Modeling of HLA class II susceptibility to Type I diabetes reveals an effect associated with DPB1

The association of HLA-DP loci with autoimmune diabetes in Chinese

AIMS

To determine if HLA-DP loci independently contribute to classic type 1 diabetes (T1D) of all ages, childhood-onset T1D and latent autoimmune diabetes in adults (LADA) among Chinese Han population.

METHODS

A total of 518 patients with classic T1D (Among them 180 participants manifested T1D between 1 and 14 years), 519 patients with LADA and 527 normal controls were genotyped for both HLA-DPA1 and -DPB1 loci. The frequencies of DP alleles and haplotypes in patients were directly compared to those in controls, followed by adjustment for linkage disequilibrium (LD) with DR-DQ haplotypes.

RESULTS

In the direct comparison, DPA1*01:03, DPB1*04:01 and DPA1*01:03-DPB1*04:01 showed disease-predisposing effects in both the overall T1D group and the childhood-onset T1D group mainly due to their conjunction with the known susceptible DR3 haplotype. Conditioning on DR-DQ haplotypes, only DPA1*02:02-DPB1*02:02 significantly increased T1D risk among those diagnosed during childhood (OR = 2.02, 95% CI = 1.35-3.01). Whether or not adjusted for LD, no statistically significant HLA-DP association could be observed for LADA.

CONCLUSION

HLA-DP is implicated in the pathogenesis of childhood-onset T1D in Chinese, independent of the predominant DR-DQ loci and might serve as additional markers in genetic models for the recognition of those genetically at-risk individuals.

Immunogenetics of type 1 diabetes: A comprehensive review

Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing beta cells in the pancreas. Prevention of T1D will require the ability to detect and modulate the autoimmune process before the clinical onset of disease. Genetic screening is a logical first step in identification of future patients to test prevention strategies. Susceptibility to T1D includes a strong genetic component, with the strongest risk attributable to genes that encode the classical Human Leukocyte Antigens (HLA). Other genetic loci, both immune and non-immune genes, contribute to T1D risk; however, the results of decades of small and large genetic linkage and association studies show clearly that the HLA genes confer the most disease risk and protection and can be used as part of a prediction strategy for T1D. Current predictive genetic models, based on HLA and other susceptibility loci, are effective in identifying the highest-risk individuals in populations of European descent. These models generally include screening for the HLA haplotypes "DR3" and "DR4." However, genetic variation among racial and ethnic groups reduces the predictive value of current models that are based on low resolution HLA genotyping. Not all DR3 and DR4 haplotypes are high T1D risk; some versions, rare in Europeans but high frequency in other populations, are even T1D protective. More information is needed to create predictive models for non-European populations. Comparative studies among different populations are needed to complete the knowledge base for the genetics of T1D risk to enable the eventual development of screening and intervention strategies applicable to all individuals, tailored to their individual genetic background. This review summarizes the current understanding of the genetic basis of T1D susceptibility, focusing on genes of the immune system, with particular emphasis on the HLA genes.

Genetics of type 1 diabetes

Genetic susceptibility to type 1 diabetes (T1D) has been a subject of intensive study for nearly four decades. This article will present the history of these studies, beginning with observations of the Human Leukocyte Antigen (HLA) association in the 1970s, through the advent of DNA-based genotyping methodologies, through recent large, international collaborations and genome-wide association studies. More than 40 genetic loci have been associated with T1D in multiple studies; however, the HLA region, with its multiple genes and extreme polymorphism at those loci, remains by far the greatest contributor to the genetic susceptibility to T1D. Even after decades of study, the complete story has yet to unfold, and exact mechanisms by which HLA and other associated loci confer T1D susceptibility remain elusive.

Genetics of type 1 diabetes

Genetic susceptibility to type 1 diabetes (T1D) has been a subject of intensive study for nearly four decades. This article will present the history of these studies, beginning with observations of the Human Leukocyte Antigen (HLA) association in the 1970s, through the advent of DNA-based genotyping methodologies, through recent large, international collaborations and genome-wide association studies. More than 40 genetic loci have been associated with T1D in multiple studies; however, the HLA region, with its multiple genes and extreme polymorphism at those loci, remains by far the greatest contributor to the genetic susceptibility to T1D. Even after decades of study, the complete story has yet to unfold, and exact mechanisms by which HLA and other associated loci confer T1D susceptibility remain elusive.

