Naming HLA diversity: A review of HLA nomenclature

Comprehensive Annotation of Complete ABO Alleles and Resolution of ABO Variants by an Improved Full-Length ABO Haplotype Sequencing

BACKGROUND

Full-length ABO haplotype sequencing is crucial for accurate genotyping, reference gene annotation, and molecular mechanism analysis of its variants. However, there is currently a deficiency of comprehensive annotation for full-length ABO haplotypes, spanning from the 5' untranslated region (UTR) to the 3' UTR.

METHODS

Two sets of specimens (79 random blood donors and 47 ABO variants) were tested. The full-length ABO gene spanning the 5' UTR to the 3' UTR was amplified using an improved one-step ultra-long-range PCR with a pair of PCR suppression primers. A single-molecule real-time library was constructed, and ABO haplotype sequencing was performed. Data analysis including basecalling, aligning, variant calling, clustering, and variant annotation were performed.

RESULTS

The amplicon measured 26.1 kb without splicing, representing the most complete ABO gene reported to date. The complete ABO haplotype sequence was obtained via long-read sequencing. The comprehensive ABO reference alleles were obtained and the ABO sequence patterns within each allele in a Chinese population were further classified. The full-length ABO gene haplotype analysis technique effectively resolved ABO variants with structural variations (SVs), including large fragment deletions, inversions, recombination, and chimeras.

CONCLUSIONS

Full-length ABO haplotype sequencing filled a gap that was missing with respect to the 3' UTR sequences of ABO alleles and can advance blood group genomic analysis, aiding in ABO gene function analysis, evolutionary studies, and the resolution of ABO variants.

Genetic Diversity and Ethnic Tapestry of Kazakhstan as Inferred from HLA Polymorphism and Population Dynamics: A Comprehensive Review

Background: The human leukocyte antigen (HLA) system represents the most polymorphic segment within human DNA sequences and constitutes a core component of immune defense responses and in understanding population genetics. This research investigates the distribution of HLA class I and II polymorphisms across different ethnic groups in Kazakhstan, offering valuable insights into the genetic diversity and demographic evolution within this region. Methods: We performed an in-depth examination of HLA class I and II polymorphisms across diverse ethnic communities living in Kazakhstan, including Kazakhs, Russians, Uzbeks, Ukrainians, Germans, Tatars, and Koreans. Utilizing data from high-resolution HLA typing studies allowed us to assess allele frequencies alongside haplotype distributions while analyzing genetic interrelations between these populations. Additionally, we performed comparative assessments with global HLA databases to determine the genetic affiliations between these groups and their relationships with neighboring and more distant populations. Results: Our study revealed over 200 HLA alleles within the analyzed populations, and significant variations were observed in their allele and haplotype frequencies. Notably, the Kazakh group exhibited strong genetic ties to Asian and Siberian demographics; conversely, other ethnicities showed associations reflective of their historical roots. Notable alleles included HLA-A*02:01, B*07:02, C*07:02, DRB1*07:01, and DQB1*03:01, commonly observed across various groups. Linkage disequilibrium analysis revealed the presence of population-specific haplotypes, highlighting distinct genetic structures within these communities. Conclusions: The findings highlight the significant genetic diversity in Kazakhstan, influenced by its geographical location at the crossroads of Europe and Asia. These results are pertinent to immunogenetics, transplantation medicine, and personalized healthcare within Kazakhstan and adjacent regions. Future research should expand the sample size and explore disease associations to enhance our comprehension of HLA genetics across Central Asia.

Divergent B-cell and cytotoxic TNK cell activation signatures in HLA-B27-associated ankylosing spondylitis and acute anterior uveitis

