IPD-IMGT/HLA Database

T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy

In cancer, non-synonymous DNA base changes alter protein sequence and produce neoantigens that are detected by the immune system. For immune detection, neoantigens must first be presented on class I or II human leukocyte antigens (HLA) followed by recognition by peptide-specific receptors, exemplified by the T-cell receptor (TCR). Detection of neoantigens represents a unique challenge to the immune system due to their high similarity with endogenous 'self' proteins. Here, we review insights into how TCRs detect neoantigens from structural studies and delineate two broad mechanistic categories: 1) recognition of mutated 'self' peptides and 2) recognition of novel 'non-self' peptides generated through anchor residue modifications. While mutated 'self' peptides differ only by a single amino acid from an existing 'self' epitope, mutations that form anchor residues generate an entirely new epitope, hitherto unknown to the immune system. We review recent structural studies that highlight these structurally distinct mechanisms and discuss how they may lead to differential anti-tumor immune responses. We discuss how T cells specific for neoantigens derived from anchor mutations can be of high affinity and provide insights to their use in adoptive T cell transfer-based immunotherapy.

Characterization of the novel HLA-A*24:564 allele by sequencing-based typing

HLA-A*24:564 differs from HLA-A*24:02:01:01 by one nucleotide substitution in codon 240 in exon 4. This article is protected by copyright. All rights reserved.

Predicted impact of the viral mutational landscape on the cytotoxic response against SARS-CoV-2

The massive assessment of immune evasion due to viral mutations that increase COVID-19 susceptibility can be computationally facilitated. The adaptive cytotoxic T response is critical during primary infection and the generation of long-term protection. Here, potential HLA class I epitopes in the SARS-CoV-2 proteome were predicted for 2,915 human alleles of 71 families using the netMHCIpan EL algorithm. Allele families showed extreme epitopic differences, underscoring genetic variability of protective capacity between humans. Up to 1,222 epitopes were associated with any of the twelve supertypes, that is, allele clusters covering 90% population. Next, from all mutations identified in ~118,000 viral NCBI isolates, those causing significant epitope score reduction were considered epitope escape mutations. These mutations mainly involved non-conservative substitutions at the second and C-terminal position of the ligand core, or total ligand removal by large recurrent deletions. Escape mutations affected 47% of supertype epitopes, which in 21% of cases concerned isolates from two or more sub-continental areas. Some of these changes were coupled, but never surpassed 15% of evaded epitopes for the same supertype in the same isolate, except for B27. In contrast to most supertypes, eight allele families mostly contained alleles with few SARS-CoV-2 ligands. Isolates harboring cytotoxic escape mutations for these families co-existed geographically within sub-Saharan and Asian populations enriched in these alleles according to the Allele Frequency Net Database. Collectively, our findings indicate that escape mutation events have already occurred for half of HLA class I supertype epitopes. However, it is presently unlikely that, overall, it poses a threat to the global population. In contrast, single and double mutations for susceptible alleles may be associated with viral selective pressure and alarming local outbreaks. The integration of genomic, geographical and immunoinformatic information eases the surveillance of variants potentially affecting the global population, as well as minority subpopulations.

Minimal Information about MHC Multimers (MIAMM)

With the goal of improving the reproducibility and annotatability of MHC multimer reagent data, we present the establishment of a new data standard: Minimal Information about MHC Multimers (https://miamm.lji.org/). Multimers are engineered reagents composed of a ligand and a MHC, which can be represented in a standardized format using ontology terminology. We provide an online Web site to host the details of the standard, as well as a validation tool to assist with the adoption of the standard. We hope that this publication will bring increased awareness of Minimal Information about MHC Multimers and drive acceptance, ultimately improving the quality and documentation of multimer data in the scientific literature.

SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8 T cells

Although mRNA vaccine efficacy against severe COVID-19 remains high, variant emergence and breakthrough infections have changed vaccine policy to include booster immunizations. However, the effect of diverse and repeated antigen exposures on SARS-CoV-2 memory T cells is poorly understood. Here, we utilize DNA-barcoded MHC-multimers combined with scRNAseq and scTCRseq to capture the ex vivo profile of SARS-CoV-2-responsive T cells within a cohort of individuals with one, two, or three antigen exposures, including vaccination, primary infection, and breakthrough infection. We found that the order of exposure determined the relative distribution between spike- and non-spike-specific responses, with vaccination after infection leading to further expansion of spike-specific T cells and differentiation to a CCR7-CD45RA+ effector phenotype. In contrast, individuals experiencing a breakthrough infection mount vigorous non-spike-specific responses. In-depth analysis of over 4,000 epitope-specific T cell receptor sequences demonstrates that all types of exposures elicit diverse repertoires characterized by shared, dominant TCR motifs, with no evidence for repertoire narrowing from repeated exposure. Our findings suggest that breakthrough infections diversify the T cell memory repertoire and that current vaccination protocols continue to expand and differentiate spike-specific memory responses.

Transethnic analysis of psoriasis susceptibility in South Asians and Europeans enhances fine-mapping in the MHC and genomewide

Because transethnic analysis may facilitate prioritization of causal genetic variants, we performed a genomewide association study (GWAS) of psoriasis in South Asians (SAS), consisting of 2,590 cases and 1,720 controls. Comparison with our existing European-origin (EUR) GWAS showed that effect sizes of known psoriasis signals were highly correlated in SAS and EUR (Spearman ρ = 0.78; p < 2 × 10-14). Transethnic meta-analysis identified two non-MHC psoriasis loci (1p36.22 and 1q24.2) not previously identified in EUR, which may have regulatory roles. For these two loci, the transethnic GWAS provided higher genetic resolution and reduced the number of potential causal variants compared to using the EUR sample alone. We then explored multiple strategies to develop reference panels for accurately imputing MHC genotypes in both SAS and EUR populations and conducted a fine-mapping of MHC psoriasis associations in SAS and the largest such effort for EUR. HLA-C*06 was the top-ranking MHC locus in both populations but was even more prominent in SAS based on odds ratio, disease liability, model fit and predictive power. Transethnic modeling also substantially boosted the probability that the HLA-C*06 protein variant is causal. Secondary MHC signals included coding variants of HLA-C and HLA-B, but also potential regulatory variants of these two genes as well as HLA-A and several HLA class II genes, with effects on both chromatin accessibility and gene expression. This study highlights the shared genetic basis of psoriasis in SAS and EUR populations and the value of transethnic meta-analysis for discovery and fine-mapping of susceptibility loci.

HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed abstracts

Extreme complexity in the Human Leukocyte Antigens (HLA) system and its nomenclature makes it difficult to interpret and integrate relevant information for HLA associations with diseases, Adverse Drug Reactions (ADR) and Transplantation. PubMed search displays ~ 146,000 studies on HLA reported from diverse locations. Currently, IPD-IMGT/HLA (Robinson et al., Nucleic Acids Research 48:D948-D955, 2019) database houses data on 28,320 HLA alleles. We developed an automated pipeline with a unified graphical user interface HLA-SPREAD that provides a structured information on SNPs, Populations, REsources, ADRs and Diseases information. Information on HLA was extracted from ~ 28 million PubMed abstracts extracted using Natural Language Processing (NLP). Python scripts were used to mine and curate information on diseases, filter false positives and categorize to 24 tree hierarchical groups and named Entity Recognition (NER) algorithms followed by semantic analysis to infer HLA association(s). This resource from 109 countries and 40 ethnic groups provides interesting insights on: markers associated with allelic/haplotypic association in autoimmune, cancer, viral and skin diseases, transplantation outcome and ADRs for hypersensitivity. Summary information on clinically relevant biomarkers related to HLA disease associations with mapped susceptible/risk alleles are readily retrievable from HLASPREAD. The resource is available at URL http://hla-spread.igib.res.in/ . This resource is first of its kind that can help uncover novel patterns in HLA gene-disease associations.

Characterization of the novel HLA-DRB1*04:315 allele by next-generation sequencing

HLA-DRB1*04:315 differs from HLA-DRB1*04:07:01:02 by a single nucleotide substitution in codon 147 of exon 3.

Human Leukocyte Antigen (HLA) Testing in Pharmacogenomics

The genetic region on the short arm of chromosome 6 where the human leukocyte antigen (HLA) genes are located is the major histocompatibility complex. The genes in this region are highly polymorphic, and some loci have a high degree of homology with other genes and pseudogenes. Histocompatibility testing has traditionally been performed in the setting of transplantation and involves determining which specific alleles are present. Several HLA alleles have been associated with disease risk or increased risk of adverse drug reaction (ADR) when treated with certain medications. Testing for these applications differs from traditional histocompatibility in that the desired result is simply presence or absence of the allele of interest, rather than determining which allele is present. At present, the majority of HLA typing is done by molecular methods using commercially available kits. A subset of pharmacogenomics laboratories has developed their own methods, and in some cases, query single nucleotide variants associated with certain HLA alleles rather than directly testing for the allele. In this chapter, a brief introduction to the HLA system is provided, followed by an overview of a variety of testing technologies including those specifically used in pharmacogenomics, and the chapter concludes with details regarding specific HLA alleles associated with ADR.

Structural Prediction of Peptide-MHC Binding Modes

The immune system is constantly protecting its host from the invasion of pathogens and the development of cancer cells. The specific CD8⁺ T-cell immune response against virus-infected cells and tumor cells is based on the T-cell receptor recognition of antigenic peptides bound to class I major histocompatibility complexes (MHC) at the surface of antigen presenting cells. Consequently, the peptide binding specificities of the highly polymorphic MHC have important implications for the design of vaccines, for the treatment of autoimmune diseases, and for personalized cancer immunotherapy. Evidence-based machine-learning approaches have been successfully used for the prediction of peptide binders and are currently being developed for the prediction of peptide immunogenicity. However, understanding and modeling the structural details of peptide/MHC binding is crucial for a better understanding of the molecular mechanisms triggering the immunological processes, estimating peptide/MHC affinity using universal physics-based approaches, and driving the design of novel peptide ligands. Unfortunately, due to the large diversity of MHC allotypes and possible peptides, the growing number of 3D structures of peptide/MHC (pMHC) complexes in the Protein Data Bank only covers a small fraction of the possibilities. Consequently, there is a growing need for rapid and efficient approaches to predict 3D structures of pMHC complexes. Here, we review the key characteristics of the 3D structure of pMHC complexes before listing databases and other sources of information on pMHC structures and MHC specificities. Finally, we discuss some of the most prominent pMHC docking software.

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

Association of HLA Class I Genotype with Mortality in Patients with Diabetes Mellitus and COVID-19

Numerous studies showed that diabetes mellitus (DM) increases the risk of death from COVID-19 by five times. It is generally accepted that the high lethality of COVID-19 against the background of DM is due to the main complications of this disease: micro- and macroangiopathies, as well as heart and kidney failure. In addition, it was shown that acute respiratory viral infection increases the production of interferon gamma, increases muscle resistance to insulin, and modulates the activity of effector CD8+ T cells. The ability of CD8+ T cells to recognize SARS-CoV-2-infected cells depends not only on humoral factors but also on individual genetic characteristics, including the individual set of major histocompatibility complex class I (MHC-I) molecules. In this study, the relationship of the MHC-I genotype of patients with DM aged less than 60 years with the outcome of COVID-19 was studied using a sample of 222 patients. It was shown that lethal outcomes of COVID-19 in patients with DM are associated with the low affinity of the interaction of an individual set of MHC-I molecules with SARS-CoV-2 peptides.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Rapid Identification of MHCII-Binding Peptides Through Microsphere-Assisted Peptide Screening (MAPS)

CD4⁺ T cells play a vital role in the immune response, and their function requires T cell receptor (TCR) recognition of peptide epitopes presented in complex with MHC class II (MHCII) molecules. Consequently, rapidly identifying peptides that bind MHCII is critical to understanding and treating infectious disease, cancer, autoimmunity, allergy, and transplant rejection. Computational methods provide a fast, ultrahigh-throughput approach to predict MHCII-binding peptides but lack the accuracy of experimental methods. In contrast, experimental methods offer accurate, quantitative results at the expense of speed. To address the gap between these two approaches, we developed a high-throughput, semiquantitative experimental screening strategy termed microsphere-assisted peptide screening (MAPS). Here, we use the Zika virus envelope protein as an example to demonstrate the rapid identification of MHCII-binding peptides from a single pathogenic protein using MAPS. This process involves several key steps including peptide library design, peptide exchange into MHCII, peptide-MHCII loading onto microspheres, flow cytometry screening, and data analysis to identify peptides that bind to one or more MHCII alleles.