From markers to molecular mechanisms: type 1 diabetes in the post-GWAS era

By the year 2000, a draft of the human genome sequence was completed. Millions of single-nucleotide polymorphisms (SNPs) had been deposited into public databases, and high throughput technologies were under development for SNP genotyping. At that time, it was predicted that large case control association studies would provide far better resolution and power than genome-wide linkage studies. Type 1 diabetes was one of the first phenotypes to be examined by genome-wide association studies (GWAS), and to date over 50 genomic regions have been associated with the disease. In general, the great majority of these loci individually contribute a relatively small degree of risk, and most loci lie outside of coding sequences. The identification of molecular mechanisms from these genomic data therefore remains a significant challenge. Here, we summarize genetic candidate, linkage, and association studies of type 1 diabetes and discuss a potential strategy to identify mechanisms of disease from genomic data.

HLA class I and genetic susceptibility to type 1 diabetes: results from the Type 1 Diabetes Genetics Consortium

OBJECTIVE

We report here genotyping data and type 1 diabetes association analyses for HLA class I loci (A, B, and C) on 1,753 multiplex pedigrees from the Type 1 Diabetes Genetics Consortium (T1DGC), a large international collaborative study.

RESEARCH DESIGN AND METHODS

Complete eight-locus HLA genotyping data were generated. Expected patient class I (HLA-A, -B, and -C) allele frequencies were calculated, based on linkage disequilibrium (LD) patterns with observed HLA class II DRB1-DQA1-DQB1 haplotype frequencies. Expected frequencies were compared to observed allele frequencies in patients.

RESULTS

Significant type 1 diabetes associations were observed at all class I HLA loci. After accounting for LD with HLA class II, the most significantly type 1 diabetes-associated alleles were B*5701 (odds ratio 0.19; P = 4 × 10(-11)) and B*3906 (10.31; P = 4 × 10(-10)). Other significantly type 1 diabetes-associated alleles included A*2402, A*0201, B*1801, and C*0501 (predisposing) and A*1101, A*3201, A*6601, B*0702, B*4403, B*3502, C*1601, and C*0401 (protective). Some alleles, notably B*3906, appear to modulate the risk of all DRB1-DQA1-DQB1 haplotypes on which they reside, suggesting a class I effect that is independent of class II. Other class I type 1 diabetes associations appear to be specific to individual class II haplotypes. Some apparent associations (e.g., C*1601) could be attributed to strong LD to another class I susceptibility locus (B*4403).

CONCLUSIONS

These data indicate that HLA class I alleles, in addition to and independently from HLA class II alleles, are associated with type 1 diabetes.

Genetic variation within the HLA class III influences T1D susceptibility conferred by high-risk HLA haplotypes

Human leukocyte antigen (HLA) class II DRB1 and DQB1 represent the major type I diabetes (T1D) genetic susceptibility loci; however, other genes in the HLA region are also involved in T1D risk. We analyzed 1411 pedigrees (2865 affected individuals) from the type I diabetes genetics consortium genotyped for HLA classical loci and for 12 single-nucleotide polymorphisms (SNPs) in the class III region previously shown to be associated with T1D in a subset of 886 pedigrees. Using the transmission disequilibrium test, we compared the proportion of SNP alleles transmitted from within the high-risk DR3 and DR4 haplotypes to affected offspring. Markers rs4151659 (mapping to CFB) and rs7762619 (mapping 5' of LTA) were the most strongly associated with T1D on DR3 (P=1.2 x 10(-9) and P=2 x 10(-12), respectively) and DR4 (P=4 x 10(-15) and P=8 x 10(-8), respectively) haplotypes. They remained significantly associated after stratifying individuals in analyses for B*1801, A*0101-B*0801, DPB1*0301, DPB1*0202, DPB1*0401 or DPB1*0402. Rs7762619 and rs4151659 are in strong linkage disequilibrium (LD) (r(2)=0.82) with each other, but a joint analysis showed that the association for each SNP was not solely because of LD. Our data support a role for more than one locus in the class III region contributing to risk of T1D.