Ankylosing spondylitis (AS), also known as radiographic axial spondyloarthritis (r-axSpA), is an immune-mediated inflammatory disorder frequently associated with acute anterior uveitis (AAU). Both conditions share a strong association with the genetic risk factor, human leukocyte antigen (HLA)-B27. However, the immunophenotype underlying HLA-B27-associated AS and/or AAU pathophysiology remains known. Using cellular indexing of transcriptomes and epitopes (CITE-Seq) in a well-characterized cohort of 25 subjects-including AS (HLA-B27pos), AS+AAU (HLA-B27pos), AAU (HLA-B27pos), HCs (HLA-B27pos), and HCs (HLA-B27neg); N = 5/group-we identified transcriptomic differences at the single-cell level, along with differentially expressed cell surface markers. Our study elucidates both shared and distinct immune alterations linked to HLA-B27 and disease. Furthermore, we employed sparse decomposition of arrays (SDA) analysis, an unsupervised machine learning method, to examine the high-dimensional transcriptional landscape of our data and identify complex and nonlinear relationships. Our study identified HLA-B27- and disease-specific transcriptomic differences in AS and AAU. The immune profiles of AS+AAU closely resembled those of AS, suggesting AS plays a dominant role in immune dysregulation. SDA analysis further revealed dysregulated B-cell maturation and activation in AS subjects, whereas AAU subjects exhibited an enrichment of cytotoxic effector function in T and NK cells. However, both AS and AAU exhibited myeloid cell activation, a key process in initiating and sustaining inflammation. Additionally, both AS and AAU subjects showed a dampening in homeostatic function, i.e., the balance between identifying and actively eliminating foreign pathogens while preventing an immune response against self-antigens, suggesting that inflammation may arise from immune dysregulation. In conclusion, our results highlight overlapping myeloid effector involvement, along with distinct immunophenotypic responses, such as a decrease in naive B cells in AS subjects and a reduction in the CD8/NK cell population in AAU subjects. These results highlight a distinct set of immune mediators driving AS and AAU pathogenesis. Future studies incorporating HLA-B27-negative AS and AAU patients, along with validation of B-cell and myeloid dysfunction in these diseases, may provide novel biomarkers and therapeutic targets.

A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools: OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm.

Hiding in plain sight: Misinterpretation of immunogenic DPB epitopes within G/P groups

The clinical impact of HLA DP antibodies is poorly understood, resulting in variable clinical strategies for transplant candidates and recipients with donor-directed HLA-DP antibodies. Complicating matters further, the DPB naming convention is not based on allelic homology and requires sequence alignments to identify potential immunogenic epitopes. Historically, G and P codes, which consolidated alleles that were identical over Exon 2, were used to simplify the reporting of HLA Class II typing as differences outside of Exon 2 have not been considered immunogenic (i.e., able to induce an antibody response). Herein, we present four cases demonstrating that polymorphisms at codons 96R/K and 170I/T, in Exon 3 of DPB, are targets for alloantibody recognition. These regions "hide in plain sight" due to the current use of G/P code-level typing, potentially leading to incorrect compatibility assessments (i.e., virtual crossmatches) and misinterpreted antibody responses. The unintentional crossing of an HLA-DPB donor-specific antibody (DSA) in a solid organ or hematopoietic stem cell transplant may lead to unforeseen deleterious clinical outcomes. Our data underscore the complexities of DPB histocompatibility assessments and highlight the need for adaptable systems that align with evolving research and clinical outcomes.

The Primate Major Histocompatibility Complex: An Illustrative Example of Gene Family Evolution

Gene families are groups of evolutionarily-related genes. One large gene family that has experienced rapid evolution is the Major Histocompatibility Complex (MHC), whose proteins serve critical roles in innate and adaptive immunity. Across the ~60 million year history of the primates, some MHC genes have turned over completely, some have changed function, some have converged in function, and others have remained essentially unchanged. Past work has typically focused on identifying MHC alleles within particular species or comparing gene content, but more work is needed to understand the overall evolution of the gene family across species. Thus, despite the immunologic importance of the MHC and its peculiar evolutionary history, we lack a complete picture of MHC evolution in the primates. We readdress this question using sequences from dozens of MHC genes and pseudogenes spanning the entire primate order, building a comprehensive set of gene and allele trees with modern methods. Overall, we find that the Class I gene subfamily is evolving much more quickly than the Class II gene subfamily, with the exception of the Class II MHC-DRB genes. We also pay special attention to the often-ignored pseudogenes, which we use to reconstruct different events in the evolution of the Class I region. We find that despite the shared function of the MHC across species, different species employ different genes, haplotypes, and patterns of variation to achieve a successful immune response. Our trees and extensive literature review represent the most comprehensive look into MHC evolution to date.

