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Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified > 300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alíeles. These results implicate the nature of the HLA-viral peptide interaction as the major factor modulating durable control of HIV infection.

Previous studies have attempted to define human leukocyte antigen (HLA) class II supertypes, analogous to the case for class I, on the basis of shared peptide-binding motifs or structure. In the present study, we determined the binding capacity of a large panel of non-redundant peptides for a set of 27 common HLA DR, DQ, and DP molecules. The measured binding data were then used to define class II supertypes on the basis of shared binding repertoires. Seven different supertypes (main DR, DR4, DRB3, main DQ, DQ7, main DP, and DP2) were defined. The molecules associated with the respective supertypes fell largely along lines defined by MHC locus and reflect, in broad terms, commonalities in reported peptide-binding motifs. Repertoire overlaps between molecules within the same class II supertype were found to be similar in magnitude to what has been observed for HLA class I supertypes. Surprisingly, however, the degree to which repertoires between molecules in the different class II supertypes also overlapped was found to be five to tenfold higher than repertoire overlaps noted between molecules in different class I supertypes. These results highlight a high degree of repertoire overlap amongst all HLA class II molecules, perhaps reflecting binding in multiple registers, and more pronounced dependence on backbone interactions rather than peptide anchor residues. This fundamental difference between HLA class I and class II would not have been predicted on the basis of analysis of either binding motifs or the sequence/predicted structures of the HLA molecules.

Background Several recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data. Results HLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A , − B , and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing–based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A , − B , − C , − DQB1 , and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%. Conclusions HLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.

Whole genome comparisons identified introgression from archaic to modern humans. Our analysis of highly polymorphic human leukocyte antigen (HLA) class I, vital immune system components subject to strong balancing selection, shows how modern humans acquired the HLA-B*73 allele in west Asia through admixture with archaic humans called Denisovans, a likely sister group to the Neandertals. Virtual genotyping of Denisovan and Neandertal genomes identified archaic HLA haplotypes carrying functionally distinctive alleles that have introgressed into modern Eurasian and Oceanian populations. These alleles, of which several encode unique or strong ligands for natural killer cell receptors, now represent more than half the HLA alleles of modern Eurasians and also appear to have been later introduced into Africans. Thus, adaptive introgression of archaic alleles has significantly shaped modern human immune systems.

Aims/hypothesisThe aim of this study was to determine if retention of C-peptide following immunotherapy using recombinant GAD65 conjugated to aluminium hydroxide (GAD-alum) is influenced by HLA risk haplotypes DR3-DQ2 and DR4-DQ8.MethodsHLA-dependent treatment effect of GAD-alum therapy on C-peptide retention in individuals with recent-onset type 1 diabetes was evaluated using individual-level patient data from three placebo-controlled, randomised clinical trials using a mixed repeated measures model.ResultsA significant and dose-dependent effect was observed in individuals positive for the genotypes that include HLA-DR3-DQ2 but not HLA-DR4-DQ8 and in the broader subgroup of individuals positive for all genotypes that include HLA-DR3-DQ2 (i.e. including those also positive for HLA-DR4-DQ8). Higher doses (three or four injections) showed a treatment effect ratio of 1.596 (95% CI 1.132, 2.249; adjusted p = 0.0035) and 1.441 (95% CI 1.188, 1.749; adjusted p = 0.0007) vs placebo for the two respective HLA subgroups.Conclusions/interpretationGAD65-specific immunotherapy has a significant effect on C-peptide retention in individuals with recent-onset type 1 diabetes who have the DR3-DQ2 haplotype.

Human leukocyte antigen (HLA) genes are the most polymorphic in the human genome. They play a pivotal role in the immune response and have been implicated in numerous human pathologies, especially autoimmunity and infectious diseases. Despite their importance, however, they are rarely characterized comprehensively because of the prohibitive cost of standard technologies and the technical challenges of accurately discriminating between these highly related genes and their many allelles. Here we demonstrate a high-resolution, and cost-effective methodology to type HLA genes by sequencing, which combines the advantage of long-range amplification, the power of high-throughput sequencing platforms, and a unique genotyping algorithm. We calibrated our method for HLA-A, -B, -C, and -DRB1 genes with both reference cell lines and clinical samples and identified several previously undescribed alleles with mismatches, insertions, and deletions. We have further demonstrated the utility of this method in a clinical setting by typing five clinical samples in an Illumina MiSeq instrument with a 5-d turnaround. Overall, this technology has the capacity to deliver low-cost, high-throughput, and accurate HLA typing by multiplexing thousands of samples in a single sequencing run, which will enable comprehensive disease-association studies with large cohorts. Furthermore, this approach can also be extended to include other polymorphic genes.

