Alleles of HLA class II genes DQB1, DQA1, and DRB1 in the MHC region are major determinants of genetic predisposition to type 1 diabetes (T1D). Several alleles of each of these three loci are associated with susceptibility or protection from disease. In addition, relative risks for some DR-DQ genotypes are not simply the sum or product of the single haplotype relative risks. For example, the risk of the DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotype is often found to be higher than for the individual DRB1*03-DQB1*02 and DRB1*0401-DQB1*0302 homozygous genotypes. It has been hypothesized that this synergy or epistasis occurs through formation of highly susceptible trans-encoded HLA-DQ(α1, β1) heterodimers. Here, we evaluated this hypothesis by estimating the disease associations of the range of DR-DQ genotypes and their inferred dimers in a large collection of nuclear families. We determined whether the risk of haplotypes in DRB1*0401-DQB1*0302-positive genotypes relative to the DRB1*03-DQB1*02-positive genotypes is different from that of DRB1*01-DQB1*0501, which we used as a baseline reference. Several haplotypes showed a different risk compared to DRB1*01-DQB1*0501, which correlated with their ability to form certain trans-encoded DQ dimers. This result provides new evidence for the potential importance of trans-encoded HLA DQ molecules in the determination of HLA-associated risk in T1D.
The association between genes in the class II region of the HLA complex on chromosome 6p (IDDM1) and type 1 diabetes (T1D), first described in 1974, is one of the most extensively studied genetic susceptibility factors for a complex disease.1, 2, 3, 4 A large number of publications have established that particular combinations of alleles at HLA-DQB1, -DQA1, and -DRB1 show strong association with T1D.5, 6, 7, 8, 9, 10, 11, 12 The complex nature of this association is partly caused by the presence of multiple susceptible and protective HLA class II haplotypes, and may be modified by the presence of multiple other loci in the MHC region.13, 14
The haplotypes DRB1*0401-DQA1*0301-DQB1*0302 and DRB1*0301-DQA1*0501-DQB1*0201 have been found to be the major susceptible haplotypes in most populations, whereas DRB1*1501-DQA1*0102-DQB1* 0602 has been described to be protective in a dominant manner.2 Many previous studies have measured the disease risk of DR-DQ haplo- and genotypes by odds ratios (ORs) and have categorized the haplo- or genotypes in terms of susceptibility, neutrality, and protection.2, 6, 7, 10, 11 Inferences have also been made concerning the strength of susceptibility or protection, for example, DRB1*04 subtypes have been shown to display different ORs on an identical DQA1*0301-DQB1*0302 haplotype, with ranking 0405>0401>0404>0403>0406–8.2, 4, 15 However, the presence of multiple disease-associated haplotypes complicates the analysis of the DR-DQ loci. Most of the studies cited above use ORs to evaluate the risk of haplotypes or genotypes. Several authors have recognized that the OR of one haplotype can be influenced by the risk associated with the other haplotype present in an individual, for example, ORs of neutral factors can be significantly decreased due to the increased frequency of a strong susceptibility factor.2 To address this problem, several other measures have been proposed, like attributable risk and relative predispositional effect.16, 17 However, these measures only partly solve the problem. Here, relative risks are estimated relative to a baseline reference haplo- or genotype, which alleviates the above problem. Furthermore, we estimate the risk conferred by one DR-DQ haplotype or genotype by family-based logistic regression conditional on parental genotypes, which circumvents assumption of Hardy–Weinberg (HW) equilibrium and random mating in the general population.18, 19 Finally, this family-based approach and conditioning on parental genotypes avoids inaccurate risk estimation due to population admixture effects or ascertainment on multiple affected siblings, which can affect case–control and family-based AFBAC designs.20