Variation within the non-coding genome influences genetic and epigenetic regulation of the human leukocyte antigen genes

Variation within the non-coding genome may influence the regulation and expression of important genes involved in immune control such as the human leukocyte antigen (HLA) system. Class I and Class II HLA molecules are essential for peptide presentation which is required for T lymphocyte activation. Single nucleotide polymorphisms within non-coding regions of HLA Class I and Class II genes may influence the expression of these genes by affecting the binding of transcription factors and chromatin modeling molecules. Furthermore, an interplay between genetic and epigenetic factors may also influence HLA expression. Epigenetic factors such as DNA methylation and non-coding RNA, regulate gene expression without changing the DNA sequence. However, genetic variation may promote or allow genes to escape regulation by epigenetic factors, resulting in altered expression. The HLA system is central to most diseases, therefore, understanding the role of genetics and epigenetics on HLA regulation will tremendously impact healthcare. The knowledge gained from these studies may lead to novel and cost-effective diagnostic approaches and therapeutic interventions. This review discusses the role of non-coding variants on HLA regulation. Furthermore, we discuss the interplay between genetic and epigenetic factors on the regulation of HLA by evaluating literature based on polymorphisms within DNA methylation and miRNA regulatory sites within class I and Class II HLA genes. We also provide insight into the importance of the HLA non-coding genome on disease, discuss ethnic-specific differences across the HLA region and provide guidelines for future HLA studies.

Fifty years of HLA-associated type 1 diabetes risk: history, current knowledge, and future directions

More than 50 years have elapsed since the association of human leukocyte antigens (HLA) with type 1 diabetes (T1D) was first reported. Since then, methods for identification of HLA have progressed from cell based to DNA based, and the number of recognized HLA variants has grown from a few to tens of thousands. Current genotyping methodology allows for exact identification of all HLA-encoding genes in an individual's genome, with statistical analysis methods evolving to digest the enormous amount of data that can be produced at an astonishing rate. The HLA region of the genome has been repeatedly shown to be the most important genetic risk factor for T1D, and the original reported associations have been replicated, refined, and expanded. Even with the remarkable progress through 50 years and over 5,000 reports, a comprehensive understanding of all effects of HLA on T1D remains elusive. This report represents a summary of the field as it evolved and as it stands now, enumerating many past and present challenges, and suggests possible paradigm shifts for moving forward with future studies in hopes of finally understanding all the ways in which HLA influences the pathophysiology of T1D.

Haplotype Analysis Reveals Pleiotropic Disease Associations in the HLA Region

The human leukocyte antigen (HLA) region plays an important role in human health through involvement in immune cell recognition and maturation. While genetic variation in the HLA region is associated with many diseases, the pleiotropic patterns of these associations have not been systematically investigated. Here, we developed a haplotype approach to investigate disease associations phenome-wide for 412,181 Finnish individuals and 2,459 traits. Across the 1,035 diseases with a GWAS association, we found a 17-fold average per-SNP enrichment of hits in the HLA region. Altogether, we identified 7,649 HLA associations across 647 traits, including 1,750 associations uncovered by haplotype analysis. We find some haplotypes show trade-offs between diseases, while others consistently increase risk across traits, indicating a complex pleiotropic landscape involving a range of diseases. This study highlights the extensive impact of HLA variation on disease risk, and underscores the importance of classical and non-classical genes, as well as non-coding variation.

Gemcitabine Modulates HLA-I Regulation to Improve Tumor Antigen Presentation by Pancreatic Cancer Cells

Pancreatic cancer is a lethal disease, harboring a five-year overall survival rate of only 13%. Current treatment approaches thus require modulation, with attention shifting towards liberating the stalled efficacy of immunotherapies. Select chemotherapy drugs which possess inherent immune-modifying behaviors could revitalize immune activity against pancreatic tumors and potentiate immunotherapeutic success. In this study, we characterized the influence of gemcitabine, a chemotherapy drug approved for the treatment of pancreatic cancer, on tumor antigen presentation by human leukocyte antigen class I (HLA-I). Gemcitabine increased pancreatic cancer cells' HLA-I mRNA transcripts, total protein, surface expression, and surface stability. Temperature-dependent assay results indicated that the increased HLA-I stability may be due to reduced binding of low affinity peptides. Mass spectrometry analysis confirmed changes in the HLA-I-presented peptide pool post-treatment, and computational predictions suggested improved affinity and immunogenicity of peptides displayed solely by gemcitabine-treated cells. Most of the gemcitabine-exclusive peptides were derived from unique source proteins, with a notable overrepresentation of translation-related proteins. Gemcitabine also increased expression of select immunoproteasome subunits, providing a plausible mechanism for its modulation of the HLA-I-bound peptidome. Our work supports continued investigation of immunotherapies, including peptide-based vaccines, to be used with gemcitabine as new combination treatment modalities for pancreatic cancer.