Confirmation of HLA class II independent type 1 diabetes associations in the major histocompatibility complex including HLA-B and HLA-A

AIM

Until recently, human leucocyte antigen (HLA) class II-independent associations with type 1 diabetes (T1D) in the Major Histocompatibility Complex (MHC) region were not adequately characterized owing to insufficient map coverage, inadequate statistical approaches and strong linkage disequilibrium spanning the entire MHC. Here we test for HLA class II-independent associations in the MHC using fine mapping data generated by the Type 1 Diabetes Genetics Consortium (T1DGC).

METHODS

We have applied recursive partitioning to the modelling of the class II loci and used stepwise conditional logistic regression to test approximately 1534 loci between 29 and 34 Mb on chromosome 6p21, typed in 2240 affected sibpair (ASP) families.

RESULTS

Preliminary analyses confirm that HLA-B (at 31.4 Mb), HLA-A (at 30.0 Mb) are associated with T1D independently of the class II genes HLA-DRB1 and HLA-DQB1 (P = 6.0 x 10(-17) and 8.8 x 10(-13), respectively). In addition, a second class II region of association containing the single-nucleotide polymorphism (SNP), rs439121, and the class II locus HLA-DPB1, was identified as a T1D susceptibility effect which is independent of HLA-DRB1, HLA-DQB1 and HLA-B (P = 9.2 x 10(-8)). A younger age-at-diagnosis of T1D was found for HLA-B*39 (P = 7.6 x 10(-6)), and HLA-B*38 was protective for T1D.

CONCLUSIONS

These analyses in the T1DGC families replicate our results obtained previously in approximately 2000 cases and controls and 850 families. Taking both studies together, there is evidence for four T1D-associated regions at 30.0 Mb (HLA-A), 31.4 Mb (HLA-B), 32.5 Mb (rs9268831/HLA-DRA) and 33.2 Mb (rs439121/HLA-DPB1) that are independent of HLA-DRB1/HLA-DQB1. Neither study found evidence of independent associations at HLA-C, HLA-DQA1 loci nor in the UBD/MAS1L or ITPR3 gene regions. These studies show that to find true class II-independent effects, large, well-powered sample collections are required and be genotyped with a dense map of markers. In addition, a robust statistical methodology that fully models the class II effects is necessary. Recursive partitioning is a useful tool for modelling these multiallelic systems.

Several loci in the HLA class III region are associated with T1D risk after adjusting for DRB1-DQB1

AIM

Several studies have indicated that genes in the human leucocyte antigen (HLA) region additional to the HLA class II DRB1-DQB1 contribute to type 1 diabetes (T1D) susceptibility. The aim of this study was to assess if markers in the class III Major Histocompatibility Complex (MHC) region are associated with T1D after accounting for linkage disequilibrium (LD) with DRB1-DQB1.

METHODS

We investigated 356 single nucleotide polymorphisms (SNPs) in the class III region covering 1.1 megabases in two subsets of data: 289 Human Biological Data Interchange (HBDI) Caucasian families and 597 additional Caucasian families collected by the Type 1 Diabetes Genetics Consortium (T1DGC). Analysis conditioning on DRB1-DQB1 was performed using the overall conditional genotype method.

RESULTS

Thirteen SNPs replicated in both subsets of the data and showed evidence of an additional effect on disease risk. Although some of the SNPs are in tight LD with each other, at least six of the associations were not because of LD with other class III markers. The strongest association within class III markers was with rs2395106 that maps 5' to the NOTCH4 gene, which has also been implicated in susceptibility to rheumatoid arthritis. The second association was with rs707915 mapping to the MSH5 gene, in a block of six markers significantly associated with T1D after adjusting for LD with DR-DQ. In total, six-independent associations within class III were observed although results were not adjusted for LD with class I.

CONCLUSIONS

Our data confirm that the class III region is involved in T1D susceptibility and suggest that more than one gene in the region is involved.