It is evident that the risks of HLA genotypes are not simply the sum or product of the single haplotype relative risks. Apart from their incomplete disease penetrance, the risk of the DRB1*03-DQB1*02/DRB1* 0401-DQB1*0302 heterozygote genotype was found to be increased compared to that of the individual DRB1*03-DQB1*02 and DRB1*0401-DQB1*0302 homozygous genotypes, indicating an epistatic or synergistic effect.4, 21 Other genotype effects have been found for DRB1*08-DQB1*0402 (increased risk when together with DRB1*0401-DQB1*0302) and DRB1*09-DQB1*0303 (increased risk mainly with DRB1*03-DQB1*02),6, 22, 23 occurring fairly consistently across several ethnic groups.4 It has been postulated that the unexpected increase in risk of these genotypes is caused by highly susceptible trans-encoded DQ(α1, β1) heterodimers as formed in the DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotype.4, 24 The DQ molecule is an important antigen-presenting molecule for CD4-positive T cells, and consists of a DQ(α1, β1) heterodimer for which the DQβ1 and DQα1 chains are encoded by the DQB1 and DQA1 genes, respectively. Both cis- and trans-heterodimer molecules are expressed in class II heterozygous individuals, for example, in the high-risk DRB1*03-DQB1*02/DRB1* 0401-DQB1*0302 heterozygotes.25 To explain the genotype effect found for DRB1*03-DQB1*02/DRB1*0401-DQB1*0302, the trans-encoded dimers, namely DQ(α1* 0501, β1*0302) and DQ(α1*0301, β1*0201), have been proposed to confer higher risk than the cis dimers, DQ(α1*0301, β1*0302) and DQ(α1*0501, β1*0201). It has been postulated that similar molecules are formed in trans in DRB1*0401-DQB1*0302/DRB1*08-DQB1*0402 (DQ(α1*0401, β1*0302)-positive individuals, with α1*0401 being structurally similar to α1*0501, and for DRB1*03-DQB1*02/DRB1*09-DQB1*0303 (DQ(α1* 0301, β1*0201)) genotypes,4, 24 supporting the hypothesis that these trans-encoded molecules confer high risk.
The aim of this study was to estimate the relative risk (RR) for disease for HLA class II haplo- and genotypes and determine whether genotype effects indicative of trans effects are present for genotypes other than those previously described. The results indicate that DQ trans dimer formation could be an important factor in the association of HLA with T1D.
Haplotype risks in separate populations
Populations were first analysed separately and DRB1-DQB1 haplotype ORs were found comparable in different populations (Table 1). Only haplotypes with counts larger than 10 were analysed. No genotype analysis in separate populations was performed, since the result is unreliable because of limited number of observations. Differences between populations in magnitude and rank of haplotype risk were observed, although the main features of the HLA class II associations were maintained: DRB1*04-DQB1*0302 haplotypes were universally the most potent source of susceptibility except for those with the DRB1*0403 allele, and equally significant disease protection compared to DRB1*01-DQB1*05 haplotypes by the common DRB1*11-DQB1* 0301 and DRB1*15-DQB1*06 haplotypes.
Table 2 shows the DRB1-DQB1 haplotype RRs for the populations combined. Overall, this analysis confirms susceptible and protective haplotypes reported in many previous studies, with major high-risk haplotypes DRB1* 03-DQB1*02, DRB1*0401-DQB1*0302, and protective haplotypes DRB1*11-DQB1*0301, DRB1*14-DQB1*05, DRB1*07-DQB1*09, DRB1*0407-DQB1*0301, and DRB1*15-DQB1*06 (Table 2). The DRB1*04-DQB1*0302 subtypes were ranked from most to least susceptible: *0401≥*0405>*0404∼*0402>*0403.
