Genotyping of classical human leukocyte antigen (HLA) alleles is an essential tool in the analysis of diseases and adverse drug reactions with associations mapping to the major histocompatibility complex (MHC). However, deriving high-resolution HLA types subsequent to whole-genome single-nucleotide polymorphism (SNP) typing or sequencing is often cost prohibitive for large samples. An alternative approach takes advantage of the extended haplotype structure within the MHC to predict HLA alleles using dense SNP genotypes, such as those available from genome-wide SNP panels. Current methods for HLA imputation are difficult to apply or may require the user to have access to large training data sets with SNP and HLA types. We propose HIBAG, HLA Imputation using attribute BAGging, that makes predictions by averaging HLA-type posterior probabilities over an ensemble of classifiers built on bootstrap samples. We assess the performance of HIBAG using our study data (n=2668 subjects of European ancestry) as a training set and HLA data from the British 1958 birth cohort study (n≈1000 subjects) as independent validation samples. Prediction accuracies for HLA-A, B, C, DRB1 and DQB1 range from 92.2% to 98.1% using a set of SNP markers common to the Illumina 1M Duo, OmniQuad, OmniExpress, 660K and 550K platforms. HIBAG performed well compared with the other two leading methods, HLA*IMP and BEAGLE. This method is implemented in a freely available HIBAG R package that includes pre-fit classifiers for European, Asian, Hispanic and African ancestries, providing a readily available imputation approach without the need to have access to large training data sets.
HLA; MHC; imputation; GWAS; HLA*IMP; BEAGLE
Located on Chromosome 6p21, classical human leukocyte antigen genes are highly polymorphic. HLA alleles associate with a variety of phenotypes, such as narcolepsy, autoimmunity, as well as immunologic response to infectious disease. Moreover, high resolution genotyping of these loci is critical to achieving long-term survival of allogeneic transplants. Development of methods to obtain high resolution analysis of HLA genotypes will lead to improved understanding of how select alleles contribute to human health and disease risk. Genomic DNAs were obtained from a cohort of n = 383 subjects recruited as part of an Ulcerative Colitis study and analyzed for HLA-DRB1. HLA genotypes were determined using sequence specific oligonucleotide probes and by next-generation sequencing using the Roche/454 GSFLX instrument. The Clustering and Alignment of Polymorphic Sequences (CAPSeq) software application was developed to analyze next-generation sequencing data. The application generates HLA sequence specific 6-digit genotype information from next-generation sequencing data using MUMmer to align sequences and the R package diffusionMap to classify sequences into their respective allelic groups. The incorporation of Bootstrap Aggregating, Bagging to aid in sorting of sequences into allele classes resulted in improved genotyping accuracy. Using Bagging iterations equal to 60, the genotyping results obtained using CAPSeq when compared with sequence specific oligonucleotide probe characterized 4-digit genotypes exhibited high rates of concordance, matching at 759 out of 766 (99.1%) alleles.
Persistent infection with high-risk human papillomavirus (HPV) is a major risk factor for malignant lesions and cervical cancer. A widely studied element in the search for genetic factors influencing risk HPV infection diseases is allelic variation of the human leukocyte antigen (HLA) locus. The study was designed to search for HLA susceptibility alleles contributing to the persistence of HPV infection in Mexican women.
A total of 172 subjects were divided into three groups: 1) HPV–persistent patients; 2) HPV–cleared; and 3) HPV–reinfected patients. They were screened for HPV types using a polymerase chain reaction (PCR). PCR-sequence specific oligonucleotide probes (PCR-SSOP) was used for HLA DRB1 and DQB1 typing.
We observed that HLA-DQB1*0501 allele might be associated with susceptibility of reinfection with HPV (p = 0.01, OR = 4.9, CI 95% = 1.3 -18.7). Allele frequency of HLA-DRB1*14 was particularly reduced in patients with cancer when compared with the HPV–persistent group (p = 0.04), suggesting that this allele is a possible protective factor for the development of cervical cancer (OR = 2.98). HLA-DRB1*07 might be associated with viral clearance (p = 0.04).
