[Show abstract][Hide abstract] ABSTRACT: Tissue transglutaminase autoantibodies (tTGAs) represent the first evidence of celiac disease (CD) development. Associations of HLA-DR3-DQA1*05:01-DQB1*02:01 (i.e., DR3-DQ2) and, to a lesser extent, DR4-DQA1*03:01-DQB1*03:02 (i.e., DR4-DQ8) with the risk of CD differ by country, consistent with additional genetic heterogeneity that further refines risk. Therefore, we examined human leukocyte antigen (HLA) factors other than DR3-DQ2 for their contribution to developing tTGAs.
The Environmental Determinants of Diabetes in the Young (TEDDY) study enrolled 8,676 infants at an increased HLA-DR-DQ risk for type 1 diabetes and CD into a 15-year prospective surveillance follow-up. Of those followed up, 21% (n=1,813) carried DR3-DQ2/DR3-DQ2, 39% (n=3,359) carried DR3-DQ2/DR4-DQ8, 20% (n=1701) carried DR4-DQ8/DR4-DQ8, and 17% (n=1,493) carried DR4-DQ8/DQ4. Within TEDDY, a nested case-control design of 248 children with CD autoimmunity (CDA) and 248 matched control children were genotyped for HLA-B, -DRB3, -DRB4, -DPA1, and -DPB1 genes, and the entire cohort was genotyped for single-nucleotide polymorphisms (SNPs) using the Illumina ImmunoChip. CDA was defined as a positive tTGA test at two consecutive clinic visits, whereas matching in those with no evidence of tTGAs was based on the presence of HLA-DQ2, country, and sex.
After adjustment for DR3-DQ2 and restriction to allele frequency (AF) ≥5%, HLA-DPB1*04:01 was inversely associated with CDA by conditional logistic regression (AF=44%, odds ratio=0.71, 95% confidence interval (CI)=0.53-0.96, P=0.025). This association of time to CDA and HLA-DPB1*04:01 was replicated with statistical significance in the remainder of the cohort using imputation for specific HLA alleles based on SNP genotyping (hazard ratio=0.84, 95% CI=0.73-0.96, P=0.013).
HLA-DPB1*04:01 may reduce the risk of tTGAs, an early marker of CD, among DR3-DQ2 children, confirming that additional variants in the HLA region influence the risk for CDA.Am J Gastroenterol advance online publication, 26 May 2015; doi:10.1038/ajg.2015.150.
The American Journal of Gastroenterology 05/2015; 110(6). DOI:10.1038/ajg.2015.150 · 10.76 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Recently, genome-wide association studies (GWAS) have been particularly successful in identifying vitiligo susceptibility loci in populations of European-derived white, Chinese, and Indian subcontinental ancestry (Spritz, 2013). The strongest genetic associations of vitiligo are in the major histocompatibility complex (MHC) on chromosome 6, both in terms of statistical significance and magnitude of effect (odds ratio; OR). However, the specific associated MHC loci and alleles differ among different world populations. In European-derived whites, vitiligo is associated with both MHC class I (HLA-A) and class II loci. On the Indian subcontinent, vitiligo is associated with MHC class II loci. In Han Chinese, vitiligo is associated with the class III region (Spritz, 2013).This article is protected by copyright. All rights reserved.
[Show abstract][Hide abstract] ABSTRACT: NK cells are innate immune cells known for their cytolytic activities toward tumors and infections. They are capable of expressing diverse killer Ig-like receptors (KIRs), and KIRs are implicated in susceptibility to Crohn's disease (CD), a chronic intestinal inflammatory disease. However, the cellular mechanism of this genetic contribution is unknown. In this study, we show that the "licensing" of NK cells, determined by the presence of KIR2DL3 and homozygous HLA-C1 in host genome, results in their cytokine reprogramming, which permits them to promote CD4(+) T cell activation and Th17 differentiation ex vivo. Microfluidic analysis of thousands of NK single cells and bulk secretions established that licensed NK cells are more polarized to proinflammatory cytokine production than unlicensed NK cells, including production of IFN-γ, TNF-α, CCL-5, and MIP-1β. Cytokines produced by licensed NK augmented CD4(+) T cell proliferation and IL-17A/IL-22 production. Ab blocking indicated a primary role for IFN-γ, TNF-α, and IL-6 in the augmented T cell-proliferative response. In conclusion, NK licensing mediated by KIR2DL2/3 and HLA-C1 elicits a novel NK cytokine program that activates and induces proinflammatory CD4(+) T cells, thereby providing a potential biologic mechanism for KIR-associated susceptibility to CD and other chronic inflammatory diseases.