Conditional analyses on the T1DGC MHC dataset: novel associations with type 1 diabetes around HLA-G and confirmation of HLA-B

The major histocompatibility complex (MHC) is known to harbour genetic risk factors for type 1 diabetes (T1D) additional to the class II determinants HLA-DRB1, -DQA1 and -DQB1, but strong linkage disequilibrium (LD) has made efforts to establish their location difficult. This study utilizes a dataset generated by the T1D genetics consortium (T1DGC), with genotypes for 2965 markers across the MHC in 2321 T1D families of multiple (mostly Caucasian) ethnicities. Using a comprehensive approach consisting of complementary conditional methods and LD analyses, we identified three regions with T1D association, independent both of the known class II determinants and of each other. A subset of polymorphisms that could explain most of the association in each region included single nucleotide polymorphisms (SNPs) in the vicinity of HLA-G, particular HLA-B and HLA-DPB1 alleles, and SNPs close to the COL11A2 and RING1 genes. Apart from HLA-B and HLA-DPB1, all of these represent novel associations, and subpopulation analyses did not indicate large population-specific differences among Caucasians for our findings. On account of the unusual genetic complexity of the MHC, further fine mapping is demanded, with the possible exception of HLA-B. However, our results mean that these efforts can be focused on narrow, defined regions of the MHC.

HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families

OBJECTIVE

The Type 1 Diabetes Genetics Consortium has collected type 1 diabetic families worldwide for genetic analysis. The major genetic determinants of type 1 diabetes are alleles at the HLA-DRB1 and DQB1 loci, with both susceptible and protective DR-DQ haplotypes present in all human populations. The aim of this study is to estimate the risk conferred by specific DR-DQ haplotypes and genotypes.

RESEARCH DESIGN AND METHODS

Six hundred and seven Caucasian families and 38 Asian families were typed at high resolution for the DRB1, DQA1, and DQB1 loci. The association analysis was performed by comparing the frequency of DR-DQ haplotypes among the chromosomes transmitted to an affected child with the frequency of chromosomes not transmitted to any affected child.

RESULTS

A number of susceptible, neutral, and protective DR-DQ haplotypes have been identified, and a statistically significant hierarchy of type 1 diabetes risk has been established. The most susceptible haplotypes are the DRB1*0301-DQA1*0501-DQB1*0201 (odds ratio [OR] 3.64) and the DRB1*0405-DQA1*0301-DQB1*0302, DRB1*0401-DQA1*0301-DQB*0302, and DRB1*0402-DQA1*0301-DQB1*0302 haplotypes (ORs 11.37, 8.39, and 3.63), followed by the DRB1*0404-DQA1*0301-DQB1*0302 (OR 1.59) and the DRB1*0801-DQB1*0401-DQB1*0402 (OR 1.25) haplotypes. The most protective haplotypes are DRB1*1501-DQA1*0102-DQB1*0602 (OR 0.03), DRB1*1401-DQA1*0101-DQB1*0503 (OR 0.02), and DRB1*0701-DQA1*0201-DQB1*0303 (OR 0.02).

CONCLUSIONS

Specific combinations of alleles at the DRB1, DQA1, and DQB1 loci determine the extent of haplotypic risk. The comparison of closely related DR-DQ haplotype pairs with different type 1 diabetes risks allowed identification of specific amino acid positions critical in determining disease susceptibility. These data also indicate that the risk associated with specific HLA haplotypes can be influenced by the genotype context and that the trans-complementing heterodimer encoded by DQA1*0501 and DQB1*0302 confers very high risk.

Searching for additional disease loci in a genomic region

Our aim is to review methods to optimize detection of all disease genes in a genetic region. As a starting point, we assume there is sufficient evidence from linkage and/or association studies, based on significance levels or replication studies, for the involvement in disease risk of the genetic region under study. For closely linked markers, there will often be multiple associations with disease, and linkage analyses identify a region rather than the specific disease-predisposing gene. Hence, the first task is to identify the primary (major) disease-predisposing gene or genes in a genetic region, and single nucleotide polymorphisms thereof, that is, how to distinguish true associations from those that are just due to linkage disequilibrium with the actual disease-predisposing variants. Then, how do we detect additional disease genes in this genetic region? These two issues are of course very closely interrelated. No existing programs, either individually or in aggregate, can handle the magnitude and complexity of the analyses needed using currently available methods. Further, even with modern computers, one cannot study every possible combination of genetic markers and their haplotypes across the genome, or even within a genetic region. Although we must rely heavily on computers, in the final analysis of multiple effects in a genetic region and/or interaction or independent effects between unlinked genes, manipulation of the data by the individual investigator will play a crucial role. We recommend a multistrategy approach using a variety of complementary methods described below.