Genetic markers for HPV infection susceptibility are different in each population, in Mexicans several HLA-DQB1 alleles might be associated with an enhanced risk for viral persistence. In contrast, DRB1*14, seems to confer protection against cervical cancer.
HPV; HLA class II; Susceptibility; Persistent infection; DRB1
Correctly matching the HLA haplotypes of donor and recipient is essential to the success of allogenic hematopoietic stem cell transplantation. Current HLA typing methods rely on targeted testing of recognized antigens or sequences. Despite advances in Next Generation Sequencing, general high throughput transcriptome sequencing is currently underutilized for HLA haplotyping due to the central difficulty in aligning sequences within this highly variable region. Here we present the method, HLAforest, that can accurately predict HLA haplotype by hierarchically weighting reads and using an iterative, greedy, top down pruning technique. HLAforest correctly predicts >99% of allele group level (2 digit) haplotypes and 93% of peptide-level (4 digit) haplotypes of the most diverse HLA genes in simulations with read lengths and error rates modeling currently available sequencing technology. The method is very robust to sequencing error and can predict 99% of allele-group level haplotypes with substitution rates as high as 8.8%. When applied to data generated from a trio of cell lines, HLAforest corroborated PCR-based HLA haplotyping methods and accurately predicted 16/18 (89%) major class I genes for a daughter–father-mother trio at the peptide level. Major class II genes were predicted with 100% concordance between the daughter–father-mother trio. In fifty HapMap samples with paired end reads just 37 nucleotides long, HLAforest predicted 96.5% of allele group level HLA haplotypes correctly and 83% of peptide level haplotypes correctly. In sixteen RNAseq samples with limited coverage across HLA genes, HLAforest predicted 97.7% of allele group level haplotypes and 85% of peptide level haplotypes correctly.
The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.
The present study was aimed to analyze the frequencies of human leukocyte antigen (HLA)-A, -B, and -DRB1 alleles and A-B-DRB1, A-B, A-DRB1 and B-DRB1 haplotypes in inhabitants of Guizhou province, China. All samples were typed in the HLA-A,-B, and -DRB1 loci using the polymerase chain reaction-reverse sequence specific oligonucleotide probe (PCR-rSSOP) method and HLA polymorphisms were analyzed. A total of 18 HLA-A, 31 HLA-B, and 13 HLA-DRB1 alleles were found in the Guizhou population. The first two frequent alleles in the HLA-A, -B, and -DRB1 loci were A*11(30.72%) and A*02(30.65%), B*40(16.27%) and B*46(16.27%), and DRB1*09(15.91%) and DRB1*15(13.51%), respectively. The most common haplotype was A*02-B*46-DRB1*09(5.59%) in A-B-DRB1, A*02-B*46(11.73%) in A-B, B*46-DRB1*09(7.49%) in B-DRB1, and A*02-DRB1*09(8.08%) in A-DRB1. Some haplotypes with strong linkage disequilibrium (LD) were found not only in the common haplotypes, such as A*33-B*58, B*30-DRB1*07, and B*33-DRB1*03, but also in the rare haplotypes, such as A*01-B*37, B*37-DRB1*10, and A*01-DRB1*10. Guizhou inhabitants shared some characteristics of the Southern Chinese population but also had their own unique features. Overall, HLA polymorphism in Guizhou population was more consistent with that of Chengdu population than that of other populations in China.