Description of HLA-DRB1*14:02:09, a novel HLA allele identified in a Colombian donor

HLA-DRB1*14:02:09 differs from HLA-DRB1*14:02:01:02 by a single nucleotide substitution in codon 169 of exon 3. This article is protected by copyright. All rights reserved.

Genetic markers for psoriatic arthritis among patients with psoriasis. Part II: HLA genes

Psoriatic arthritis often leads to the development of severe outcomes ankylosis, deformities of the affected joints with severe impairment of their functions and disability. Early identification of patients with psoriasis with an increased risk of developing psoriatic arthritis for the purpose of its timely diagnosis and early initiation of therapy can prevent the development of severe disease outcomes. It is believed that the genes of the HLA system make the greatest individual genetic contribution to the formation of a predisposition to hereditary diseases with polygenic inheritance. The literature review considers the polymorphisms of the genes of the HLA system, associated with the development of psoriatic arthritis, in patients with psoriasis. The HLA alleles that contribute to the development of psoriatic arthritis and its individual forms have been identified. HLA alleles have been identified, which have a protective effect against the development of psoriatic arthritis.

Single-Molecule RNA Sequencing Reveals IFNγ-Induced Differential Expression of Immune Escape Genes in Merkel Cell Polyomavirus-Positive MCC Cell Lines

Merkel cell carcinoma (MCC) is a rare and highly aggressive cancer, which is mainly caused by genomic integration of the Merkel cell polyomavirus and subsequent expression of a truncated form of its large T antigen. The resulting primary tumor is known to be immunogenic and under constant pressure to escape immune surveillance. Because interferon gamma (IFNγ), a key player of immune response, is secreted by many immune effector cells and has been shown to exert both anti-tumoral and pro-tumoral effects, we studied the transcriptomic response of MCC cells to IFNγ. In particular, immune modulatory effects that may help the tumor evade immune surveillance were of high interest to our investigation. The effect of IFNγ treatment on the transcriptomic program of three MCC cell lines (WaGa, MKL-1, and MKL-2) was analyzed using single-molecule sequencing via the Oxford Nanopore platform. A significant differential expression of several genes was detected across all three cell lines. Subsequent pathway analysis and manual annotation showed a clear upregulation of genes involved in the immune escape of tumor due to IFNγ treatment. The analysis of selected genes on protein level underlined our sequencing results. These findings contribute to a better understanding of immune escape of MCC and may help in clinical treatment of MCC patients. Furthermore, we demonstrate that single-molecule sequencing can be used to assess characteristics of large eukaryotic transcriptomes and thus contribute to a broader access to sequencing data in the community due to its low cost of entry.

Peptides Derived From Mismatched Paternal Human Leukocyte Antigen Predicted to Be Presented by HLA-DRB1, -DRB3/4/5, -DQ, and -DP Induce Child-Specific Antibodies in Pregnant Women

Predicted Indirectly ReCognizable Human Leukocyte Antigen (HLA) Epitopes (PIRCHE) are known to be a significant risk factor for the development of donor HLA-specific antibodies after organ transplantation. Most previous studies on PIRCHE limited their analyses on the presentation of the HLA-DRB1 locus, although HLA-DRB3/4/5, -DQ, and -DP are also known for presenting allopeptides to CD4+ T cells. In this study, we analyzed the impact of predicted allopeptides presented by these additional loci on the incidence of HLA-specific antibodies after an immunization event. We considered pregnancy as a model system of an HLA immunization and observed child-specific HLA antibody (CSA) development of 231 mothers during pregnancy by samples being taken at delivery. Our data confirm that PIRCHE presented by HLA-DRB1 along with HLA-DRB3/4/5, -DQ, and -DP are significant predictors for the development of CSA. Although there was limited peptidome overlap observed within the mothers’ presenting HLA proteins, combining multiple presenting loci in a single predictor improved the model only marginally. Prediction performance of PIRCHE further improved when normalizing scores by the respective presenters’ binding promiscuity. Immunogenicity analysis of specific allopeptides could not identify significant drivers of an immune response in this small cohort, suggesting confirmatory studies.

Predicted Epitope Abundance Supports Vaccine-Induced Cytotoxic Protection Against SARS-CoV-2 Variants of Concern

The effect of emerging SARS-CoV-2 variants on vaccine efficacy is of critical importance. In this study, the potential impact of mutations that facilitate escape from the cytotoxic cellular immune response in these new virus variants for the 551 most abundant HLA class I alleles was analyzed. Computational prediction showed that most of these alleles, that cover >90% of the population, contain enough epitopes without escape mutations in the principal SARS-CoV-2 variants. These data suggest that the cytotoxic cellular immune protection elicited by vaccination is not greatly affected by emerging SARS-CoV-2 variants.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Characterization of the novel HLA-DQA1*05:49 allele by sequencing-based typing

HLA-DQA1*05:49 differs from HLA-DQA1*05:01:01:02 by one nucleotide substitution in codon 78 in exon 2.

Characterization of the novel HLA-DPB1*665:01:02 allele by sequencing-based typing

HLA-DPB1*665:01:02 differs from HLA-DPB1*665:01:01 by one nucleotide substitution in codon 139 in exon 3.

Characterization of the novel HLA-DRB4*01:151 allele by sequencing-based typing

HLA-DRB4*01:151 differs from DRB4*01:01:01:01 by one nucleotide substitution in codon 178 in exon 3.

Characterization of the novel HLA-B*57:146 allele by sequencing-based typing

HLA-B*57:146 differs from HLA-B*57:01:01:01 by one nucleotide substitution in codon 103 in exon 3.

Characterization of the novel HLA-DQA1*01:76 allele by sequencing-based typing

HLA-DQA1*01:76 differs from HLA-DQA1*01:03:01:06 by one nucleotide substitution in codon -11 in exon 1.

PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation

The increasing availability of next generation sequencing (NGS) for personal genomics could promote pharmacogenomics (PGx) discovery and application. However, current tools for analysis and interpretation of pharmacogenomic variants from NGS data are inadequate, as none offer comprehensive analytic functions in a simple, web-based platform. In addition, no tools exist to analyze human leukocyte antigen (HLA) genes for determining potential risks of immune-mediated adverse drug reaction (IM-ADR). We describe PharmVIP, a web-based PGx tool, for one-stop comprehensive analysis and interpretation of genome-wide variants obtained from NGS platforms. PharmVIP comprises three main interpretation modules covering analyses of pharmacogenes involved in pharmacokinetics, pharmacodynamics and IM-ADR. The Guideline module provides Clinical Pharmacogenetics Implementation Consortium (CPIC) drug guideline recommendations based on the translation of genotypic data in genes having guidelines. The HLA module reports HLA genotypes, potential adverse drug reactions, and the relevant drug guidelines. The Pharmacogenes module is employed for prioritizing variants according to variant effect on gene function. Detailed, customizable reports are provided as exportable files and as an interactive web version. PharmVIP is a new integrated NGS workflow for the PGx community to facilitate discovery and clinical application.

SARS-CoV-2-Reactive Mucosal B Cells in the Upper Respiratory Tract of Uninfected Individuals

SARS-CoV-2 is a respiratory pathogen that can cause severe disease in at-risk populations but results in asymptomatic infections or a mild course of disease in the majority of cases. We report the identification of SARS-CoV-2-reactive B cells in human tonsillar tissue obtained from children who were negative for coronavirus disease 2019 prior to the pandemic and the generation of mAbs recognizing the SARS-CoV-2 Spike protein from these B cells. These Abs showed reduced binding to Spike proteins of SARS-CoV-2 variants and did not recognize Spike proteins of endemic coronaviruses, but subsets reacted with commensal microbiota and exhibited SARS-CoV-2-neutralizing potential. Our study demonstrates pre-existing SARS-CoV-2-reactive Abs in various B cell populations in the upper respiratory tract lymphoid tissue that may lead to the rapid engagement of the pathogen and contribute to prevent manifestations of symptomatic or severe disease.

Two probable human leukocyte antigen haplotypes in association with human leukocyte antigen HLA-DRB1*13:50:01 identified in 41 randomized unrelated Taiwanese individuals

Objectives:

Here, we show two probable haplotypes associated with the human leukocyte antigen (HLA) DRB1*13:50:01 allele. The haplotypes were observed from 41 randomized unrelated Taiwanese individuals among a population of 23,064 individuals tested.

Materials and Methods:

The samples in this study were blood samples, preserved in dipotassium ethylenediaminetetraacetic acid and/or ACD anticoagulants. The population is of donors from Tzu Chi Bone Marrow Donor Registry. Allele typing was performed using the sequence-based typing method, Sanger's sequencing. To discern the HLA-A and HLA-B alleles, exons 2 and 3 were sequenced. For DRB1 alleles, exon 2 was sequenced. Target exon sequence amplifications were done by a polymerase chain reaction and the resulting amplicons were sequenced by Bigdye Terminator Cycle Sequencing Ready Reaction kit, according to the manufacturer's protocols.

Results:

Two probable haplotypes that are associated with the DRB1*13:50:01 were observed among the 23,064 Taiwanese randomized unrelated individuals. One of the haplotypes is observed in 39 individuals while the other in two individuals.

Conclusion:

The findings in this study may be useful in studies reinforcing the understanding and clinical application of the polymorphism of HLA genes and haplotypes.

Characterization of the novel HLA-DQA1*05:01:07 allele by sequencing-based typing

HLA-DQA1*05:01:07 differs from HLA-DQA1*05:01:01:02 by one nucleotide substitution in codon 58 in exon 2.

Characterization of the novel HLA-A*29:02:38 allele by sequencing-based typing

HLA-A*29:02:38 differs from HLA-A*29:02:01:01 by one nucleotide substitution in codon 201 in exon 4.

ERAP1 Controls the Autoimmune Response against Melanocytes in Psoriasis by Generating the Melanocyte Autoantigen and Regulating Its Amount for HLA-C*06:02 Presentation

Autoimmune diseases develop when autoantigens activate previously quiescent self-reactive lymphocytes. Gene-gene interaction between certain HLA class I risk alleles and variants of the endoplasmic reticulum aminopeptidase ERAP1 controls the risk for common immune-mediated diseases, including psoriasis, ankylosing spondylitis, and Behçet disease. The functional mechanisms underlying this statistical association are unknown. In psoriasis, HLA-C*06:02 mediates an autoimmune response against melanocytes by autoantigen presentation. Using various genetically modified cell lines together with an autoreactive psoriatic TCR in a TCR activation assay, we demonstrate in this study that in psoriasis, ERAP1 generates the causative melanocyte autoantigen through trimming N-terminal elongated peptide precursors to the appropriate length for presentation by HLA-C*06:02. An ERAP1 risk haplotype for psoriasis produced the autoantigen much more efficiently and increased HLA-C expression and stimulation of the psoriatic TCR by melanocytes significantly more than a protective haplotype. Compared with the overall HLA class I molecules, cell surface expression of HLA-C decreased significantly more upon ERAP1 knockout. The combined upregulation of ERAP1 and HLA-C on melanocytes in psoriasis lesions emphasizes the pathogenic relevance of their interaction in patients. We conclude that in psoriasis pathogenesis, the increased generation of an ERAP1-dependent autoantigen by an ERAP1 risk haplotype enhances the likelihood that autoantigen presentation by HLA-C*06:02 will exceed the threshold for activation of potentially autoreactive T cells, thereby triggering CD8+ T cell-mediated autoimmune disease. These data identify ERAP1 function as a central checkpoint and promising therapeutic target in psoriasis and possibly other HLA class I-associated diseases with a similar genetic predisposition.

Immune system regulation and role of the human leukocyte antigen in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a debilitating condition that adversely affect mental and physical health. Recent studies have increasingly explored the role of the immune system in risk for PTSD and its related symptoms. Dysregulation of the immune system may lead to central nervous system tissue damage and impair learning and memory processes. Individuals with PTSD often have comorbid inflammatory or auto-immune disorders. Evidence shows associations between PTSD and multiple genes that are involved in immune-related or inflammatory pathways. In this review, we will summarize the evidence of immune dysregulation in PTSD, outlining the contributions of distinct cell types, genes, and biological pathways. We use the Human Leukocyte Antigen (HLA) locus to illustrate the contribution of genetic variation to function in different tissues that contribute to PTSD etiology, severity, and comorbidities.