Relative predispositional effects of HLA class II DRB1-DQB1 haplotypes and genotypes on type 1 diabetes: a meta-analysis

The direct involvement of the human leukocyte antigen class II DR-DQ genes in type 1 diabetes (T1D) is well established, and these genes display a complex hierarchy of risk effects at the genotype and haplotype levels. We investigated, using data from 38 studies, whether the DR-DQ haplotypes and genotypes show the same relative predispositional effects across populations and ethnic groups. Significant differences in risk within a population were considered, as well as comparisons across populations using the patient/control (P/C) ratio. Within a population, the ratio of the P/C ratios for two different genotypes or haplotypes is a function only of the absolute penetrance values, allowing ranking of risk effects. Categories of consistent predisposing, intermediate ('neutral'), and protective haplotypes were identified and found to correlate with disease prevalence and the marked ethnic differences in DRB1-DQB1 frequencies. Specific effects were identified, for example for predisposing haplotypes, there was a statistically significant and consistent hierarchy for DR4 DQB1*0302s: DRB1*0405 =*0401 =*0402 > *0404 > *0403, with DRB1*0301 DQB1*0200 (DR3) being significantly less predisposing than DRB1*0402 and more than DRB1*0404. The predisposing DRB1*0401 DQB1*0302 haplotype was relatively increased compared with the protective haplotype DRB1*0401 DQB1*0301 in heterozygotes with DR3 compared with heterozygotes with DRB1*0101 DQB1*0501 (DR1). Our results show that meta-analyses and use of the P/C ratio and rankings thereof can be valuable in determining T1D risk factors at the haplotype and amino acid residue levels.

14th International HLA and Immunogenetics Workshop: report on the HLA component of type 1 diabetes

The type 1 diabetes (T1D) component of the 13th International Histocompatibility Workshop (IHW) obtained microsatellite (msat) and human leukocyte antigen (HLA)-DR/DQ data on case/control and family samples through an international collaboration. The aim was to detect the effects of susceptibility loci on the HLA complex independent of the primary determinants in the class II region (HLA-DR/DQ). As part of the activity of the 14th International HLA and Immunogenetics Workshop (14th IHIWS), a T1D workshop was held to present analyses of the 13th IHW data and to discuss the current status of knowledge about the genetics of T1D. These data are now available online through dbMHC, a web-based resource established by the National Center for Biotechnology. Continuing work since the 13th IHW has resulted in published work showing heterogeneity of DR3 haplotypes in data sets from the 13th IHW and Human Biological Data Interchange (HBDI). In addition, we identified markers that define DRB1*1501 DQB1*0602 haplotypes conferring reduced protection from diabetes in a Swedish 13th IHW data set. Further analyses of the 13th IHW data set not only showed some significant results but also demonstrated extensive heterogeneity reminiscent of non-HLA genes. The haplotype analysis in HBDI families identified two msats with significant effects on susceptibility and statistically significant age of onset effects at class III markers that are not because of linkage disequilibrium, with class I alleles known to affect age of onset. The above studies underscore the importance of refining our understanding of susceptibility associated with genes in the HLA complex.

Type 1 diabetes: evidence for susceptibility loci from four genome-wide linkage scans in 1,435 multiplex families

Type 1 diabetes is a common, multifactorial disease with strong familial clustering (genetic risk ratio [lambda(S)] approximately 15). Approximately 40% of the familial aggregation of type 1 diabetes can be attributed to allelic variation of HLA loci in the major histocompatibility complex on chromosome 6p21 (locus-specific lambda(S) approximately 3). Three other disease susceptibility loci have been clearly demonstrated based on their direct effect on risk, INS (chromosome 11p15, allelic odds ratio [OR] approximately 1.9), CTLA4 (chromosome 2q33, allelic OR approximately 1.2), and PTPN22 (chromosome 1p13, allelic OR approximately 1.7). However, a large proportion of type 1 diabetes clustering remains unexplained. We report here on a combined linkage analysis of four datasets, three previously published genome scans, and one new genome scan of 254 families, which were consolidated through an international consortium for type 1 diabetes genetic studies (www.t1dgc.org) and provided a total sample of 1,435 families with 1,636 affected sibpairs. In addition to the HLA region (nominal P = 2.0 x 10(-52)), nine non-HLA-linked regions showed some evidence of linkage to type 1 diabetes (nominal P < 0.01), including three at (or near) genome-wide significance (P < 0.05): 2q31-q33, 10p14-q11, and 16q22-q24. In addition, after taking into account the linkage at the 6p21 (HLA) region, there was evidence supporting linkage for the 6q21 region (empiric P < 10(-4)). More than 80% of the genome could be excluded as harboring type 1 diabetes susceptibility genes of modest effect (lambda(S) > or = 1.3) that could be detected by linkage. This study represents one of the largest linkage studies ever performed for any common disease. The results demonstrate some consistency emerging for the existence of susceptibility loci on chromosomes 2q31-q33, 6q21, 10p14-q11, and 16q22-q24 but diminished support for some previously reported locations.