human leukocyte antigen; allele; haplotype; linkage; disequilibrium; Guizhou
Follicular lymphoma (FL) is an indolent, sometimes fatal disease characterized by recurrence at progressively shorter intervals and is frequently refractive to therapy. Genome-wide association studies have identified SNPs in the human leukocyte antigen (HLA) region on chromosome 6p21.32–33 that are statistically significantly associated with FL risk. Low to medium resolution typing of single or multiple HLA genes has provided an incomplete picture of the total genetic risk imparted by this highly variable region. To gain further insight into the role of HLA alleles in lymphomagenesis and to investigate the independence of validated SNPs and HLA alleles with FL risk, high-resolution HLA typing was conducted using next-generation sequencing in 222 non-Hispanic white FL cases and 220 matched controls from a larger San Francisco Bay Area population-based case-control study of lymphoma. A novel protective association was found between the DPB1*03:01 allele and FL risk (OR=0.39, 95% CI 0.21–0.68). Extended haplotypes DRB1*01:01-DQA1*01:01-DQB1*05:01 (OR=2.01, 95% CI 1.22–3.38) and DRB1*15-DQA1*01-DQB1*06 (OR=0.55, 95% CI 0.36–0.82) also influenced FL risk. Moreover, DRB1*15-DQA1*01-DQB1*06 was highly correlated with an established FL risk locus, rs2647012. These results provide further insight into the critical roles of HLA alleles and SNPs in FL pathogenesis that involve multi-locus effects across the HLA region.
follicular lymphoma; HLA; genetic risk factors; next-generation sequencing
HLA, the most genetically diverse loci in the human genome, play a crucial role in host-pathogen interaction by mediating innate and adaptive cellular immune responses. A vast number of infectious diseases affect East Africa, including HIV/AIDS, malaria, and tuberculosis, but the HLA genetic diversity in this region remains incompletely described. This is a major obstacle for the design and evaluation of preventive vaccines. Available HLA typing techniques, that provide the 4-digit level resolution needed to interpret immune responses, lack sufficient throughput for large immunoepidemiological studies. Here we present a novel HLA typing assay bridging the gap between high resolution and high throughput. The assay is based on real-time PCR using sequence-specific primers (SSP) and can genotype carriers of the 49 most common East African class I HLA-A, -B, and -C alleles, at the 4-digit level. Using a validation panel of 175 samples from Kampala, Uganda, previously defined by sequence-based typing, the new assay performed with 100% sensitivity and specificity. The assay was also implemented to define the HLA genetic complexity of a previously uncharacterized Tanzanian population, demonstrating its inclusion in the major East African genetic cluster. The availability of genotyping tools with this capacity will be extremely useful in the identification of correlates of immune protection and the evaluation of candidate vaccine efficacy.
We report the efficient identification of four human histocompatibility leukocyte antigen (HLA)-A*0201–presented cytotoxic T lymphocyte (CTL) epitopes in the tumor-associated antigen PRAME using an improved “reverse immunology” strategy. Next to motif-based HLA-A*0201 binding prediction and actual binding and stability assays, analysis of in vitro proteasome-mediated digestions of polypeptides encompassing candidate epitopes was incorporated in the epitope prediction procedure. Proteasome cleavage pattern analysis, in particular determination of correct COOH-terminal cleavage of the putative epitope, allows a far more accurate and selective prediction of CTL epitopes. Only 4 of 19 high affinity HLA-A*0201 binding peptides (21%) were found to be efficiently generated by the proteasome in vitro. This approach avoids laborious CTL response inductions against high affinity binding peptides that are not processed and limits the number of peptides to be assayed for binding. CTL clones induced against the four identified epitopes (VLDGLDVLL, PRA100–108; SLYSFPEPEA, PRA142–151; ALYVDSLFFL, PRA300–309; and SLLQHLIGL, PRA425–433) lysed melanoma, renal cell carcinoma, lung carcinoma, and mammary carcinoma cell lines expressing PRAME and HLA-A*0201. This indicates that these epitopes are expressed on cancer cells of diverse histologic origin, making them attractive targets for immunotherapy of cancer.