The number of observations for each individual data set was too small to estimate genotype risks. We, therefore, used conditional extended transmission disequilibrium test (CETDT) to avoid the problem of inaccurate risk estimation due to population admixture or ascertainment bias and combined the data from the different populations to calculate genotype OR estimates (relative transmission probability (RTP) and OR-r), relative to the reference DRB1*01-DQB1*05/DRB1*01-DQB1*05 genotype (Table 3). This reference genotype was chosen as it represents the most frequent and relatively ‘neutral’ genotype. No major differences were observed when a different reference was chosen (not shown). As expected, the DRB1*0401-DQB1*0302/DRB1*03-DQB1*02 genotype shows the highest RTP (RTP=33), which was significantly different from the DRB1*0401-DQB1*0302 homozygous (RTP=26.6) and the DRB1*03-DQB1*02/DRB1* 03-DQB1*02 genotype (RTP=8.1) (P=1 × 10−5 and 1.4 × 10−5, respectively) (Table 3). This observation confirms the epistatic synergy between DRB1*0401-DQB1*0302 and DRB1*03-DQB1*02 haplotypes. Significant susceptibility was also found for DRB1*0401-DQB1*0302/DRB1*08-DQB1*04 (RTP=17.4), DRB1* 0401-DQB1*0302/DRB1*01-DQB1*05 (RTP=8.8), DRB1* 0401-DQB1*0302/DRB1*13-DQB1*06 (RTP=8.1), DRB1* 0401-DQB1*0302/DRB1*07-DQB1*02 (RTP=6.1), and DRB1*0401-DQB1*0302/DRB1*0401-DQB1*0301 (RTP=5.2).
The main question investigated here was whether synergy between haplotypes in terms of the ability to form disease susceptible trans-encoded DQ dimers can be observed in genotypes other than DRB1*0301-DQB1*0201/DRB1*0401-DQB1*0302. The DRB1*01-DQB1*0501 haplotype-encoded DQ β1 and α1 chains cannot form trans dimers with the DQ β1 and α1 chains from the DRB1*0401-DQB1*0302 or DRB1*03-DQB1*02 haplotypes22 and, therefore, the difference in risk of the DRB1*0401-DQB1*0302/DRB1*01-DQB1*0501 genotype (RTP=8.8) compared to the DRB1*03-DQB1*02/DRB1*01-DQB1*0501 genotype (RTP=2.5) can be taken as the ‘neutral’ reference for the difference in risk between DRB1*0401-DQB1*0302 and DRB1*03-DQB1*02 haplotypes. Our observation that an approximate three-fold difference in risk exists between the DRB1*0401-DQB1*0302 and DRB1*03-DQB1*02 homozygous genotypes (RTP=26.6 vs RTP=8.1, respectively, see Table 3), and a similar three-fold difference in risk exists between the DRB1*0401-DQB1*0302/DRB1*01-DQB1*0501 and DRB1*03-DQB1*02/DRB1*01-DQB1*0501 genotypes (RTP=26.6 vs RTP=8.1, respectively, see Table 3) is consistent with this assumption. We, therefore, compared the diff-erence in risk of haplotypes in a DRB1*0401-DQB1* 0302-positive genotype relative to the DRB1*03-DQB1* 02-positive genotype with the difference in risk of DRB1* 01-DQB1*05/DRB1*0401-DQB1*0302 vs the DRB1*01-DQB1*05/DRB1*03-DQB1*02 genotype (Table 4).
The haplotypes DRB1*11-DQA1*0501-DQB1*0301, DRB1*07-DQA1*0201-DQB1*0202, and DRB1*08-DQA1*0401-DQB1*0402 showed higher increased risk in DRB1*0401-DQB1*0302-positive genotypes than in DRB1*03-DQB1*02-positive genotypes compared to the reference DRB1*01-DQB1*05 haplotype. These haplotypes can potentially form putative high-risk trans-encoded DQ dimers in a DRB1*0401-DQB1*0302-positive genotype, DQ(α1*0501, β1*0302), DQ(α1*0301, β1*02), and DQ(α1*0401, β1*0302), respectively. Note that the DQ(α1*0401) molecule, encoded by the DRB1*08-DQA1*0401-DQB1*0402 haplotype, is structurally very similar to the DQ(α1*0501) molecule. In contrast, DRB1*0401-DQB1*0301 and DRB1*09-DQB1*0303 haplotypes can form the DQ(α1*0301, β1*02) trans-encoded dimer in DRB1*03-DQB1*02-positive genotypes, but not in DRB1*0401-DQB1*0302-positive genotypes (Table 4). This can explain why the increase in risk of DRB1*0401-DQB1*0301 and DRB1*09-DQB1*0303 haplotypes in a DRB1*0401-DQB1*0302- compared to DRB1*03-DQB1* 02-positive genotype is even lower than that of DRB1*01-DQB1*0501, suggesting interaction of these haplotypes with DRB1*03-DQB1*02.