The Journal of Immunology 06/2014; 193(2). DOI:10.4049/jimmunol.1400093 · 4.92 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The high-resolution human leukocyte antigen (HLA) genotyping assay that we developed using 454 sequencing and Conexio software uses generic polymerase chain reaction (PCR) primers for DRB exon 2. Occasionally, we observed low abundance DRB amplicon sequences that resulted from in vitro PCR 'crossing over' between DRB1 and DRB3/4/5. These hybrid sequences, revealed by the clonal sequencing property of the 454 system, were generally observed at a read depth of 5%-10% of the true alleles. They usually contained at least one mismatch with the IMGT/HLA database, and consequently, were easily recognizable and did not cause a problem for HLA genotyping. Sometimes, however, these artifactual sequences matched a rare allele and the automatic genotype assignment was incorrect. These observations raised two issues: (1) could PCR conditions be modified to reduce such artifacts? and (2) could some of the rare alleles listed in the IMGT/HLA database be artifacts rather than true alleles? Because PCR crossing over occurs during late cycles of PCR, we compared DRB genotypes resulting from 28 and (our standard) 35 cycles of PCR. For all 21 cell line DNAs amplified for 35 cycles, crossover products were detected. In 33% of the cases, these hybrid sequences corresponded to named alleles. With amplification for only 28 cycles, these artifactual sequences were not detectable. To investigate whether some rare alleles in the IMGT/HLA database might be due to PCR artifacts, we analyzed four samples obtained from the investigators who submitted the sequences. In three cases, the sequences were generated from true alleles. In one case, our 454 sequencing revealed an error in the previously submitted sequence.
[Show abstract][Hide abstract] ABSTRACT: Historically, association of disease with the major histocompatibility complex (HLA) genes has been tested with HLA alleles that encode antigen-binding affinity. The association with Parkinson disease (PD), however, was discovered with noncoding SNPs in a genome-wide association study (GWAS). We show here that several HLA-region SNPs that have since been associated with PD form two blocks tagged by rs3129882 (p = 9 × 10(-11)) and by rs9268515 and/or rs2395163 (p = 3 × 10(-11)). We investigated whether these SNP-associations were driven by HLA-alleles at adjacent loci. We imputed class I and class II HLA-alleles for 2000 PD cases and 1986 controls from the NeuroGenetics Research Consortium GWAS and sequenced a subset of 194 cases and 204 controls. We were therefore able to assess accuracy of two imputation algorithms against next-generation-sequencing while taking advantage of the larger imputed data sets for disease study. Additionally, we imputed HLA alleles for 843 cases and 856 controls from another GWAS for replication. PD risk was positively associated with the B(∗)07:02_C(∗)07:02_DRB5(∗)01_DRB1(∗)15:01_DQA1(∗)01:02_DQB1(∗)06:02 haplotype and negatively associated with the C(∗)03:04, DRB1(∗)04:04 and DQA1(∗)03:01 alleles. The risk haplotype and DQA1(∗)03:01 lost significance when conditioned on the SNPs, but C(∗)03:04 (OR = 0.72, p = 8 × 10(-6)) and DRB1(∗)04:04 (OR = 0.65, p = 4 × 10(-5)) remained significant. Similarly, rs3129882 and the closely linked rs9268515 and rs2395163 remained significant irrespective of HLA alleles. rs3129882 and rs2395163 are expression quantitative trait loci (eQTLs) for HLA-DR and HLA-DQ (9 × 10(-5) ≥ PeQTL ≥ 2 × 10(-79)), suggesting that HLA gene expression might influence PD. Our data suggest that PD is associated with both structural and regulatory elements in HLA. Furthermore, our study demonstrates that noncoding SNPs in the HLA region can be associated with disease irrespective of HLA alleles, and that observed associations with HLA alleles can sometimes be secondary to a noncoding variant.
The American Journal of Human Genetics 10/2013; 93(5). DOI:10.1016/j.ajhg.2013.10.009 · 10.93 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Aim
Next generation sequencing of HLA exonic amplicons with the 454 Life Sciences GS FLX System and Conexio AssignTM-ATF software provides high resolution, high throughput HLA genotyping for 8 class I and class II loci (Bentley et al., 20091, Holcomb et al., 20112). HLA typing of potential donors for Unrelated Bone Marrow Donor Registries requires using a subset of these loci at high sample throughput and low cost per sample. To maximize the throughput, we have incorporated the Fluidigm® Access ArrayTM system to simplify amplicon library preparation and allow the efficient introduction of MIDs (Multiplex Identifiers) or barcodes.