Association of HLA gene polymorphisms with Helicobacter pylori related gastric cancer-a systematic review

The appropriate host cell immune responses for the progression of several diseases, including gastric or stomach cancer (GC), are significantly influenced by HLA polymorphisms. Our objective was to systematically review the evidence linking HLA polymorphisms with the risk of Helicobacter. pylori related GC. We conducted a comprehensive literature search to identify studies published between 2000 and April 2023 on the association of HLA polymorphisms with H. pylori related GC using databases such as Medline through PubMed, Embase, Web of Science (core collection), The Cochrane Library, and Scopus. Two authors independently screened articles, extracted data, and assessed the risk of bias using the Risk of Bias Assessment tool for Non-randomized Studies. From 7872 retrieved studies, 19 met inclusion criteria, encompassing 1656 cases and 16,787 controls across four World Health Organization regions, with Japan contributing the most studies. We explored HLA-A/B/C, HLA-DRB1/DQA1/DQB1, HLA-G, and MICA alleles. Of 29 significant HLA polymorphisms identified, 18 showed a positive association with GC, whereas 11 were negatively associated. HLA-DQB1*06 allele was most frequently associated to susceptibility, as reported in four studies, followed by HLA-DRB1*04 and HLA-DQA1*01, each reported in two studies. Conversely, HLA-G*01, HLA-DQA1*01, HLA-DQA1*05, and HLA-DQB1*03 were identified as protective in two studies each. Additionally, five genotypes and six haplotypes were reported as positive, whereas three genotypes and two haplotypes were negative factors for the disease incidence or mortality. Despite heterogeneity in the study population and types of HLA polymorphisms examined, our analysis indicates certain polymorphisms are associated with H. pylori related GC progression and mortality in specific populations.

Eligibility for Human Leukocyte Antigen-Based Therapeutics by Race and Ethnicity

Importance

The development of therapeutics for patients who are positive for specific human leukocyte antigen (HLA) subtypes evokes the question of whether certain racial and ethnic groups are more or less likely to be eligible for novel products.

Objective

To determine whether racial and ethnic inequities were present with regard to trial eligibility in trials investigating a therapeutic restricted to patients with specific HLA subtypes.

Design, Setting, and Participants

This cross-sectional study included all clinical trials registered in ClinicalTrials.gov through March 18, 2022, that investigated an interventional study of a therapeutic strategy and restricted participants to those with at least 1 HLA subtype. Data were analyzed from May 8 to July 1, 2022.

Main Outcomes and Measures

The type of therapeutics used in trials, the condition under study, the HLA subtypes used, and the likelihood of being enrolled in such a trial according to race and ethnicity.

Results

Of 2135 trials identified, 263 met inclusion criteria. Overall, the estimated likelihood of being eligible for an HLA-based trial was 50.3%. Individuals of African American descent had the lowest likelihood of eligibility (33.0%), while being an individual of European descent conferred the highest (53.0%; 1.6 times more likely than African American individuals). Most trials studied anticancer therapeutics (258 [98.1%; 95% CI, 96.4%-99.7%]), and most were a therapeutic vaccine (179 [68.1%; 95% CI, 62.4%-73.7%]). The HLA-A*02:01 allele and the HLA-A2 serotype were the most frequent HLA subtypes for trial eligibility. The frequency of the HLA-A*02:01 allele in the population varied, with 11.9% (95% CI, 11.8%-12.0%) in African or African American individuals and 27.1% (95% CI, 27.1%-27.1%) in individuals of European descent.

Conclusions and Relevance

The findings of this cross-sectional study suggest that enrollment restrictions for clinical trials investigating novel HLA therapeutics may be associated with racial and ethnic inequities with regard to trial eligibility. Overcoming these restrictions poses biological challenges, but solutions must be implemented to provide equal access to innovative strategies regardless of race or ethnicity.

Neoantigen identification: Technological advances and challenges

Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.