In this large data set analysed using a statistical approach resistant to population admixture effects, ascertainment bias and the complexity due to the multiplicity of both predisposing and protective alleles at the HLA class II loci, we confirm that the DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotype is significantly more associated with T1D than DRB1*0401-DQB1*0302/DRB1*0401-DQB1*0302 and DRB1*03-DQB1*02/DRB1*03-DQB1*02 genotypes. Furthermore, evidence is provided for synergy between either DRB1*0401-DQB1*0302 or DRB1*03 -DQB1*02 and two previously implicated haplotypes (DRB1*08-DQA1*0401-DQB1*04 and DRB1*09-DQA1* 0301-DQB1*0303), and for three new haplotypes (DRB1* 11-DQA1*0501-DQB1*0301, DRB1*07-DQA1*0201-DQB1* 02, and DRB1*0401-DQA1*0301-DQB1*0301). The haplotypes DRB1*11-DQA1*0501-DQB1*0301, DRB1*08-DQA1* 0401-DQB1*04, and DRB1*07-DQA1*0201-DQB1*02 show interaction with DRB1*0401-DQB1*0302 haplotype. Assuming that DQA1*0401 is structurally similar to DQA1*0501, in a DRB1*0401-DQB1*0302-positive genotype, the first two haplotypes can form the DQ(α1*0501, β1*0302) trans-encoded heterodimer, whereas the latter can form DQ(α1*0301, β1*0201). The haplotypes DRB1*09-DQA1*0301-DQB1*0303 and DRB1*0401-DQA1*0301-DQB1*0301 show interaction with DRB1* 03-DQB1*02 haplotype and can form in individuals with a DRB1*03-DQB1*02-positive genotype the DQ(α1*0301, β1*0201) trans heterodimer. This correlation between haplotype interaction and possible formation of the trans-encoded heterodimers similar to those formed in the high-risk DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotype provides new evidence for the possibility of trans-encoded HLA DQ dimer disease susceptibility. One potential mechanism is that the trans-encoded dimers bind certain peptides differently from the cis heterodimers. Although one study did not find support for a relevance of an increase in the peptide-binding repertoire, this issue requires further investigations.26 Further studies will have to be carried out with potential autoantigenic epitopes to test this hypothesis. Finally, we have shown new evidence for synergy of three haplotypes (DRB1*11-DQA1*0501-DQB1*0301, DRB1*07-DQA1*0201-DQB1*02, and DRB1*0401-DQA1* 0301-DQB1*0301), but it is difficult from these data to conclude which of the two trans-encoded DQ heterodimers in DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 may be associated with the strongest susceptibility, that is, DQ(α1*0301,β1*0201) or DQ(α1*0501, β1*0302), although some suggestions have been made previously.4, 24
Obviously, it cannot be ruled out that the interaction observed here is at another locus in the HLA region, or through an alternative mechanism.27 Furthermore, it follows from Table 3 that the absolute risk of a genotype depends more on the sum of susceptible and protective elements, such as the presence of protective DQ heterodimers, DR molecules, and non-HLA factors.
It has been shown that efficiency of dimer formation differs between different DQα1 and DQβ1 allele products.28 The DQ molecules from the DRB1*0101-DQB1*0501 haplotype are not able to form trans-encoded dimers with the DQ β1 and α1 chain products from either of the DRB1*0401-DQB1*0302 or DRB1*03-DQB1*02 haplotypes. This suggests that only cis-encoded dimers are expressed by DRB1*0401-DQB1*0302/DRB1*01-DQB1*05 and DRB1*03-DQB1*02/DRB1*01-DQB1*05 genotypes. The risk of DRB1*0401-DQB1*0302/DRB1*01-DQB1*05 is approximately three-fold that of DRB1*03-DQB1*02/DRB1*01-DQB1*05 (Table 3). Interestingly, the risk of the DRB1*0401-DQB1*0302 homozygous genotype is also three-fold that of the DRB1*03-DQB1*02 homozygous genotype (Table 3). Since it is unlikely that non-multiplicative epistatic effects are present in these genotypes, the similarity between the increase in risk suggests that these genotypes can be considered as ‘pure’ measures of the susceptibility provided by the DRB1*03-DQB1*02 and DRB1*0401-DQB1*0302 haplotypes.