antigen presentation; antigen processing; cytotoxic T lymphocyte induction; human histocompatibility leukocyte antigen class I binding; tumor immunotherapy
Targeted capture of large fragments of genomic DNA that enrich for human leukocyte antigen (HLA) system haplotypes has utility in haematopoietic stem cell transplantation. Current methods of HLA matching are based on inference or familial studies of inheritance; and each approach has its own inherent limitations. We have designed and tested a probe–target-extraction method for capturing specific HLA haplotypes by hybridization of peptide nucleic acid (PNA) probes to alleles of the HLA-DRB1 gene. Short target fragments contained in plasmids were initially used to optimize the method followed by testing samples of genomic DNA from human subjects with preselected HLA haplotypes and obtained approximately 10% enrichment for the specific haplotype. When performed with high-molecular-weight genomic DNA, 99.0% versus 84.0% alignment match was obtained for the specific haplotype probed. The allele-specific target enrichment that we obtained can facilitate the elucidation of haplotypes between the 65 kb separating the HLA-DRB1 and the HLA-DQA1 genes, potentially spanning a total distance of at least 130 kb. Allele-specific target enrichment with PNA probes is a straightforward technique that has the capability to improve the resolution of DNA and whole genome sequencing technologies by allowing haplotyping of enriched DNA and crucially, retaining the DNA methylation profile.
Haplotyping; HLA haplotype; HLA matching; HLA-DRB1; peptide nucleic acid
Killer Immunoglobulin-like Receptors (KIRs) are surface receptors of natural killer cells that bind to their corresponding Human Leukocyte Antigen (HLA) class I ligands, making them interesting candidate genes for HLA-associated autoimmune diseases, including type 1 diabetes (T1D). However, allelic and copy number variation in the KIR region effectively mask it from standard genome-wide association studies: single nucleotide polymorphism (SNP) probes targeting the region are often discarded by standard genotype callers since they exhibit variable cluster numbers. Quantitative Polymerase Chain Reaction (qPCR) assays address this issue. However, their cost is prohibitive at the sample sizes required for detecting effects typically observed in complex genetic diseases.
We propose a more powerful and cost-effective alternative, which combines signals from SNPs with more than three clusters found in existing datasets, with qPCR on a subset of samples. First, we showed that noise and batch effects in multiplexed qPCR assays are addressed through normalisation and simultaneous copy number calling of multiple genes. Then, we used supervised classification to impute copy numbers of specific KIR genes from SNP signals. We applied this method to assess copy number variation in two KIR genes, KIR3DL1 and KIR3DS1, which are suitable candidates for T1D susceptibility since they encode the only KIR molecules known to bind with HLA-Bw4 epitopes. We find no association between KIR3DL1/3DS1 copy number and T1D in 6744 cases and 5362 controls; a sample size twenty-fold larger than in any previous KIR association study. Due to our sample size, we can exclude odds ratios larger than 1.1 for the common KIR3DL1/3DS1 copy number groups at the 5% significance level.
We found no evidence of association of KIR3DL1/3DS1 copy number with T1D, either overall or dependent on HLA-Bw4 epitope. Five other KIR genes, KIR2DS4, KIR2DL3, KIR2DL5, KIR2DS5 and KIR2DS1, in high linkage disequilibrium with KIR3DL1 and KIR3DS1, are also unlikely to be significantly associated. Our approach could potentially be applied to other KIR genes to allow cost effective assaying of gene copy number in large samples.
KIR3DL1; KIR3DS1; KIR2DS4; KIR2DL3; KIR2DL5; KIR2DS5; KIR2DS1; HLA-Bw4; CNV; qPCR; ImmunoChip; KIR; Imputation; T1D
Human leukocyte antigen (HLA) alleles code for proteins that are involved in the recognition of foreign antigens and activation of the immune system. The frequency of HLA alleles varies across different populations.
To describe the frequency of HLA alleles in a population of Inuit women of Nunavik, Quebec, Canada.
A cohort of women was recruited from 4 different communities between January 2002 and December 2007. HLA-B*07, HLA-DQB1*03, DQB1*06:02, DRB1*13 and DRB1*15:01 alleles were typed by PCR sequence-specific primers (PCR-SSP) and HLA-E and G alleles were type by DNA-sequencing procedures.