A Comprehensive Review of HLA and Severe Cutaneous Adverse Drug Reactions: Implication for Clinical Pharmacogenomics and Precision Medicine

Human leukocyte antigen (HLA) encoded by the HLA gene is an important modulator for immune responses and drug hypersensitivity reactions as well. Genetic polymorphisms of HLA vary widely at population level and are responsible for developing severe cutaneous adverse drug reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), maculopapular exanthema (MPE). The associations of different HLA alleles with the risk of drug induced SJS/TEN, DRESS and MPE are strongly supportive for clinical considerations. Prescribing guidelines generated by different national and international working groups for translation of HLA pharmacogenetics into clinical practice are underway and functional in many countries, including Thailand. Cutting edge genomic technologies may accelerate wider adoption of HLA screening in routine clinical settings. There are great opportunities and several challenges as well for effective implementation of HLA genotyping globally in routine clinical practice for the prevention of drug induced SCARs substantially, enforcing precision medicine initiatives.

Connecting MHC-I-binding motifs with HLA alleles via deep learning

The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performance on binding affinity. However, the decisive MHC residues and their relation to the selection of binding peptides are still unrevealed. Here, we connected HLA alleles with binding motifs via our deep learning-based framework, MHCfovea. MHCfovea expanded the knowledge of MHC-I-binding motifs from 150 to 13,008 alleles. After clustering N-terminal and C-terminal sub-motifs on both observed and unobserved alleles, MHCfovea calculated the hyper-motifs and the corresponding allele signatures on the important positions to disclose the relation between binding motifs and MHC-I sequences. MHCfovea delivered 32 pairs of hyper-motifs and allele signatures (HLA-A: 13, HLA-B: 12, and HLA-C: 7). The paired hyper-motifs and allele signatures disclosed the critical polymorphic residues that determine the binding preference, which are believed to be valuable for antigen discovery and vaccine design when allele specificity is concerned.

Ko-Han Lee et al. develop MHCfovea, a machine-learning method for predicting peptide-binding by MHC molecules and inferring peptide motifs and MHC allele signatures. They demonstrate that MHCfovea is capable of detecting meaningful hyper-motifs and allele signatures, making it a useful resource for the community.

Single-Nucleotide Polymorphisms in MICA and MICB Genes Could Play a Role in the Outcome in AML Patients after HSCT

NKG2D and its ligands, MICA and MICB, are known as the key regulators of NK cells. NK cells are the first reconstituted cells after the allogeneic hematopoietic stem cell transplantation (HSCT); therefore, it is crucial to understand their role in HSCT outcome. In the presented study, we investigated the single amino acid changes across the exons 2–4 of MICA and MICB genes, and point mutations within the NKG2D gene, which defines the type of NKG2D haploblock (HNK/LNK) in the donors (n = 124), as well as in patients with acute myeloid leukemia (n = 78). In our cohort, we found that graft from a donor with at least one MICA allele containing glycine at position 14 (MICA-14Gly) is significantly associated with deterioration of a patient’s overall survival (OS) (p < 0.05). We also observed a negative effect of MICB-58 (Lys → Glu) polymorphism on relapse-free survival (RFS), although it was not statistically significant in multivariate analysis (p = 0.069). To our knowledge, this is the first work describing the role of MICA-14 and MICB-58 polymorphisms on HSCT outcome.

HLA-C and KIR permutations influence chronic obstructive pulmonary disease risk

A role for hereditary influences in the susceptibility for chronic obstructive pulmonary disease (COPD) is widely recognized. Cytotoxic lymphocytes are implicated in COPD pathogenesis, and functions of these leukocytes are modulated by interactions between their killer cell Ig-like receptors (KIR) and human leukocyte antigen–Class I (HLA–Class I) molecules on target cells. We hypothesized HLA–Class I and KIR inheritance affect risks for COPD. HLA–Class I alleles and KIR genotypes were defined by candidate gene analyses in multiple cohorts of patients with COPD (total n = 392) and control smokers with normal spirometry (total n = 342). Compared with controls, patients with COPD had overrepresentations of HLA-C*07 and activating KIR2DS1, with underrepresentations of HLA-C*12. Particular HLA-KIR permutations were synergistic; e.g., the presence of HLA-C*07 + KIR2DS1 + HLA-C12^null versus HLAC*07^null + KIR2DS1^null + HLA-C12 was associated with COPD, especially among HLA-C1 allotype homozygotes. Cytotoxicity of COPD lymphocytes was more enhanced by KIR stimulation than those of controls and was correlated with lung function. These data show HLA-C and KIR polymorphisms strongly influence COPD susceptibility and highlight the importance of lymphocyte-mediated cytotoxicity in COPD pathogenesis. Findings here also indicate that HLA-KIR typing could stratify at-risk patients and raise possibilities that HLA-KIR axis modulation may have therapeutic potential.

Peptides of H. sapiens and P. falciparum that are predicted to bind strongly to HLA-A*24:02 and homologous to a SARS-CoV-2 peptide

AIM

This study is looking for a common pathogenicity between SARS-CoV-2 and Plasmodium species, in individuals with certain HLA serotypes.

METHODS

1. Tblastx searches of SARS-CoV-2 are performed by limiting searches to five Plasmodium species that infect humans. 2. Aligned sequences in the respective organisms' proteomes are searched with blastp. 3. Binding predictions of the identified SARS-CoV-2 peptide to HLA supertype representatives are performed. 4. Blastp searches of predicted epitopes that bind strongly to the identified HLA allele are performed by limiting searches to H. sapiens and Plasmodium species, separately. 5. Peptides with minimum 60% identity to the predicted epitopes are found in results. 6. Peptides among those, which bind strongly to the same HLA allele, are predicted. 7. Step-4 is repeated by limiting searches to H. sapiens, followed by the remaining steps until step-7, for peptides sourced by Plasmodium species after step-6.

RESULTS

SARS-CoV-2 peptide with single letter amino acid code CFLGYFCTCYFGLFC has the highest identity to P. vivax. Its YFCTCYFGLF part is predicted to bind strongly to HLA-A*24:02. Peptides in the human proteome both homologous to YFCTCYFGLF and with a strong binding affinity to HLA-A*24:02 are YYCARRFGLF, YYCHCPFGVF, and YYCQQYFFLF. Such peptides in the Plasmodium species' proteomes are FFYTFYFELF, YFVACLFILF, and YFPTITFHLF. The first one belonging to P. falciparum has a homologous peptide (YFYLFSLELF) in the human proteome, which also has a strong binding affinity to the same HLA allele.