However, the risk of the homozygous genotypes is higher than the heterozygous DRB1*01-DQB1*05 genotypes, indicating that the amount of expressed highly susceptible heterodimers is important.29 An alternative explanation is that the DRB1*01-DQB1*05 haplotype confers dominant protection, which seems unlikely when comparing the risk of DRB1*01-DQB1*05 to that of established protective haplotypes such as DRB1*14-DQB1*05 and DRB1*15-DQB1*06, and from transmission rates of DRB1*01-DQB1*05 to affected siblings that do not carry either DRB1*0401-DQB1*0302 or DRB1*03-DQB1*02.30 Taken together with the observed associations of trans-encoded dimers, these observations suggest that part of the variation in risk observed is influenced by the number of expressed high-risk dimers, which is determined by the number of combinations of DQβ and DQα chains and their affinity to form heterodimers.31 Evidence for such a gene dosage effect of HLA-DQ2 in correlation to T-cell response to gluten peptide epitopes has been found recently in coeliac disease, in which the T-cell response was correlated to the number of DQ2 molecules.32 In coeliac disease, the susceptible dimer is DQA1*0501-DQB1*02, which is also formed in trans when the DRB1*07-DQB1*02 haplotype is found in a DRB1*03-DQB1*02-positive genotype. It has been well documented that the increased susceptibility of the DRB1*07-DQB1*02 haplotype is only present when combined with another haplotype that carries DQA1*0501. In narcolepsy, the high-risk haplotype is DRB1*15-DQB1*06, which in homozygous form has the highest genotype risk for disease, suggestive of a dosage effect. Remarkably, DQB1*0501 and DQA1*01 (non-*0102) alleles are protective in narcolepsy.33 Following our hypothesis, the protection of DQB1*0501 and non-DQA1*0102 can be explained by the effect of the DRB1*01-DQA1*0101-DQB1*0501 haplotype through reduction in the number of susceptible heterodimers, since it is likely that DQB1*05 can form a heterodimer with DQA1*0102 of the DRB1*15-DQB1*06 haplotype.
Apart from the trans dimer effect described here, several other factors are likely to play a role in the susceptibility of HLA class II. First, it has been described that the response of a DQ2.1 restricted HSV-2 specific T-cell clone responding to HSV peptides was not correlated with gene dosage, but rather with the peptide–MHC avidity.34 Second, the importance of DRB1 is obvious by the difference in susceptibility of DR4 subtypes. Most clear is the lower risk of DRB1*0403 and DRB1*0406 as previously described.35, 36, 37 DRB1*0403 and DRB1*0406 share the E at position –74, which differentiates the two from the high-risk DRB1*0401 allele. Position –74 is part of the P4 pocket of the DRB1 molecule, which has been consistently implicated in several models for disease prediction in rheumatoid arthritis.38, 39 The predictive value of the P4 pocket has also been demonstrated by others,2, 40, 41 and has a strong pocket structural similarity between DRB1*0403 and DQB1*0301, both protective for T1D.2 Third, several reports suggest the presence of an additional susceptibility locus in the class II, III, and I regions in several autoimmune diseases, although the necessity of fully compensating for the class II effect in these studies is a complicating factor.14, 27 Finally, variations within the regulatory sequences of HLA-DQ have also been found that could influence susceptibility. Together, these susceptibility factors probably have a large influence on the risk as measured for HLA class II and could contribute to the synergy observed in DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotypes.
Estimation of the risk of genotypes in case–control design
Several authors have recognized that standard risk calculation by OR can be biased when more than one risk allele is present. A common correction for this bias is to ‘standardize’ the OR by setting one haplo- or genotype to unity as a ‘reference’. Here we show ORs calculated with DRB1*01-DQB1*0501 haplo- or homozygous genotype as the reference (OR-r). Calculation with a different reference did not lead to significant differences in ranking or relative magnitude of the haplo- or genotypes.