Advancing cell-based cancer immunotherapy through stem cell engineering

Advances in cell-based therapy, particularly CAR-T cell therapy, have transformed the treatment of hematological malignancies. Although an important step forward for the field, autologous CAR-T therapies are hindered by high costs, manufacturing challenges, and limited efficacy against solid tumors. With ongoing progress in gene editing and culture techniques, engineered stem cells and their application in cell therapy are poised to address some of these challenges. Here, we review stem cell-based immunotherapy approaches, stem cell sources, gene engineering and manufacturing strategies, therapeutic platforms, and clinical trials, as well as challenges and future directions for the field.

Re-generation of cytotoxic γδT cells with distinctive signatures from human γδT-derived iPSCs

For a long time, ex vivo-expanded peripheral-blood-derived γδT cell (PBγδT)-based immunotherapy has been attractive, and clinical trials have been undertaken. However, the difficulty in expanding cytotoxic γδT cells to an adequate number has been a major limitation to the efficacy of treatment in most cases. We successfully re-generated γδT cells from γδT cell-derived human induced pluripotent stem cells (iPSCs). The iPSC-derived γδT cells (iγδTs) killed several cancer types in a major histocompatibility complex (MHC)-unrestricted manner. Single-cell RNA sequencing (scRNA-seq) revealed that the iγδTs were identical to a minor subset of PBγδTs. Compared with a major subset of PBγδTs, the iγδTs showed a distinctive gene expression pattern: lower CD2, CD5, and antigen-presenting genes; higher CD7, KIT, and natural killer (NK) cell markers. The iγδTs expressed granzyme B and perforin but not interferon gamma (IFNγ). Our data provide a new source for γδT cell-based immunotherapy without quantitative limitation.

Identification of the novel HLA-B*50:01:17 allele by polymerase chain reaction sequence-based typing

HLA-B*50:01:17 shows one nucleotide substitution at position 861 when compared with HLA-B*50:01:01:01.

Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections

The human leukocyte antigen (HLA) system is one of the most crucial host factors influencing disease progression in bacterial and viral infections. This review provides the basic concepts of the structure and function of HLA molecules in humans. Here, we highlight the main findings on the associations between HLA class I and class II alleles and susceptibility to important infectious diseases such as tuberculosis, leprosy, melioidosis, Staphylococcus aureus infection, human immunodeficiency virus infection, coronavirus disease 2019, hepatitis B, and hepatitis C in populations worldwide. Finally, we discuss challenges in HLA typing to predict disease outcomes in clinical implementation. Evaluation of the impact of HLA variants on the outcome of bacterial and viral infections would improve the understanding of pathogenesis and identify those at risk from infectious diseases in distinct populations and may improve the individual treatment.

Glycolysis-Related Gene Signature Can Predict Survival and Immune Status of Hepatocellular Carcinoma

BACKGROUND

Concise and precise prognostic models are urgently needed due to the intricate genetic variations among hepatocellular carcinoma (HCC) cells. Disorder or change in glycolysis metabolism has been considered one of the "hallmarks" of cancer. However, the prognostic value of glycolysis-related genes in HCC remains elusive.

METHODS

A multigene prognostic model was constructed by least absolute shrinkage and selection operator Cox regression analysis in the The Cancer Genome Atlas (TCGA) cohort with 365 HCC patients and validated in the International Cancer Genome Consortium (ICGC) cohort with 231 HCC patients. The Kaplan-Meier methodology and time-dependent receiver operating characteristic curve were employed to confirm its predictive capability. A predictive nomogram was established based on the stepwise multivariate regression model. The differential expression of prognostic genes between HCC tissues and normal tissues was verified by quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry in an independent sample cohort with 30 HCC patients.

RESULTS

The glycolysis-related gene signature and the nomogram model exhibited robust validity in predicting prognosis. The risk score was an independent predictor for overall survival (OS). Expression levels of immune checkpoint genes and cell cycle genes were significantly elevated in the high-risk group. The high-risk group presented high levels of immune exclusion. The risk score can distinguish the effect of immunotherapy in the IMvigor210 cohort. The prognostic gene expression showed a significant difference between HCC tissues and adjacent nontumorous tissues in the independent sample cohort.

CONCLUSION

The currently established glycolysis-related gene signature can accurately predict prognosis and reflect immune status, which may be a therapeutic alternative.