CONCLUSION

Immune responses to the identified-peptides with similar sequences and strong binding affinities to HLA-A*24:02 can be related to autoimmune response risk in individuals with HLA-A*24:02 serotypes, upon getting infected with SARS-CoV-2 or P. falciparum.

Deep Sequencing of MHC-Adapted Viral Lines Reveals Complex Recombinational Exchanges With Endogenous Retroviruses Leading to High-Frequency Variants

Experimental evolution (serial passage) of Friend virus complex (FVC) in mice demonstrates phenotypic adaptation to specific host major histocompatibility complex (MHC) genotypes. These evolved viral lines show increased fitness and virulence in their host-genotype-of-passage, but display fitness and virulence tradeoffs when infecting unfamiliar host MHC genotypes. Here, we deep sequence these viral lines in an attempt to discover the genetic basis of FVC adaptation. The principal prediction for genotype-specific adaptation is that unique mutations would rise to high frequency in viral lines adapted to each host MHC genotype. This prediction was not supported by our sequencing data as most observed high-frequency variants were present in each of our independently evolved viral lines. However, using a multi-variate approach to measure divergence between viral populations, we show that populations of replicate evolved viral lines from the same MHC congenic mouse strain were more similar to one another than to lines derived from different MHC congenic mouse strains, suggesting that MHC genotype does predictably act on viral evolution in our model. Sequence analysis also revealed rampant recombination with endogenous murine leukemia virus sequences (EnMuLVs) that are encoded within the BALB/c mouse genome. The highest frequency variants in all six lines contained a 12 bp insertion from a recombinant EnMuLV source, suggesting such recombinants were either being favored by selection or were contained in a recombinational hotspot. Interestingly, they did not reach fixation, as if they are low fitness. The amount of background mutations linked to FVC/EnMuLV variable sites indicated that FVC/EnMuLV recombinants had not reached mutation selection equilibrium and thus, that EnMuLV sequences are likely continuously introgressing into the replicating viral population. These discoveries raise the question: is the expression of EnMuLV sequences in mouse splenocytes that permit recombination with exogenous FVC a pathogen or host adaptation?

A novel and efficient approach to high-throughput production of HLA-E/peptide monomer for T-cell epitope screening

Over the past two decades, there has been a great interest in the study of HLA-E-restricted αβ T cells during bacterial and viral infections, including recently SARS-CoV-2 infection. Phenotyping of these specific HLA-E-restricted T cells requires new tools such as tetramers for rapid cell staining or sorting, as well as for the identification of new peptides capable to bind to the HLA-E pocket. To this aim, we have developed an optimal photosensitive peptide to generate stable HLA-E/pUV complexes allowing high-throughput production of new HLA-E/peptide complexes by peptide exchange. We characterized the UV exchange by ELISA and improved the peptide exchange readout using size exclusion chromatography. This novel approach for complex quantification is indeed very important to perform tetramerization of MHC/peptide complexes with the high quality required for detection of specific T cells. Our approach allows the rapid screening of peptides capable of binding to the non-classical human HLA-E allele, paving the way for the development of new therapeutic approaches based on the detection of HLA-E-restricted T cells.

An immunogenetic view of COVID-19

Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.

Major Insights in Dynamics of Host Response to SARS-CoV-2: Impacts and Challenges

The coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization on March 11, 2020, is caused by the infection of highly transmissible species of a novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of July 25, 2021, there are 194,372,584 cases and 4,167,937 deaths with high variability in clinical manifestations, disease burden, and post-disease complications among different people around the globe. Overall, COVID-19 is manifested as mild to moderate in almost 90% of the cases and only the rest 10% of the cases need hospitalization. However, patients with older age and those having different comorbidities have made worst the pandemic scenario. The variability of pathological consequences and clinical manifestations of COVID-19 is associated with differential host-SARS-CoV-2 interactions, which are influenced by the factors that originated from the SARS-CoV-2 and the host. These factors usually include the genomic attributes and virulent factors of the SARS-CoV-2, the burden of coinfection with other viruses and bacteria, age and gender of the individuals, different comorbidities, immune suppressions/deficiency, genotypes of major histocompatibility complex, and blood group antigens and antibodies. We herein retrieved and reviewed literatures from PubMed, Scopus, and Google relevant to clinical complications and pathogenesis of COVID-19 among people of different age, sex, and geographical locations; genomic characteristics of SARS-CoV-2 including its variants, host response under different variables, and comorbidities to summarize the dynamics of the host response to SARS-CoV-2 infection; and host response toward approved vaccines and treatment strategies against COVID-19. After reviewing a large number of published articles covering different aspects of host response to SARS-CoV-2, it is clear that one aspect from one region is not working with the scenario same to others, as studies have been done separately with a very small number of cases from a particular area/region of a country. Importantly, to combat such a pandemic as COVID-19, a conclusive understanding of the disease dynamics is required. This review emphasizes on the identification of the factors influencing the dynamics of host responses to SARS-CoV-2 and offers a future perspective to explore the molecular insights of COVID-19.

PopCover-2.0. Improved Selection of Peptide Sets With Optimal HLA and Pathogen Diversity Coverage

The use of minimal peptide sets offers an appealing alternative for design of vaccines and T cell diagnostics compared to conventional whole protein approaches. T cell immunogenicity towards peptides is contingent on binding to human leukocyte antigen (HLA) molecules of the given individual. HLA is highly polymorphic, and each variant typically presents a different repertoire of peptides. This polymorphism combined with pathogen diversity challenges the rational selection of peptide sets with broad immunogenic potential and population coverage. Here we propose PopCover-2.0, a simple yet highly effective method, for resolving this challenge. The method takes as input a set of (predicted) CD8 and/or CD4 T cell epitopes with associated HLA restriction and pathogen strain annotation together with information on HLA allele frequencies, and identifies peptide sets with optimal pathogen and HLA (class I and II) coverage. PopCover-2.0 was benchmarked on historic data in the context of HIV and SARS-CoV-2. Further, the immunogenicity of the selected SARS-CoV-2 peptides was confirmed by experimentally validating the peptide pools for T cell responses in a panel of SARS-CoV-2 infected individuals. In summary, PopCover-2.0 is an effective method for rational selection of peptide subsets with broad HLA and pathogen coverage. The tool is available at https://services.healthtech.dtu.dk/service.php?PopCover-2.0.