For this application, a streamlined amplicon sequencing workflow employing many different Multiplex Identifiers (MIDs) enables multiplexed sequencing of a large number of samples, allowing researchers to meet these cost targets. The Fluidigm® 48 x 48 Access ArrayTM system and the “4 primer” approach provides an efficient way to achieve parallel semi-automated genomic PCRs with simultaneous incorporation of 48 different MIDs corresponding to 48 genomic DNA samples, and up to 48 different primer pairs, making possible 2,304 reactions in one amplification run. Minimal volumes (calculated to be about 45% less cost per run) of reagents are used in this micro- fluidics-based system. During genomic PCR, the outer set of primers containing the MIDs and the 454 adaptor sequences are incorporated into the amplicons generated by the inner set of HLA specific primers containing a complementary “universal” Fluidigm tag. Pools of the resulting amplicons are used for emulsion PCR and clonal sequencing on the 454 GS FLX System, as well as genotyping with Conexio AssignTM-ATF software.
Using the Access Array system, we have successfully (100% concordance with known genotypes) genotyped 192 samples with 8 primer pairs (covering exons 2 and 3 in HLA-A, B, C and Exon 2 in DRB1, DRB3/4/5 and DQB1) using 96 MIDs per region in a single GS FLX run on a 2 region PicoTiterPlate™ (PTP) and 96 samples using 48 MIDs per region in a 4 region PTP. An average of 166 and 137 sequence reads per amplicon were recovered respectively. We have also genotyped, in a single run, 96 samples at high resolution (14 primer pairs covering exons 2, 3, and 4 of the class I loci and exons 2 of DRB1,3/4/5, DQA1, DQB1, DPB1, and exon 3 of DQB1) recovering an average of 175 sequence reads per amplicon at 100% concordance. The system reduces the overall time for the entire process (192 samples) from 8 days for manual processing to about 4 days with 1 FTE.
[Show abstract][Hide abstract] ABSTRACT: OBJECTIVE
This study assessed the ability to distinguish between type 1 diabetes-affected individuals and their unaffected relatives using HLA and single nucleotide polymorphism (SNP) genotypes.RESEARCH DESIGN AND METHODS
Eight models, ranging from only the high-risk DR3/DR4 genotype to all significantly associated HLA genotypes and two SNPs mapping to the cytotoxic T-cell-associated antigen-4 gene (CTLA4) and insulin (INS) genes, were fitted to high-resolution class I and class II HLA genotyping data for patients from the Type 1 Diabetes Genetics Consortium collection. Pairs of affected individuals and their unaffected siblings were divided into a "discovery" (n = 1,015 pairs) and a "validation" set (n = 318 pairs). The discriminating performance of various combinations of genetic information was estimated using receiver operating characteristic (ROC) curve analysis.RESULTSThe use of only the presence or absence of the high-risk DR3/DR4 genotype achieved very modest discriminating ability, yielding an area under the curve (AUC) of 0.62 in the discovery set and 0.59 in the validation set. The full model, which included HLA information from the class II loci DPB1, DRB1, DQB1, selected alleles from HLA class I loci A and B, and SNPs from the CTLA4 and INS genes, increased the AUC to 0.74 in the discovery set and to 0.71 in the validation set. A cost-effective alternative is proposed, using genotype information equivalent to typing four SNPs (DR3, DR4-DQB1*03:02, CTLA-4, and INS), which achieved an AUC of 0.72 in the discovery set and 0.69 in the validation set.CONCLUSIONS
Genotyping data sufficient to tag DR3, DR4-DQB1*03:02, CTLA4, and INS was shown to distinguish between subjects with type 1 diabetes and their unaffected siblings adequately to achieve clinically utility to identify children in multiplex families to be considered for early intervention.