Estimation of the risk of haplotype and genotype in nuclear families
Relative risks can be estimated using simplex families. Likelihood methods for these case–parent triads can be used, conditional on the parental genotype.42, 43, 44, 45 These methods alleviate bias caused by population admixture, nonrandom mating, and deviations from HW equilibrium, and conditioning on parental genotypes avoids bias by ascertainment on multiple affected siblings.18, 20, 42, 43, 44, 45 With the likelihood method, haplotype relative risks (RRi) or genotype relative risks (RRij) can be estimated, for haplotype i or genotype ij. We have previously written a program (CETDT) that outputs the ETDT estimate RRi or, when using the full genotype model, RRij.19 For clarity, we refer to this ETDT measure as RTP. Furthermore, CETDT can be used to test directly whether two different haplotypes have different risks. Here, we have used this program to analyse HLA class II haplotypes and genotypes in T1D families from several populations. For the multiplex families, one random affected sibling was chosen to reduce these families to a simplex form.
Nuclear diabetic families with HLA class II DQB1, DQA1, and DRB1 typing were available from Dutch (219 families), Norwegian (386 families), UK (379 families), US (176 families), and Sardinian populations (261 families), in total comprising 1421 families. Full subtyping was available for US and Norwegian families. DQB1*06 subtyping was available for the Dutch families, and DRB1*04 subtyping was available for all populations.
Conditional Extended Transmission Disequilibrium Test
Relative Transmission Probability
Relative Risk for disease.
Cucca F, Todd JA . HLA susceptibility to type 1 diabetes: methods and mechanisms. In: Browning MJ, McMichael AJ (eds). HLA and MHC: Genes, Molecules and Function. BIOS Scientific Publishers Ltd: Oxford, 1996, pp 23–60.
Cucca F, Lampis R, Congia M et al. A correlation between the relative predisposition of MHC class II alleles to type 1 diabetes and the structure of their proteins. Hum Mol Genet 2001; 10: 2025–2037.
Thorsby E, Undlien D . The HLA associated predisposition to type 1 diabetes and other autoimmune diseases. J Pediatr Endocrinol Metab 1996; 9 (Suppl 1): 75–88.
She JX . Susceptibility to type I diabetes: HLA-DQ and DR revisited [see comments]. Immunol Today 1996; 17: 323–329.
Cucca F, Muntoni F, Lampis R et al. Combinations of specific DRB1, DQA1, DQB1 haplotypes are associated with insulin-dependent diabetes mellitus in Sardinia. Hum Immunol 1993; 37: 85–94.
Noble JA, Valdes AM, Cook M, Klitz W, Thomson G, Erlich HA . The role of HLA class II genes in insulin-dependent diabetes mellitus: molecular analysis of 180 Caucasian, multiplex families. Am J Hum Genet 1996; 59: 1134–1148.
Ronningen KS, Spurkland A, Iwe T, Vartdal F, Thorsby E . Distribution of HLA-DRB1, -DQA1 and -DQB1 alleles and DQA1-DQB1 genotypes among Norwegian patients with insulin-dependent diabetes mellitus. Tissue Antigens 1991; 37: 105–111.
Sheehy MJ, Scharf SJ, Rowe JR et al. A diabetes-susceptible HLA haplotype is best defined by a combination of HLA-DR and -DQ alleles. J Clin Invest 1989; 83: 830–883.
Schipper RF, Koeleman BP, Bruining GJ et al. HLA class II associations with type 1 diabetes mellitus: a multivariate approach. Tissue Antigens 2001; 57: 144–150.
Erlich HA, Zeidler A, Chang J et al. HLA class II alleles and susceptibility and resistance to insulin dependent diabetes mellitus in Mexican-American families. Nat Genet 1993; 3: 358–364.
Park YS, Wang CY, Ko KW et al. Combinations of HLA DR and DQ molecules determine the susceptibility to insulin-dependent diabetes mellitus in Koreans. Hum Immunol 1998; 59: 794–801.
Mijovic CH, Jenkins D, Jacobs KH, Penny MA, Fletcher JA, Barnett AH . HLA-DQA1 and -DQB1 alleles associated with genetic susceptibility to IDDM in a black population. Diabetes 1991; 40: 748–753.