HLA-EPI: A new EPIsode in exploring donor/recipient epitopic compatibilities

The HLA system plays a pivotal role both in transplantation and immunology. While classical HLA genotypes matching is made at the allelic level, recent progresses were developed to explore antibody–antigen recognition by studying epitopes. Donor to recipient matching at the epitopic level is becoming a trending topic in the transplantation research field because anti‐HLA antibodies are epitope‐specific rather than allele‐specific. Indeed, different HLA alleles often share common epitopes. We present the HLA‐Epi tool (hla.univ-nantes.fr) to study an HLA genotype at the epitope level. Using the international HLA epitope registry (Epregistry.com.br) as a reference, we developed HLA‐Epi to easily determine epitopic and allelic compatibility levels between several HLA genotypes. The epitope database covers the most common HLA alleles (N = 2976 HLA alleles), representing more than 99% of the total observed frequency of HLA alleles. The freely accessible web tool HLA‐Epi calculates an epitopic mismatch load between different sets of potential recipient‐donor pairs at different resolution levels. We have characterized the epitopic mismatches distribution in a cohort of more than 10,000 kidney transplanted pairs from European ancestry, which showed low number of epitopic mismatches: 56.9 incompatibilities on average. HLA‐Epi allows the exploration of epitope pairing matching to better understand epitopes contribution to immune responses regulation, particularly during transplantation. This free and ready‐to‐use bioinformatics tool not only addresses limitations of other related tools, but also offers a cost‐efficient and reproducible strategy to analyze HLA epitopes as an alternative to HLA allele compatibility. In the future, this could improve sensitization prevention for allograft allocation decisions and reduce the risk of alloreactivity.

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.

Next-generation sequencing and clinical histocompatibility testing

Histocompatibility testing is essential for donor identification and risk assessment in solid organ and hematopoietic stem cell transplant. Additionally, it is useful for identifying donor specific alleles for monitoring donor specific antibodies in post-transplant patients. Next-generation sequence (NGS) based human leukocyte antigen (HLA) typing has improved many aspects of histocompatibility testing in hematopoietic stem cell and solid organ transplant. HLA disease association testing and research has also benefited from the advent of NGS technologies. In this review we discuss the current impact and future applications of NGS typing on clinical histocompatibility testing for transplant and non-transplant purposes.

The Path to Conserved Extended Haplotypes: Megabase-Length Haplotypes at High Population Frequency

This minireview describes the history of the conceptual development of conserved extended haplotypes (CEHs): megabase-length haplotypes that exist at high (≥0.5%) population frequency. My career began in internal medicine, shifted to pediatrics, and clinical practice changed to research. My research interest was initially in hematology: on plasma proteins, their metabolism, synthesis, and function. This narrowed to a focus on proteins of the human complement system, their role in immunity and their genetics, beginning with polymorphism and deficiency of C3. My group identified genetic polymorphisms and/or inherited deficiencies of C2, C4, C6, and C8. After defining glycine-rich beta glycoprotein as factor B (Bf) in the properdin system, we found that the genes for Bf (CFB), C2, C4A, and C4B were inherited as a single haplotypic unit which we named the "complotype." Complotypes are located within the major histocompatibility complex (MHC) between HLA-B and HLA-DRB1 and are designated (in arbitrary order) by their CFB, C2, C4A, and C4B types. Pedigree analysis revealed long stretches (several megabases) of apparently fixed DNA within the MHC that we referred to as "extended haplotypes" (later as "CEHs"). About 10 to 12 common CEHs constitute at least 25 - 30% of MHC haplotypes among European Caucasian populations. These CEHs contain virtually all the most common markers of MHC-associated diseases. In the case of type 1 diabetes, we have proposed a purely genetic and epigenetic model (with a small number of Mendelian recessive disease genes) that explains all the puzzling features of the disease, including its rising incidence.

Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis

Background:

Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC.

Methods:

Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 10⁶. Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package.

Results:

HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort (P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort (P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I.

Conclusion:

In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer.