We obtained data on 524 participants. The most frequent HLA alleles in this population were HLA-E*01:03, HLA-G*01:04:01 and HLA-DQB1*03, and they were found in 89, 75 and 94% of the population, respectively.
The distribution of HLA alleles in Nunavik, Quebec is unique when compared to other populations in Canada or around the world.
human leukocyte antigen; Inuit; Nunavik; Canada
A novel approach to DNA probe hybridization and heteroduplex analysis, termed directed heteroduplex analysis (DHDA) is presented here to illustrate its utility in simplification of human lymphocyte antigen (HLA)-typing. By strategic labeling of single-stranded probe sequences, DHDA allows the identification of specific heteroduplex structures that contribute to the differentiation of DQA1 and DQB1 alleles. Because of the high degree of polymorphism among major histocompatibility complex class II second exon sequences, this analysis of 50 different heteroduplex molecules provides evidence of the importance of unpaired bases and mismatched base pairs and their effect on heteroduplex electrophoretic-mobility differences. This strategy is further used to genotype accurately a family for DQA1 which was previously analyzed by sequence specific oligonucleotide (SSO) probe hybridization. To differentiate by SSO-typing among the DQA1 and DQB1 alleles analyzed in this study requires the use of 23 different probes. Equivalent results are obtained by DHDA using only three probes. Therefore, this study suggests that accurate HLA-typing can be simplified by DHDA. Additionally, DHDA may be useful for differentiation of DNA sequence polymorphisms in other genetic systems.
Human leukocyte antigen A (HLA-A) genotypes were determined for samples from 283 multiplex, Caucasian, type 1 diabetes families from the Human Biological Data Interchange (HBDI) using an immobilized probe assay. Distribution of HLA-A alleles transmitted to patients was significantly different from that in affected family-based controls (AFBAC) (p = 0.004). Transmission disequilibrium test (TDT) analysis revealed differential transmission of several HLA-A alleles from parents to affected offspring. HLA class II DRB1 and DQB1 loci were also typed, allowing assignment of HLA-A alleles to haplotypes and calculation of linkage disequilibrium values. Some of the apparent effects of HLA-A alleles on type 1 diabetes susceptibility were attributable to linkage disequilibrium with DR and DQ alleles, although others were not. The differences in frequencies between patients and controls of alleles A*0101, A*2402, and A*3002 could not be explained by linkage disequilibrium alone. Our results suggest an important role for class I antigens in modulating susceptibility to type 1 diabetes.
HLA-A genotypes; type 1 diabetes
Normal tension glaucoma (NTG) is a subtype of glaucoma in which intraocular pressure is within the statistically normal range. NTG may be associated with an immune disorder. The aim of this study was to determine whether specific alleles in the human leukocyte antigen (HLA)-DRB1 and HLA-DQB1 genes correlated with NTG in Japanese patients.
We genotyped the HLA-DRB1 and HLA-DQB1 alleles in 113 Japanese patients with NTG and in 184 healthy Japanese control subjects using the polymerase chain reaction-sequence-specific oligonucleotide probes (PCR-SSOP) Luminex method. We assessed the allelic diversity in patients and controls.
There were no statistically significant differences in the allele frequency of HLADRB1 and HLA-DQB1 between NTG patients and control subjects, and no HLA-DRB1-HLA-DQB1 haplotypes demonstrated any significant association with NTG.
Our findings suggest that HLA-DRB1 and HLA-DQB1 polymorphisms have no significant effect on the development of NTG in Japanese patients.
We present a method, seq2HLA, for obtaining an individual's human leukocyte antigen (HLA) class I and II type and expression using standard next generation sequencing RNA-Seq data. RNA-Seq reads are mapped against a reference database of HLA alleles, and HLA type, confidence score and locus-specific expression level are determined. We successfully applied seq2HLA to 50 individuals included in the HapMap project, yielding 100% specificity and 94% sensitivity at a P-value of 0.1 for two-digit HLA types. We determined HLA type and expression for previously un-typed Illumina Body Map tissues and a cohort of Korean patients with lung cancer. Because the algorithm uses standard RNA-Seq reads and requires no change to laboratory protocols, it can be used for both existing datasets and future studies, thus adding a new dimension for HLA typing and biomarker studies.