Charles Paulding and colleagues report a genome-wide association study for susceptibility to lumiracoxib-induced liver injury. The study utilized lumiracoxib-treated cases with liver injury and lumiracoxib-treated controls, and included independent replication. The authors identify an association to a common HLA haplotype. Lumiracoxib is a selective cyclooxygenase-2 inhibitor developed for the symptomatic treatment of osteoarthritis and acute pain 1 . Concerns over hepatotoxicity have contributed to the withdrawal or non-approval of lumiracoxib in most major drug markets worldwide. We performed a case-control genome-wide association study on 41 lumiracoxib-treated patients with liver injury (cases) and 176 matched lumiracoxib-treated patients without liver injury (controls). Several SNPs from the MHC class II region showed strong evidence of association (the top SNP was rs9270986 with P = 2.8 × 10 −10 ). These findings were replicated in an independent set of 98 lumiracoxib-treated cases and 405 matched lumiracoxib-treated controls (top SNP rs3129900, P = 4.4 × 10 −12 ). Fine mapping identified a strong association to a common HLA haplotype ( HLA-DRB1*1501 - HLA-DQB1 * 0602 - HLA-DRB5 * 0101 - HLA-DQA1 * 0102 , most significant allele P = 6.8 × 10 −25 , allelic odds ratio = 5.0, 95% CI 3.6–7.0). These results offer the potential to improve the safety profile of lumiracoxib by identifying individuals at elevated risk for liver injury and excluding them from lumiracoxib treatment.

Rheumatic heart disease follows Group A Streptococcus (GAS) infection in Aboriginal Australians. A genome-wide study identified HLA as the strongest genetic risk factor. Risk and protective HLA_DQA1_DQB1 haplotypes bound with different affinities to core epitopes of pathogenic GAS M proteins. Abstract Background Rheumatic heart disease (RHD) after group A streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers proinflammatory cardiac valve-reactive T cells. Methods Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single-nucleotide polymorphisms were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P = 1.86 × 10−7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (odds ratio [OR], 1.44; 95% confidence interval [CI], 1.09–1.90; P = 9.56 × 10−3) and HLA-DQA1*0103_DQB1*0601 (OR, 1.27; 95% CI, 1.07–1.52; P = 7.15 × 10−3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14–0.65, P = 2.36 × 10−3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the 2-risk haplotypes than the protective haplotype. Conclusions Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

Background MHC class II binding predictions are widely used to identify epitope candidates in infectious agents, allergens, cancer and autoantigens. The vast majority of prediction algorithms for human MHC class II to date have targeted HLA molecules encoded in the DR locus. This reflects a significant gap in knowledge as HLA DP and DQ molecules are presumably equally important, and have only been studied less because they are more difficult to handle experimentally. Results In this study, we aimed to narrow this gap by providing a large scale dataset of over 17,000 HLA-peptide binding affinities for a set of 11 HLA DP and DQ alleles. We also expanded our dataset for HLA DR alleles resulting in a total of 40,000 MHC class II binding affinities covering 26 allelic variants. Utilizing this dataset, we generated prediction tools utilizing several machine learning algorithms and evaluated their performance. Conclusion We found that 1) prediction methodologies developed for HLA DR molecules perform equally well for DP or DQ molecules. 2) Prediction performances were significantly increased compared to previous reports due to the larger amounts of training data available. 3) The presence of homologous peptides between training and testing datasets should be avoided to give real-world estimates of prediction performance metrics, but the relative ranking of different predictors is largely unaffected by the presence of homologous peptides, and predictors intended for end-user applications should include all training data for maximum performance. 4) The recently developed NN-align prediction method significantly outperformed all other algorithms, including a naïve consensus based on all prediction methods. A new consensus method dropping the comparably weak ARB prediction method could outperform the NN-align method, but further research into how to best combine MHC class II binding predictions is required.

The expression of classical human leukocyte antigen class I antigens (HLA‐I) on the surfaces of cancer cells allows cytotoxic T cells to recognize and eliminate these cells. Reduction or loss of HLA‐I is a mechanism of escape from antitumor immunity. The present study aimed to investigate the clinicopathological impacts of HLA‐I and non–classical HLA‐I antigens expressed on pancreatic ductal adenocarcinoma (PDAC) cells. We performed immunohistochemistry to detect expression of HLA‐I antigens in PDAC using 243 PDAC cases and examined their clinicopathological influences. We also investigated the expression of immune‐related genes to characterize PDAC tumor microenvironments. Lower expression of HLA‐I, found in 33% of PDAC cases, was significantly associated with longer overall survival. Higher expression of both HLA‐E and HLA‐G was significantly associated with shorter survival. Multivariate analyses revealed that higher expression of these three HLA‐I antigens was significantly correlated with shorter survival. Higher HLA‐I expression on PDAC cells was significantly correlated with higher expression of IFNG, which also correlated with PD1, PD‐L1 and PD‐L2 expression. In vitro assay revealed that interferon gamma (IFNγ) stimulation increased surface expression of HLA‐I in three PDAC cell lines. It also upregulated surface expression of HLA‐E, HLA‐G and immune checkpoint molecules, including PD‐L1 and PD‐L2. These results suggest that the higher expression of HLA‐I, HLA‐E and HLA‐G on PDAC cells is an unfavorable prognosticator. It is possible that IFNγ promotes a tolerant microenvironment by inducing immune checkpoint molecules in PDAC tissues with higher HLA‐I expression on PDAC cells. human leukocyte antigen class I antigens (HLA‐I) are needed for T cells to recognize target cells. Here, we showed that higher HLA‐I expression on pancreatic cancer cells is associated with poor prognosis, where formation of the tolerant microenvironment may be involved in IFNγ.