Genetic Association Studies in Complex Disease: Disentangling Additional Predisposing Loci from Associated Neutral Loci Using a Constrained ‐ Permutation Approach

In the process of genetically mapping a complex disease, the question may arise whether a certain polymorphism is the only causal variant in a region. A number of methods can answer this question, but unfortunately these methods are optimal for bi-allelic loci only. We wanted to develop a method that is more suited for multi-allelic loci, such as microsatellite markers. We propose the Additional Disease Loci Test (ADLT): the alleles at an additional locus are permuted within the subsample of haplotypes that have identical alleles at the predisposing locus. The hypothesis being tested is, whether the predisposing locus is the sole factor predisposing to the trait that is in LD with the additional locus under study. We applied ADLT to simulated datasets and a published dataset on Type 1 Diabetes, genotyped for microsatellite markers in the HLA-region. The method showed the expected number of false-positive results in the absence of additional loci, but proved to be more powerful than existing methods in the presence of additional disease loci. ADLT was especially superior in datasets with less LD or with multiple predisposing alleles. We conclude that the ADLT can be useful in identifying additional disease loci.

Candidate epitope identification using peptide property models: application to cancer immunotherapy

Peptides derived from pathogens or tumors are selectively presented by the major histocompatibility complex proteins (MHC) to the T lymphocytes. Antigenic peptide-MHC complexes on the cell surface are specifically recognized by T cells and, in conjunction with co-factor interactions, can activate the T cells to initiate the necessary immune response against the target cells. Peptides that are capable of binding to multiple MHC molecules are potential T cell epitopes for diverse human populations that may be useful in vaccine design. Bioinformatical approaches to predict MHC binding peptides can facilitate the resource-consuming effort of T cell epitope identification. We describe a new method for predicting MHC binding based on peptide property models constructed using biophysical parameters of the constituent amino acids and a training set of known binders. The models can be applied to development of anti-tumor vaccines by scanning proteins over-expressed in cancer cells for peptides that bind to a variety of MHC molecules. The complete algorithm is described and illustrated in the context of identifying candidate T cell epitopes for melanomas and breast cancers. We analyzed MART-1, S-100, MBP, and CD63 for melanoma and p53, MUC1, cyclin B1, HER-2/neu, and CEA for breast cancer. In general, proteins over-expressed in cancer cells may be identified using DNA microarray expression profiling. Comparisons of model predictions with available experimental data were assessed. The candidate epitopes identified by such a computational approach must be evaluated experimentally but the approach can provide an efficient and focused strategy for anti-cancer immunotherapy development.

HLA associations in type 1 diabetes: DPB1 alleles may act as markers of other HLA-complex susceptibility genes

Alleles at the HLA-DQB1, -DQA1 and -DRB1 loci are major determinants for susceptibility to develop type 1 diabetes (T1D). Increasing evidence supports that also other genes in, or near, the HLA complex contribute to the HLA-encoded risk. Alleles at the DPB1 locus have been suggested to directly influence the risk conferred by DQB1, DQA1 and DRB1 alleles, but the results are conflicting. We therefore genotyped 217 families from Norway, Denmark, Sweden and southern France to address the role of DPB1 alleles in T1D. After taking into account linkage disequilibrium (LD) with DQB1, DQA1 and DRB1 alleles, we found evidence that some DPB1 alleles are associated with modulating the risk of developing T1D. However, we show that the strong LD in the HLA complex, and the presence of extended haplotypes complicate the interpretation of the results. On DQ2-DR3 haplotypes, both allele 3 at microsatellite D6S2223 located 5.3-Mb telomeric of DPB1 and the extended DQ2-DR3-B18 haplotype display much stronger association than DPB1 alleles. When we exclude these effects, most of the apparent association of DPB1 alleles on DQ2-DR3 haplotypes disappear. Taken together, although we cannot completely rule out an effect of some DPB1 alleles, we propose that the statistically significant, albeit weak, DPB1 associations found are most likely the result of LD with another unidentified disease-susceptibility gene(s) in this region.