The human leukocyte antigens (HLAs) are proteins found in the membranes of nearly all nucleated cells. People with certain HLA antigens are more likely to develop certain autoimmune diseases. The aim of this study was to determine the frequency of HLA-DRB1 in children with autoimmune hepatitis (AIH) as a risk factor for occurrence, its relation to preceding hepatitis A infection and treatment outcome.
Subjects and methods
25 children with AIH were subjected to HLA-DRB 1 typing performed by sequence specific oligonucleotide probe technique and compared to HLA-DRB1 found in 548 normal populations.
The most frequent alleles found in our children with AIH were HLA-DRB1*13 (36%), HLA-DRB1*04 (18%) and HLA-DRB1*03 (14%). HLA-DRB1*13 was significantly more frequent in AIH patients compared to controls. In type I AIH patients HLA-DRB1*13 was the most frequent allele (32.4%), followed by HLA-DRB1*04 in (20.6%) and HLA-DRB1*03 in (14.7%), While in type II, the most frequent alleles were HLA-DRB1*13 in (40%), HLA-DRB1*07 (20%) and HLA-DRB1*15 in (20%). HLA-DRB1*12 was significantly more frequent in AIH patients with positive Hepatitis A IgM than in patients with negative hepatitis A IgM. No statistically significant difference between partial responders and complete responders to treatment as regards HLA-DRB1 subtypes.
It is concluded from the previous study that HLA-DRB1*13 may be a susceptibility allele for the occurrence of autoimmune hepatitis in our population. HLA-DRB1*07 and HLA-DRB1*15 may be susceptibility alleles for occurrence of autoimmune hepatitis type 2. HLA-DRB1*12 association with AIH in patients triggered by hepatitis A needs further studies.
DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C) and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.
Many autoimmune diseases share a genetic association with the presence or absence of HLA-DQB1*0602, including type I diabetes, multiple sclerosis, and narcolepsy. High resolution HLA typing to determine the presence of this allele is cumbersome and expensive by currently available techniques. We present a real-time PCR assay for the identification of HLA-DQB1*0602, using sequence-specific primers and probes, that provides rapid and sensitive identification of this allele, involves minimal hands-on time, and provides a major cost savings compared to existing methods. The assay allows the simultaneous determination of both the presence and the number of copies of this allele. Since there is no post-PCR handling, the risk of contamination is avoided. We have validated the assay using 44 blinded and 32 unblinded samples, previously typed by standard techniques, which were identified with 100% accuracy, sensitivity, and specificity. Further, using a narcolepsy cohort of 734 subjects, we demonstrated the robustness of the assay to analyze DNA isolated from buccal swabs, demonstrating the applicability of this assay as an alternative approach to traditional HLA typing methods.
Genotyping; HLA-DQB1*0602; HLA typing; Multiple Sclerosis; Narcolepsy; QPCR-SSPP; Real-time PCR; Systemic Lupus Erythematosus; TaqMan; Type 1 Diabetes Mellitus
BACKGROUND AND OBJECTIVES:
Analysis of the role of different alleles of human leukocyte antigen (HLA) in rheumatoid arthritis (RA) patients is necessary in many populations and geographical areas. The aim of the present study was to investigate the frequency of HLA-DRB1 alleles in RA patients, comparing with that in control group in southeast Iran.
DESIGN AND SETTING:
Case-control study of rheumatoid arthritis patients referred to rheumatology clinic at university hospital.
PATIENTS AND METHODS:
The frequency of HLA-DRB1 alleles was determined in 79 RA patients and 93 healthy subjects in Zahedan, southeast Iran. HLA-DRB1 allele types were identified by polymerase chain reaction with sequence-specific primer (PCR-SSP).