Johansson S, Lie BA, Todd JA et al. Evidence of at least two type 1 diabetes susceptibility genes in the HLA complex distinct from HLA-DQB1, -DQA1 and -DRB1. Genes Immun 2003; 4: 46–53.
Zavattari P, Lampis R, Motzo C et al. Conditional linkage disequilibrium analysis of a complex disease superlocus, IDDM1 in the HLA region, reveals the presence of independent modifying gene effects influencing the type 1 diabetes risk encoded by the major HLA-DQB1, -DRB1 disease loci. Hum Mol Genet 2001; 10: 881–889.
Undlien DE, Friede T, Rammensee HG et al. HLA-encoded genetic predisposition in IDDM: DR4 subtypes may be associated with different degrees of protection. Diabetes 1997; 46: 143–149.
Thomson G, Motro U, Selvin S . Statistical aspects of measuring the strength of associations between HLA antigens and diseases. Tissue Antigens 1983; 21: 320–332.
Payami H, Joe S, Farid NR et al. Relative predispositional effects (RPEs) of marker alleles with disease: HLA-DR alleles and Graves disease. Am J Hum Genet 1989; 45: 541–546.
Cordell H, Clayton DG . A unified stepwise regression procedure for evaluating the relative effects of polymorphisms within a gene using case/control of family data: application to HLA in type 1 diabetes. Am J Hum Genet 2002; 70: 124–141.
Koeleman BP, Dudbridge F, Cordell HJ, Todd JA . Adaptation of the extended transmission/disequilibrium test to distinguish disease associations of multiple loci: the Conditional Extended Transmission/Disequilibrium Test. Ann Hum Genet 2000; 64: 207–213.
Cordell HJ . Effect of recombination, ascertainment, and multiple affected offspring on case/pseudo-control analysis. Genet Epidemiol 2003; 25: 244.
Thomson G, Robinson WP, Kuhner MK et al. Genetic heterogeneity, modes of inheritance, and risk estimates for a joint study of Caucasians with insulin-dependent diabetes mellitus. Am J Hum Genet 1988; 43: 799–816.
Chuang LM, Wu HP, Tsai WY, Lin BJ, Tai TY . Transcomplementation of HLA DQA1-DQB1 in DR3/DR4 and DR3/DR9 heterozygotes and IDDM in Taiwanese families. Diabetes Care 1995; 18: 1483–1486.
Ronningen KS, Markussen G, Iwe T, Thorsby E . An increased risk of insulin-dependent diabetes mellitus (IDDM) among HLA-DR4,DQw8/DRw8,DQw4 heterozygotes. Hum Immunol 1989; 24: 165–173.
Thorsby E . Invited anniversary review: HLA associated diseases. Hum Immunol 1997; 53: 1–11.
Nepom BS, Schwarz D, Palmer JP, Nepom GT . Transcomplementation of HLA genes in IDDM. HLA-DQ alpha- and beta-chains produce hybrid molecules in DR3/4 heterozygotes. Diabetes 1987; 36: 114–117.
Reichstetter S, Kwok WW, Nepom GT . Impaired binding of a DQ2 and DQ8-binding HSV VP16 peptide to a DQA1*0501/DQB1*0302 trans class II heterodimer. Tissue Antigens 1999; 53: 101–105.
Thorsby E, Caillat-Zucman S, Dorman J et al. Additional disease predisposing genes in the HLA complex. A summary of the 13.IHWS disease component studies. HLA 2004. Immunobiology of the Human MHC.
Kwok WW, Kovats S, Thurtle P, Nepom GT . HLA-DQ allelic polymorphisms constrain patterns of class II heterodimer formation. J Immunol 1993; 150: 2263–2272.
Nepom GT, Kwok WW . Molecular basis for HLA-DQ associations with IDDM. Diabetes 1998; 47: 1177–1184.
Undlien DE, Kockum I, Ronningen KS et al. HLA association in type 1 diabetes among patients not carrying high-risk DR3-DQ2 or DR4-DQ8 haplotypes. Tissue Antigens 1999; 54: 543–551.