Associations between HLA-B27 subtypes and outcomes in Thai children with enthesitis-related arthritis

OBJECTIVE

Expression of human leukocyte antigen B27 (HLA-B27) has been identified as a predictor of severe disease in enthesitis-related arthritis (ERA) patients. However, the associations between HLA-B27 subtypes and outcomes of this disease are still unclear. Here, we examined the distributions of HLA-B27 subtypes among ERA patients and the associations with disease outcomes.

METHODS

This was a historical cohort study of ERA patients. Patients were followed from diagnosis to the most recent visit. Relationships between outcomes and the HLA-B27 subtype were assessed by mixed-effect regression, Kaplan-Meier survival, and Cox proportional hazards regression analyses.

RESULTS

Of the 66 ERA patients, 50 HLA-B27-positive (86% male) and 16 HLA-B27-negative (69% male) patients were included in this study. Patients with HLA-B27-positive were classified into HLA-B*27:04-positive (84%), including combined HLA-B*27:04 and HLA-B*27:07 (2%), and HLA-B*27:04-negative (16%), including HLA-B*27:05 (10%), HLA-B*27:06 (2%), HLA-B*27:07 (2%), and HLA-B*27:15 (2%). HLA-B*27:04-positive (83.3%) and HLA-B*27:04-negative patients (100%) had refractory disease more than HLA-B27-negative patients (37.5%, p = 0.001). HLA-B*27:04-negative patients (57%, 1.73 years) had relapsing disease more and earlier than HLA-B*27:04-positive (35%, 5.54 years) and HLA-B27-negative patients (40%, 6.92 years; p < 0.001). Furthermore, HLA-B*27:04-negative was predictors of refractory disease (HR 4.56, 95%CI 1.40-14.87; p = 0.012) and relapsing disease (HR 3.80, 95% CI 1.18-12.30; p = 0.026). The duration before anti-tumor necrosis factor treatment initiation > 1 year was also a predictor of refractory disease (HR 116.08, 95% CI 14.67-918.26; p < 0.001).

CONCLUSION

HLA-B*27:04 was the most common HLA-B27 subtype in Thai ERA patients. HLA-B*27:04-negative was associated with more unfavorable outcomes than HLA-B*27:04-positive and HLA-B27-negative patients. Key Points • Most ERA patients in Thailand had HLA-B27-positive, and HLA-B*27:04 was the most common HLA-B27 allele in these patients. • The outcomes of ERA were associated with the presence of HLA-B27 and its subtypes. • HLA-B*27:04-negative patients had unfavorable outcomes, including refractory and relapsing disease, compared to HLA-B*27:04-positive and HLA-B27-negative patients.

Using de novo assembly to identify structural variation of eight complex immune system gene regions

Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14⁺ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.

The human immune system is incredibly versatile underlying its capacity to defend the body against thousands of pathogens. At a molecular level, it recognizes pathogens using large libraries of antibodies and related protein receptors. These molecules are encoded by gene families that are particularly difficult to analyze due to their unusually complex patterns of similarities and differences between genes and individuals. To overcome this, we applied several sequencing methods to DNA from a single individual and developed methods to reconstruct the underlying sequence at eight of the immune-associated regions. Importantly, we used DNA extracted from monocytes to avoid capturing the further rearrangements that occur in active immune cells. We generated accurate assemblies by integrating multiple complementary data types, although we noted a small subset of locations that remain challenging. Moreover, we found that this individual contains multiple structural differences between the two inherited chromosomes and compared to previously analyzed genomes, affecting the copy number of immune system genes. Application of these methods in larger numbers of individuals will clearly uncover much more variation than is currently known, and might lead to new understanding of the effect of genetic variation on the broad range of human diseases determined by the immune response.

Relevance of Polymorphic KIR and HLA Class I Genes in NK-Cell-Based Immunotherapies for Adult Leukemic Patients

Simple Summary

Immunotherapies are promising approaches to curing different acute leukemias. Natural killer (NK) cells are lymphocytes that are efficient in the elimination of leukemic cells. NK-cell-based immunotherapies are particularly attractive, but the landscape of the heterogeneity of NK cells must be deciphered. This review provides an overview of the polymorphic KIR and HLA class I genes that modulate the NK cell repertoire and how these markers can improve the outcomes of patients with acute leukemia. A better knowledge of these genetic markers that are linked to NK cell subsets that are efficient against hematological diseases will optimize hematopoietic stem-cell donor selection and NK immunotherapy design.

Abstract

Since the mid-1990s, the biology and functions of natural killer (NK) cells have been deeply investigated in healthy individuals and in people with diseases. These effector cells play a particularly crucial role after allogeneic hematopoietic stem-cell transplantation (HSCT) through their graft-versus-leukemia (GvL) effect, which is mainly mediated through polymorphic killer-cell immunoglobulin-like receptors (KIRs) and their cognates, HLA class I ligands. In this review, we present how KIRs and HLA class I ligands modulate the structural formation and the functional education of NK cells. In particular, we decipher the current knowledge about the extent of KIR and HLA class I gene polymorphisms, as well as their expression, interaction, and functional impact on the KIR⁺ NK cell repertoire in a physiological context and in a leukemic context. In addition, we present the impact of NK cell alloreactivity on the outcomes of HSCT in adult patients with acute leukemia, as well as a description of genetic models of KIRs and NK cell reconstitution, with a focus on emergent T-cell-repleted haplo-identical HSCT using cyclosphosphamide post-grafting (haplo-PTCy). Then, we document how the immunogenetics of KIR/HLA and the immunobiology of NK cells could improve the relapse incidence after haplo-PTCy. Ultimately, we review the emerging NK-cell-based immunotherapies for leukemic patients in addition to HSCT.

Impact of Previously Unrecognized HLA Mismatches Using Ultrahigh Resolution Typing in Unrelated Donor Hematopoietic Cell Transplantation

PURPOSE

Ultrahigh resolution (UHR) HLA matching is reported to result in better outcomes following unrelated donor hematopoietic cell transplantation, improving survival and reducing post-transplant complications. However, most studies included relatively small numbers of patients. Here we report the findings from a large, multicenter validation study.