Genetics of type 1 diabetes mellitus

At least 20 different chromosomal regions have been linked to type 1 diabetes (T1D) susceptibility in humans, using genome screening, candidate gene testing, and studies of human homologues of mouse susceptibility genes. The largest contribution from a single locus (IDDM1) comes from several genes located in the MHC complex on chromosome 6p21.3, accounting for at least 40% of the familial aggregation of this disease. Approximately 30% of T1D patients are heterozygous for HLA-DQA1*0501-DQB1*0201/DQA1*0301-DQB1*0302 alleles (formerly referred to as HLA-DR3/4 and for simplification usually shortened to HLA-DQ2/DQ8), and a particular HLA-DQ6 molecule (HLA-DQA1*0102-DQB1*0602) is associated with dominant protection from the disease. There is evidence that certain residues important for structure and function of both HLA-DQ and DR peptide-binding pockets determine disease susceptibility and resistance. Independent confirmation of the IDDM2 locus on chromosome 11p15.5 has been achieved in both case-control and family-based studies, whereas associations with the other potential IDDM loci have not always been replicated. Several possibilities to explain these variable results from different studies are discussed, and a key factor affecting both linkage and association studies is that the genetic basis of T1D susceptibility may differ between ethnic groups. Some future strategies to address these problems are proposed. These include increasing the sample size in homogenous ethnic groups, high throughput genotyping and genomewide linkage disequilibrium (LD) mapping to establish disease associated ancestral haplotypes. Elucidation of the function of particular genes ('functional genomics') in the pathogenesis of T1D will be a most important element in future studies in this field, in addition to more sophisticated methods of statistical analyses.

Analysis of the role of DPB1-encoded amino acids in the genetic predisposition to type I diabetes mellitus

The role of the DPB1 gene in genetic susceptibility to type I diabetes has yet to be elucidated. Studies of DPB1 alleles are conflicting. Analysis at the amino acid level, rather than consideration of allelic polymorphism, has been informative in determining disease susceptibility encoded by the DRB1 and DQ genes. In this study, therefore, amino acid variation at polymorphic sites of the DPbeta peptide chain encoded by the second exon of the DPB1 gene was analyzed in diabetic and control subjects from white Caucasian, North Indian Asian, and Jamaican populations. Human leukocyte antigen genotypes and haplotypes were analyzed using a logistic-regression approach and the data were conditioned for the effects on disease risk of the DRB1, DQA1, and DQB1 genes. Eight DPbeta amino acid residues were significantly associated with type I diabetes independent of DR and DQ (DPbeta 9, 33, 35, 36, 55, 56, 57, and 69). None of these residues, however, correlated consistently with disease risk in all three racial groups. This contrasts with findings for the DRbeta, DQalpha and DQbeta peptide chains, where the identity of the amino acid at particular sites has been found to correlate with predisposition to type I diabetes.

An overview of the genetic analysis of complex diseases, with reference to type 1 diabetes

Despite extensive efforts by many groups, progress in the mapping of complex diseases has been exceedingly slow, only a few genes and some genetic regions having been identified. The general picture is one of difficulty in locating disease genes and in the replication of linkages. This results from the role in disease of a large number of genes, many with a relatively minor effect and many involving common genetic variation. A multi-strategy approach to the mapping of complex diseases is required: no single method is sufficient or optimal. The role of human leukocyte antigens in type 1 diabetes has been known for nearly 30 years, and the associations, linkage and genetic contribution to disease are all strong, but all the human leukocyte antigen region genes involved in the disease process have not yet been identified. The methods used in study of this component to type 1 diabetes are a model for all complex diseases.