Origin of the Ukrainian minority of Kazakhstan as inferred from HLA-A, -B, -C, -DRB1, and -DQB1 alleles and haplotypes distribution

The present-day population of Kazakhstan comprises more than a hundred ethnic and linguistic groups, of which Ukrainians rates numerically as the fourth, following native Kazakhs, Russians, and Uzbeks. We investigated the HLA profile of Kazakhstani Ukrainians and compared them with those of other populations by applying genetic distances, correspondence analysis, admixture, and haplotype examination. Of the 128 HLA alleles identified, A*02:01 (28.64%), B*07:02 (9.71%), B*13:02 (9.71%), C*06:02 (15.05%), DRB1*07:01 (15.20%), and DQB1*03:01 (24.76%) were the utmost common alleles. The most common 2-locus haplotypes identified were A*02:01 ~ B*13:02 (6.66%), B*13:02 ~ DRB1*07:01 (6.57%), B*13:02 ~ C*06:02 (10.10%), and DRB1*01:01 ~ DQB1*05:01 (12.12%), while A*02:01 ~ B*13:02 ~ C*06:02 ~ DRB1*07:01 ~ DQB1*02:01 were the most frequent five-locus haplotype (4.04%) in Kazakhstani Ukrainians. Comparative analysis revealed that Ukrainians of Kazakhstan are closely related to Eastern Europeans (included Ukrainians), and European Russians, but distant from Asian populations. This supports the historical notion that Kazakhstani Ukrainians originated from Ukraine, following their massive migrations to central Asia in the 18th-20th centuries. This article is protected by copyright. All rights reserved.

The changing landscape of HLA typing: Understanding how and when HLA typing data can be used with confidence from bench to bedside

Human leukocyte antigen (HLA) genes are extraordinary for their extreme diversity and widespread impact on human health and disease. More than 30,000 HLA alleles have been officially named and more alleles continue to be discovered at a rapid pace. HLA typing systems which have been developed to detect HLA diversity have advanced rapidly and are revolutionizing our understanding of HLA's clinical importance. However, continuous improvements in knowledge and technology have created challenges for clinicians and scientists. This review explains how differences in HLA typing systems can impact the HLA types that are assigned. The consequences of differences in laboratory testing methods and reference databases are described. The challenges of using HLA types that are not equivalent are illustrated. A fundamental understanding of the continual expansion of our understanding of HLA diversity and limitations in some of the typing data is essential for using typing data appropriately in clinical and research settings.

A Direct Role for the CD1b Endogenous Spacer in the Recognition of a Mycobacterium tuberculosis Antigen by T-Cell Receptors

Lipids, glycolipids and lipopeptides derived from Mycobacterium tuberculosis (Mtb) are presented to T cells by monomorphic molecules known as CD1. This is the case of the Mtb-specific sulfoglycolipid Ac2SGL, which is presented by CD1b molecules and is recognized by T cells found in tuberculosis (TB) patients and in individuals with latent infections. Our group, using filamentous phage display technology, obtained two specific ligands against the CD1b-Ac2SGL complex: (i) a single chain T cell receptor (scTCR) from a human T cell clone recognizing the CD1b-AcSGL complex; and (ii) a light chain domain antibody (dAbκ11). Both ligands showed lower reactivity to a synthetic analog of Ac2SGL (SGL12), having a shorter acyl chain as compared to the natural antigen. Here we put forward the hypothesis that the CD1b endogenous spacer lipid (EnSpacer) plays an important role in the recognition of the CD1b-Ac2SGL complex by specific T cells. To support this hypothesis we combined: (a) molecular binding assays for both the scTCR and the dAbκ11 antibody domain against a small panel of synthetic Ac2SGL analogs having different acyl chains, (b) molecular modeling of the CD1b-Ac2SGL/EnSpacer complex, and (c) modeling of the interactions of this complex with the scTCR. Our results contribute to understand the mechanisms of lipid presentation by CD1b molecules and their interactions with T-cell receptors and other specific ligands, which may help to develop specific tools targeting Mtb infected cells for therapeutic and diagnostic applications.

Current Challenges in Vaccinology

The development of vaccines, which prime the immune system to respond to future infections, has led to global declines in morbidity and mortality from dreadful infectious communicable diseases. However, many pathogens of public health importance are highly complex and/or rapidly evolving, posing unique challenges to vaccine development. Several of these challenges include an incomplete understanding of how immunity develops, host and pathogen genetic variability, and an increased societal skepticism regarding vaccine safety. In particular, new high-dimensional omics technologies, aided by bioinformatics, are driving new vaccine development (vaccinomics). Informed by recent insights into pathogen biology, host genetic diversity, and immunology, the increasing use of genomic approaches is leading to new models and understanding of host immune system responses that may provide solutions in the rapid development of novel vaccine candidates.