METHODS

UHR HLA typing was available on 5,140 conventionally 10 out of 10 HLA-matched patients with malignant disease transplanted between 2008 and 2017.

RESULTS

After UHR HLA typing, 82% of pairs remained 10 out of 10 UHR-matched; 12.3% of patients were 12 out of 12 UHR HLA-matched. Compared with 12 out of 12 UHR-matched patients, probabilities of grade 2-4 acute graft-versus-host disease (aGVHD) were significantly increased with UHR mismatches (overall P = .0019) and in those patients who were HLA-DPB1 T-cell epitope permissively mismatched or nonpermissively mismatched (overall P = .0011). In the T-cell-depleted subset, the degree of UHR HLA mismatch was only associated with increased transplant-related mortality (TRM) (overall P = .0068). In the T-cell-replete subset, UHR HLA matching was associated with a lower probability of aGVHD (overall P = .0020); 12 out of 12 UHR matching was associated with reduced TRM risk when compared with HLA-DPB1 T-cell epitope permissively mismatched patients, whereas nonpermissive mismatching resulted in a greater risk (overall P = .0003).

CONCLUSION

This study did not confirm that UHR 12 out of 12 HLA matching increases the probability of overall survival but does demonstrate that aGVHD risk, and in certain settings TRM, is lowest in UHR HLA-matched pairs and thus warrants consideration when multiple 10 out of 10 HLA-matched donors of equivalent age are available.

CanImmunother: a manually curated database for identification of cancer immunotherapies associating with biomarkers, targets, and clinical effects

As immunotherapy is evolving into an essential armamentarium against cancers, numerous translational studies associated with relevant biomarkers, targets, and clinical effects have been reported in recent years. However, a large amount of associated experimental data remains unexplored due to the difficulty in accessibility and utilization. Here, we established a comprehensive high-quality database for cancer immunotherapy called CanImmunother (http://www.biomedical-web.com/cancerit/) through manual curation on 4515 publications. CanImmunother contains 3267 experimentally validated associations between 218 cancer sub-types across 34 body parts and 484 immunotherapies with 642 biomarkers, 108 targets, and 121 control therapies. Each association was manually curated by professional curators, incorporated with valuable annotation and cross references, and assigned with an association score for prioritization. To help clinicians and researchers in identifying and discovering better cancer immunotherapy and their respective biomarkers and targets, CanImmunother offers user-friendly web applications including search, browse, excel table, association prioritization, and network visualization. CanImmunother presents a landscape of experimental cancer immunotherapy association data, serving as a useful resource to improve our insight and to facilitate further discovery of advanced immunotherapy options for cancer patients.

HLA-DR Marks Recently Divided Antigen-Specific Effector CD4 T Cells in Active Tuberculosis Patients

Upon Ag encounter, T cells can rapidly divide and form an effector population, which plays an important role in fighting acute infections. In humans, little is known about the molecular markers that distinguish such effector cells from other T cell populations. To address this, we investigated the molecular profile of T cells present in individuals with active tuberculosis (ATB), where we expect Ag encounter and expansion of effector cells to occur at higher frequency in contrast to Mycobacterium tuberculosis-sensitized healthy IGRA+ individuals. We found that the frequency of HLA-DR+ cells was increased in circulating CD4 T cells of ATB patients, and was dominantly expressed in M. tuberculosis Ag-specific CD4 T cells. We tested and confirmed that HLA-DR is a marker of recently divided CD4 T cells upon M. tuberculosis Ag exposure using an in vitro model examining the response of resting memory T cells from healthy IGRA+ to Ags. Thus, HLA-DR marks a CD4 T cell population that can be directly detected ex vivo in human peripheral blood, whose frequency is increased during ATB disease and contains recently divided Ag-specific effector T cells. These findings will facilitate the monitoring and study of disease-specific effector T cell responses in the context of ATB and other infections.

Like Wings of a Bird: Functional Divergence and Complementarity between HLA-A and HLA-B Molecules

Human leukocyte antigen (HLA) genes are among the most polymorphic of our genome, as a likely consequence of balancing selection related to their central role in adaptive immunity. HLA-A and HLA-B genes were recently suggested to evolve through a model of joint divergent asymmetric selection conferring all human populations, including those with severe loss of diversity, an equivalent immune potential. However, the mechanisms by which these two genes might undergo joint evolution while displaying very distinct allelic profiles in populations are still unknown. To address this issue, we carried out extensive data analyses (among which factorial correspondence analysis and linear modeling) on 2,909 common and rare HLA-A, HLA-B, and HLA-C alleles and 200,000 simulated pathogenic peptides by taking into account sequence variation, predicted peptide-binding affinity and HLA allele frequencies in 123 populations worldwide. Our results show that HLA-A and HLA-B (but not HLA-C) molecules maintain considerable functional divergence in almost all populations, which likely plays an instrumental role in their immune defense. We also provide robust evidence of functional complementarity between HLA-A and HLA-B molecules, which display asymmetric relationships in terms of amino acid diversity at both inter- and intraprotein levels and in terms of promiscuous or fastidious peptide-binding specificities. Like two wings of a flying bird, the functional complementarity of HLA-A and HLA-B is a perfect example, in our genome, of duplicated genes sharing their capacity of assuming common vital functions while being submitted to complex and sometimes distinct environmental pressures.

SARS-CoV-2 human T cell epitopes: Adaptive immune response against COVID-19

Over the past year, numerous studies in the peer reviewed and preprint literature have reported on the virological, epidemiological and clinical characteristics of the coronavirus, SARS-CoV-2. To date, 25 studies have investigated and identified SARS-CoV-2-derived T cell epitopes in humans. Here, we review these recent studies, how they were performed, and their findings. We review how epitopes identified throughout the SARS-CoV2 proteome reveal significant correlation between number of epitopes defined and size of the antigen provenance. We also report additional analysis of SARS-CoV-2 human CD4 and CD8 T cell epitope data compiled from these studies, identifying 1,400 different reported SARS-CoV-2 epitopes and revealing discrete immunodominant regions of the virus and epitopes that are more prevalently recognized. This remarkable breadth of epitope repertoire has implications for vaccine design, cross-reactivity, and immune escape by SARS-CoV-2 variants.