupus erythematosus in a large-scale multiracial replication study. Am J Hum Genet. 2012;90:648–60. [PMC free article: PMC3322228] [PubMed: 22464253]
180.
Ban M, Goris A, Lorentzen AR, et al. Replication analysis identifies TYK2 as a multiple sclerosis susceptibility factor. Eur J Hum Genet. 2009;17:1309–13. [PMC free article: PMC2782567] [PubMed: 19293837]
181.
Wallace C, Smyth DJ, Maisuria-Armer M, Walker NM, Todd JA, Clayton DG. The imprinted DLK1-MEG3 gene region on chromosome 14q32.2 alters susceptibility to type 1 diabetes. Nat Genet. 2010;42:68–71. [PMC free article: PMC2820243] [PubMed: 19966805]
182.
Smyth DJ, Cooper JD, Bailey R, et al. A genome-wide association study of nonsynonymous SNPs identifies a type 1 diabetes locus in the interferon-induced helicase (IFIH1) region. Nat Genet. 2006;38:617–9. [PubMed: 16699517]
183.
Sutherland A, Davies J, Owen CJ, et al. Genomic polymorphism at the interferon-induced helicase (IFIH1) locus contributes to Graves’ disease susceptibility. J Clin Endocrinol Metab. 2007;92:3338–41. [PMC free article: PMC6952273] [PubMed: 17535987]
184.
Andrejeva J, Childs KS, Young DF, et al. The V proteins of paramyxoviruses bind the IFN-inducible RNA helicase, mda-5, and inhibit its activation of the IFN-beta promoter. Proc Natl Acad Sci U S A. 2004;101:17264–9. [PMC free article: PMC535396] [PubMed: 15563593]
185.
Lokki ML, Koskimies SA. Allelic differences in hemolytic activity and protein concentration of BF molecules are found in association with particular HLA haplotypes. Immunogenetics. 1991;34:242–6. [PubMed: 1916952]
186.
Renner P, Roger T, Calandra T. Macrophage migration inhibitory factor: gene polymorphisms and susceptibility to inflammatory diseases. Clin Infect Dis. 2005;41:S513–9. [PubMed: 16237655]
187.
Shen N, Fu Q, Deng Y, et al. Sex-specific association of X-linked Toll-like receptor 7 (TLR7) with male systemic lupus erythematosus. Proc Natl Acad Sci U S A. 2010;107:15838–43. [PMC free article: PMC2936646] [PubMed: 20733074]
188.
Wu X, Zhu X, Wang X, et al. Intron polymorphism in the KIAA0350 gene is reproducibly associated with susceptibility to type 1 diabetes (T1D) in the Han Chinese population. Clin Endocrinol (Oxf). 2009;71:46–9. [PubMed: 19178520]
189.
Hoppenbrouwers IA, Aulchenko YS, Janssens AC, et al. Replication of CD58 and CLEC16A as genome-wide significant risk genes for multiple sclerosis. J Hum Genet. 2009;54:676–80. [PubMed: 19834503]
190.
Graham RR, Kozyrev SV, Baechler EC, et al. A common haplotype of interferon regulatory factor 5 (IRF5) regulates splicing and expression and is associated with increased risk of systemic lupus erythematosus. Nat Genet. 2006;38:550–5. [PubMed: 16642019]
191.
Sigurdsson S, Padyukov L, Kurreeman FA, et al. Association of a haplotype in the promoter region of the interferon regulatory factor 5 gene with rheumatoid arthritis. Arthritis Rheum. 2007;56:2202–10. [PubMed: 17599733]
192.
Miceli-Richard C, Comets E, Loiseau P, Puechal X, Hachulla E, Mariette X. Association of an IRF5 gene functional polymorphism with Sjogren’s syndrome. Arthritis Rheum. 2007;56:3989–94. [PMC free article: PMC3184606] [PubMed: 18050197]
193.
Dideberg V, Kristjansdottir G, Milani L, et al. An insertion-deletion polymorphism in the interferon regulatory Factor 5 (IRF5) gene confers risk of inflammatory bowel diseases. Hum Mol Genet. 2007;16:3008–16. [PubMed: 17881657]
194.
Kristjansdottir G, Sandling JK, Bonetti A, et al. Interferon regulatory factor 5 (IRF5) gene variants are associated with multiple sclerosis in three distinct populations. J Med Genet. 2008;45:362–9. [PMC free article: PMC2564860] [PubMed: 18285424]
195.
Liu X, Invernizzi P, Lu Y, et al. Genome-wide meta-analyses identify three loci associated with primary biliary cirrhosis. Nat Genet. 2010;42:658–60. [PMC free article: PMC3150510] [PubMed: 20639880]