Diabetes care 04/2013; 36(9). DOI:10.2337/dc12-2284 · 8.42 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The primary associations of the HLA class II genes, HLA-DRB1 and HLA-DQB1, and the class I genes, HLA-A and HLA-B, with type 1 diabetes (T1D) are well established. However, the role of polymorphism at the HLA-DRB3, HLA-DRB4, and HLA-DRB5 loci remains unclear. In two separate studies, one of 500 cases and 500 controls and one of 366 DRB1*03:01-positive samples from selected multiplex T1D families, we used Roche 454 sequencing with Conexio Genomics ASSIGN™ATF HLA genotyping software analysis to analyze sequence variation at these three HLA-DRB loci. Association analyses were performed on the two HLA-DRB locus (DRB1-DRB3, -DRB4, or -DRB5) haplotypes. Three common HLA-DRB3 alleles (*01:01, *02:02, *03:01) were observed. DRB1*03:01 haplotypes carrying DRB3*02:02 conferred a higher (p=0.033) T1D risk than did DRB1*03:01 haplotypes carrying DRB3*01:01, primarily in DRB1*03:01/*03:01 homozygotes with two DRB3*01:01 alleles (OR = 3.4 95% CI= 1.46-8.09), compared with those carrying one or two DRB3*02:02 alleles (OR = 25.5; 95% CI - 3.43-189.2). For DRB1*03:01/*04:01 heterozygotes, however, the HLA-DRB3 allele did not significantly modify the T1D risk of the DRB1*03:01 haplotype (OR = 7.7 for *02:02; OR = 6.8 for *01:01). These observations were confirmed by sequence analysis of HLA-DRB3 exon 2 in a targeted replication study of 280 informative T1D family members and 86 Affected Family Based Control (AFBAC) haplotypes. The frequency of DRB3*02:02 was 42.9% in the DRB1*03:01/*03:01 patients and 27.6% in the DRB1*03:01/*04 (p = 0.005), compared to 22.6% in AFBAC DRB1*03:01 chromosomes (p = 0.001). Analysis of T1D associated alleles at other HLA loci (HLA-A, HLA-B and HLA-DPB1) on DRB1*03:01 haplotypes suggests that DRB3*02:02 on the DRB1*03:01 haplotype can contribute to T1D risk.
[Show abstract][Hide abstract] ABSTRACT: The human leukocyte antigen (HLA) class I and class II loci are the most polymorphic genes in the human genome; distinguishing the thousands of HLA alleles is challenging. Next generation sequencing of exonic amplicons with the 454 genome sequence (GS) FLX System and Conexio Assign ATF 454 software provides high resolution, high throughput HLA genotyping for eight class I and class II loci. HLA typing of potential donors for unrelated bone marrow donor registries typically uses a subset of these loci at high sample throughput and low cost per sample. The Fluidigm Access Array System enables the incorporation of 48 different multiplex identifiers (MIDs) corresponding to 48 genomic DNA samples with up to 48 different primer pairs in a microfluidic device generating 2304 parallel polymerase chain reactions (PCRs). Minimal volumes of reagents are used. During genomic PCR, in this 4-primer system, the outer set of primers containing the MID and the 454 adaptor sequences are incorporated into an amplicon generated by the inner HLA target-specific primers each containing a common sequence tag at the 5' end of the forward and reverse primers. Pools of the resulting amplicons are used for emulsion PCR and clonal sequencing on the 454 Life Sciences GS FLX System, followed by genotyping with Conexio software. We have genotyped 192 samples with 100% concordance to known genotypes using 8 primer pairs (covering exons 2 and 3 of HLA-A, B and C, and exon 2 of DRB1, 3/4/5 and DQB1) and 96 MIDs in a single GS FLX run. An average of 166 reads per amplicon was obtained. We have also genotyped 96 samples at high resolution (14 primer pairs covering exons 2, 3, and 4 of the class I loci and exons 2 of DRB1, 3/4/5, DQA1, DQB1, DPB1, and exon 3 of DQB1), recovering an average of 173 sequence reads per amplicon.
[Show abstract][Hide abstract] ABSTRACT: Human leucocyte antigen (HLA) genes play an important role in the success of organ transplantation and are associated with autoimmune and infectious diseases. Current DNA-based genotyping methods, including Sanger sequence-based typing (SSBT), have identified a high degree of polymorphism. This level of polymorphism makes high-resolution HLA genotyping challenging, resulting in ambiguous typing results due to an inability to resolve phase and/or defining polymorphisms lying outside the region amplified. Next-generation sequencing (NGS) may resolve the issue through the combination of clonal amplification, which provides phase information, and the ability to sequence larger regions of genes, including introns, without the additional effort or cost associated with current methods. The NGS HLA sequencing project of the 16IHIW aimed to discuss the different approaches to (i) template preparation including short- and long-range PCR amplicons, exome capture and whole genome; (ii) sequencing platforms, including GS 454 FLX, Ion Torrent PGM, Illumina MiSeq/HiSeq and Pacific Biosciences SMRT; (iii) data analysis, specifically allele-calling software. The pilot studies presented at the workshop demonstrated that although individual sequencers have very different performance characteristics, all produced sequence data suitable for the resolution of HLA genotyping ambiguities. The developments presented at this workshop clearly highlight the potential benefits of NGS in the HLA laboratory.
International Journal of Immunogenetics 02/2013; 40(1):72-6. DOI:10.1111/iji.12024 · 1.25 Impact Factor