Sant AJ, Germain RN . Intracellular competition for component chains determines class II MHC cell surface phenotype. Cell 1989; 57: 797–805.
Vader W, Stepniak D, Kooy Y et al. The HLA-DQ2 gene dose effect in celiac disease is directly related to the magnitude and breadth of gluten-specific T cell responses. Proc Natl Acad Sci USA 2003; 100: 12390–12395.
Mignot E, Lin L, Rogers W et al. Complex HLA-DR and-DQ interactions confer risk of narcolepsy-cataplex in three ethnic groups. Am J Hum Genet 2001; 68: 686–699.
Reichstetter S, Kwok WW, Kochik S, Koelle DM, Beaty JS, Nepom GT . MHC-peptide ligand interactions establish a functional threshold for antigen-specific T cell recognition. Hum Immunol 1999; 60: 608–618.
Awata T, Kuzuya T, Matsuda A, Iwamoto Y, Kanazawa Y . Genetic analysis of HLA class II alleles and susceptibility to type 1 (insulin-dependent) diabetes mellitus in Japanese subjects. Diabetologia 1992; 35: 419–424.
Cucca F, Muntoni F, Lampis R et al. Combinations of specific DRB1, DQA1, DQB1 haplotypes are associated with insulin-dependent diabetes mellitus in Sardinia. Hum Immunol 1993; 37: 85–94.
Cucca F, Lampis R, Frau F et al. The distribution of DR4 haplotypes in Sardinia suggest a primary association of type 1 diabetes with DRB1 and DQB1 loci. Hum Immunol 1995; 43: 301–308.
Zanelli E, Gonzalez-Gay MA, David CS . Could HLA-DRB1 be the protective locus in rheumatoid arthritis? Immunol Today 2001; 16: 274–278.
Auger I, Roudier J . HLA-DR and the development of rheumatoid arthritis. Autoimmunity 1997; 26: 123–128.
Zamani M, Cassiman JJ . Reevaluation of the importance of polymorphic HLA class II alleles and amino acids in the susceptibility of individuals of different populations to type I diabetes. Am J Med Genet 1998; 76: 183–194.
Djoulah S, Busson M, Sasazuki T et al. A new predictive model for insulin-dependent diabetes mellitus susceptibility based on combinations of molecular HLA-DRB1 and HLA-DQB1 pockets. Tissue Antigens 1999; 54: 341–348.
Self SG, Longton G, Kopecky KJ, Liang KY . On estimating HLA/disease association with application to a study of aplastic anemia. Biometrics 1991; 47: 53–56.
Schaid DJ, Sommer SS . Genotype relative risks: methods for design and analysis of candidate-gene association studies. Am J Hum Genet 1993; 53: 1114–1126.
Schaid DJ . Likelihoods and TDT for the case–parents design. Genet Epidemiol 1999; 16: 250–260.
Sham PC, Curtis D . An extended transmission/disequilibrium test (TDT) for multi-allele marker loci. Ann Hum Genet 1995; 59: 323–336.
We thank the Juvenile Diabetes Research Foundation (JDRF), the Wellcome Trust, Dutch Diabetes Research Foundation (97.137,2001.10.004), The Netherlands Organisation for Health Research and Development (ZonMW) and The Juvenile Diabetes Research Foundation International (JDRF) (2001.10.004), and the Italian Telethon for financial support. We gratefully acknowledge the participation of all patients and family members, including provision of samples from T1D families from the Human Biological Data Interchange and Diabetes UK repositories, and sample collections by The Norwegian Study Group for Childhood Diabetes, and Italy. We thank Sarah Nutland and Helen Rance for DNA preparation and HLA typing.
About this article
Frontiers in Immunology (2019)
Discriminative T cell recognition of cross-reactive islet-antigens is associated with HLA-DQ8 transdimer–mediated autoimmune diabetes
Science Advances (2019)
The Lancet Diabetes & Endocrinology (2019)
Diabetes mellitus induced by PD-1 and PD-L1 inhibitors: description of pancreatic endocrine and exocrine phenotype
Acta Diabetologica (2019)