The HLA-DRB1*10 allele showed a significantly higher frequency in patients with RA (OR=2.698, 95% CI=1.087-6.699, P=.045), while the frequency of DRB1*03 allele in these subjects was significantly lower than that in the control group (OR=0.447, 95% CI=0.2285-0.8729, P=.021). The frequencies of DRB1*01, DRB1*04, DRB1*07, DRB1*09, DRB1*11, DRB1*13, DRB1*14, DRB1*15, DRB1*16 were not significantly different between RA subjects and the control group.
The data suggest that the DRB1*10 allele is a risk factor and DRB1*03 is protective for RA in this population.
The pathogenesis of classical Hodgkin lymphoma (cHL) involves environmental and genetic factors. To explore the role of the human leukocyte antigen (HLA) genes, we performed a case-control genotyping study in 338 Dutch cHL patients using a PCR-based sequence-specific oligonucleotide probe (SSOP) hybridization approach. The allele frequencies were compared to HLA typings of more than 6,000 controls. The age of the cHL patients varied between 13 and 81 years with a median of 35 years. Nodular sclerosis subtype was the most common subtype (87%) and EBV was detected in 25% of the cHL patients. HLA-B5 was significantly increased and HLA-DR7 significantly decreased in the total cHL patient population as compared to controls. Two class II associations were observed to be specific for the EBV− cHL population with an increase of HLA-DR2 and HLA-DR5. Allele frequencies of HLA-A1, HLA-B37 and HLA-DR10 were significantly increased in the EBV+ cHL population; these alleles are in strong linkage disequilibrium and form a common haplotype in Caucasians. The allele frequency of HLA-A2 was significantly decreased in the EBV+ cHL population. Analysis of haplotypes with a frequency of >1% revealed a significant increase of HLA-A2-B7-DR2 in EBV− cHL as compared to controls. SSOP association analysis revealed significant differences between EBV+ and EBV− cHL patients for 19 probes that discriminate between HLA-A*01 and HLA-A*02. In conclusion, the HLA-A1 and HLA-A2 antigens and not specific single nucleotide variants shared by multiple alleles are responsible for the association with EBV+ cHL. Furthermore several new protective and predisposing HLA class I and II associations for the EBV+, the EBV− and the entire cHL population were identified.
Genetic variation associated with human leukocyte antigen (HLA) genes has immunological functions and is associated with autoimmune diseases. To date, large-scale studies involving classical HLA genes have been limited by time-consuming and expensive HLA-typing technologies. To reduce these costs, single-nucleotide polymorphisms (SNPs) have been used to predict HLA-allele types. Although HLA allelic distributions differ among populations, most prediction model of HLA genes are based on Caucasian samples, with few reported studies involving non-Caucasians.
Our sample consisted of 437 Han Chinese with Affymetrix 5.0 and Illumina 550 K SNPs, of whom 214 also had data on Affymetrix 6.0 SNPs. All individuals had HLA typings at a 4-digit resolution. Using these data, we have built prediction model of HLA genes that are specific for a Han Chinese population. To optimize our prediction model of HLA genes, we analyzed a number of critical parameters, including flanking-region size, genotyping platform, and imputation. Predictive accuracies generally increased both with sample size and SNP density.
SNP data from the HapMap Project are about five times more dense than commercially available genotype chip data. Using chips to genotype our samples, however, only reduced the accuracy of our HLA predictions by only ~3%, while saving a great deal of time and expense. We demonstrated that classical HLA alleles can be predicted from SNP genotype data with a high level of accuracy (80.37% (HLA-B) ~95.79% (HLA-DQB1)) in a Han Chinese population. This finding offers new opportunities for researchers in obtaining HLA genotypes via prediction using their already existing chip datasets. Since the genetic variation structure (e.g. SNP, HLA, Linkage disequilibrium) is different between Han Chinese and Caucasians, and has strong impact in building prediction models for HLA genes, our findings emphasize the importance of building ethnic-specific models when analyzing human populations.