196.
Hall JC, Rosen A. Type I interferons: crucial participants in disease amplification in autoimmunity. Nat Rev Rheumatol. 2010;6:40–9. [PMC free article: PMC3622245] [PubMed: 20046205]
197.
Graham RR, Kyogoku C, Sigurdsson S, et al. Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus. Proc Natl Acad Sci U S A. 2007;104:6758–63. [PMC free article: PMC1847749] [PubMed: 17412832]
198.
Takaoka A, Yanai H, Kondo S, et al. Integral role of IRF-5 in the gene induction programme activated by Toll-like receptors. Nature. 2005;434:243–9. [PubMed: 15665823]
199.
Han JW, Zheng HF, Cui Y, et al. Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nat Genet. 2009;41:1234–7. [PubMed: 19838193]
200.
Fransen K, Visschedijk MC, van Sommeren S, et al. Analysis of SNPs with an effect on gene expression identifies UBE2L3 and BCL3 as potential new risk genes for Crohn’s disease. Hum Mol Genet. 2010;19:3482–8. [PubMed: 20601676]
201.
Abraham C, Cho JH. Inflammatory bowel disease. N Engl J Med. 2009;361:2066–78. [PMC free article: PMC3491806] [PubMed: 19923578]
202.
Plowey ED, Cherra SJ 3rd, Liu YJ, Chu CT. Role of autophagy in G2019S-LRRK2-associated neurite shortening in differentiated SH-SY5Y cells. J Neurochem. 2008;105:1048–56. [PMC free article: PMC2361385] [PubMed: 18182054]
203.
Goyette P, Lefebvre C, Ng A, et al. Gene-centric association mapping of chromosome 3p implicates MST1 in IBD pathogenesis. Mucosal Immunol. 2008;1:131–8. [PMC free article: PMC4550306] [PubMed: 19079170]
204.
Edberg JC, Wu J, Langefeld CD, et al. Genetic variation in the CRP promoter: association with systemic lupus erythematosus. Hum Mol Genet. 2008;17:1147–55. [PubMed: 18182444]
205.
Guarner F, Bourdet-Sicard R, Brandtzaeg P, et al. Mechanisms of disease: the hygiene hypothesis revisited. Nat Clin Pract Gastroenterol Hepatol. 2006;3:275–84. [PubMed: 16673007]
206.
Walport MJ. Complement and systemic lupus erythematosus. Arthritis Res. 2002;4:S279–93. [PMC free article: PMC3240161] [PubMed: 12110148]
207.
Niederer HA, Willcocks LC, Rayner TF, et al. Copy number, linkage disequilibrium and disease association in the FCGR locus. Hum Mol Genet. 2010;19:3282–94. [PMC free article: PMC2908468] [PubMed: 20508037]
208.
Crow YJ, Hayward BE, Parmar R, et al. Mutations in the gene encoding the 3’-5’ DNA exonuclease TREX1 cause Aicardi-Goutieres syndrome at the AGS1 locus. Nat Genet. 2006;38:917–20. [PubMed: 16845398]
209.
Knaup P, Ammenwerth E, Brandner R, et al. Towards clinical bioinformatics: advancing genomic medicine with informatics methods and tools. Methods Inf Med. 2004;43:302–7. [PubMed: 15227561]
210.
Kann MG. Advances in translational bioinformatics: computational approaches for the hunting of disease genes. Brief Bioinform. 2010;11:96–110. [PMC free article: PMC2810112] [PubMed: 20007728]
211.
Feero WG, Guttmacher AE, Collins FS. Genomic medicine an updated primer. N Engl J Med. 2010;362:2001–11. [PubMed: 20505179]
212.
Guttmacher AE, Collins FS. Welcome to the genomic era. N Engl J Med. 2003;349:996–8. [PubMed: 12954750]
213.
Bernal JE. Human diversity in Colombia. Science. 1995;267:774. [PubMed: 7846516]
214.
Lessard CJ, Adrianto I, Kelly JA, et al. Identification of a systemic lupus erythematosus susceptibility locus at 11p13 between PDHX and CD44 in a multiethnic study. Am J Hum Genet. 2011;88:83–91. [PMC free article: PMC3014359] [PubMed: 21194677]
© 2013 Universidad del Rosario.
Bookshelf ID: NBK459446
Contents

Views

  • PubReader
  • Print View
  • Cite this Page
  • PDF version of this title (39M)

In this Page

Related information

  • PMC
    PubMed Central citations
  • PubMed
    Links to PubMed

Recent Activity

ClearTurn OffTurn On

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...