Major histocompatibility complex (MHC); Human leukocyte antigen (HLA); Single-nucleotide polymorphisms (SNPs)
Background Although human leukocyte antigen (HLA) DQ and
DR loci appear to confer the strongest genetic risk for
type 1 diabetes, more detailed information is required for other loci within the
HLA region to understand causality and stratify additional risk factors. The
Type 1 Diabetes Genetics Consortium (T1DGC) study design included
high-resolution genotyping of HLA-A, B,
C, DRB1, DQ, and
DP loci in all affected sibling pair and trio families, and
cases and controls, recruited from four networks worldwide, for analysis with
clinical phenotypes and immunological markers.
Purpose In this article, we present the operational strategy of training,
classification, reporting, and quality control of HLA genotyping in four
laboratories on three continents over nearly 5 years.
Methods Methods to standardize HLA genotyping at eight loci included: central
training and initial certification testing; the use of uniform reagents,
protocols, instrumentation, and software versions; an automated data transfer;
and the use of standardized nomenclature and allele databases. We implemented a
rigorous and consistent quality control process, reinforced by repeated
workshops, yearly meetings, and telephone conferences.
Results A total of 15,246 samples have been HLA genotyped at eight loci to
four-digit resolution; an additional 6797 samples have been HLA genotyped at two
loci. The genotyping repeat rate decreased significantly over time, with an
estimated unresolved Mendelian inconsistency rate of 0.21%. Annual
quality control exercises tested 2192 genotypes (4384 alleles) and achieved
99.82% intra-laboratory and 99.68% inter-laboratory
Limitations The chosen genotyping platform was unable to distinguish many allele
combinations, which would require further multiple stepwise testing to resolve.
For these combinations, a standard allele assignment was agreed upon, allowing
further analysis if required.
Conclusions High-resolution HLA genotyping can be performed in multiple laboratories
using standard equipment, reagents, protocols, software, and communication to
produce consistent and reproducible data with minimal systematic error. Many of
the strategies used in this study are generally applicable to other large
Conditional ligands have enabled the high-throughput production of human leukocyte antigen (HLA) libraries that present defined peptides. Immunomonitoring platforms typically concentrate on restriction elements associated with European ancestry, and such tools are scarce for Asian HLA variants. We report 30 novel irradiation-sensitive ligands, specifically targeting South East Asian populations, which provide 93, 63, and 79% coverage for HLA-A, -B, and -C, respectively. Unique ligands for all 16 HLA types were constructed to provide the desired soluble HLA product in sufficient yield. Peptide exchange was accomplished for all variants as demonstrated by an ELISA-based MHC stability assay. HLA tetramers with redirected specificity could detect antigen-specific CD8+ T-cell responses against human cytomegalovirus, hepatitis B (HBV), dengue virus (DENV), and Epstein-Barr virus (EBV) infections. The potential of this population-centric HLA library was demonstrated with the characterization of seven novel T-cell epitopes from severe acute respiratory syndrome coronavirus, HBV, and DENV. Posthoc analysis revealed that the majority of responses would be more readily identified by our unbiased discovery approach than through the application of state-of-the-art epitope prediction. This flow cytometry-based technology therefore holds considerable promise for monitoring clinically relevant antigen-specific T-cell responses in populations of distinct ethnicity.
CD8+ T-cell response; Conditional ligand; Epitope mapping; HLA polymorphism; Immunotechnology
Many effective options exist to accurately type DNA for HLA alleles. However, most of the existing methods are excessively costly in terms of overall monetary costs, DNA requirements, and proprietary software. We present a novel assay able to resolve heterozygous HLA-DQB1 allelotypes at two digits, with even greater specificity for the HLA-DQB1*06 allele family, by using the multiplexed ligation-dependent probe amplification (MLPA) technology. This assay provides more specific allele data than genome-wide analysis and is more affordable than sequencing, making it a useful intermediate for researchers seeking to accurately allelotype human DNA samples.
DQB1; genotyping; MHC class II; MLPA