Human Leukocyte Antigen Molecules Research Articles

APEX-pHLA: A novel method for accurate prediction of the binding between exogenous short peptides and HLA class I molecules

Human leukocyte antigen (HLA) molecules play critically significant role within the realm of immunotherapy due to their capacities to recognize and bind exogenous antigens such as peptides, subsequently delivering them to immune cells. Predicting the binding between peptides and HLA molecules (pHLA) can expedite the screening of immunogenic peptides and facilitate vaccine design. However, traditional experimental methods are time-consuming and inefficient. In this study, an efficient method based on deep learning was developed for predicting peptide-HLA binding, which treated peptide sequences as linguistic entities. It combined the architectures of textCNN and BiLSTM to create a deep neural network model called APEX-pHLA. This model operated without limitations related to HLA class I allele variants and peptide segment lengths, enabling efficient encoding of sequence features for both HLA and peptide segments. On the independent test set, the model achieved Accuracy, ROC_AUC, F1, and MCC is 0.9449, 0.9850, 0.9453, and 0.8899, respectively. Similarly, on an external test set, the results were 0.9803, 0.9574, 0.8835, and 0.7863, respectively. These findings outperformed fifteen methods previously reported in the literature. The accurate prediction capability of the APEX-pHLA model in peptide-HLA binding might provide valuable insights for future HLA vaccine design.

Frequency of the Main Human Leukocyte Antigen A, B, DR, and DQ Loci Known to Be Associated with the Clearance or Persistence of Hepatitis C Virus Infection in a Healthy Population from the Southern Region of Morocco: A Preliminary Study.

Hepatitis C Virus (HCV) infection represents a significant global health challenge, with its natural course largely influenced by the host's immune response. Human Leukocyte Antigen (HLA) molecules, particularly HLA class I and II, play a crucial role in the adaptive immune response against HCV. The polymorphism of HLA molecules contributes to the variability in immune response, affecting the outcomes of HCV infection. This study aims to investigate the frequency of HLA A, B, DR, and DQ alleles known to be associated with HCV clearance or persistence in a healthy Moroccan population. Conducted at the University Hospital Center Mohammed VI, Marrakech, this study spanned from 2015 to 2022 and included 703 healthy Moroccan individuals. HLA class I and II typing was performed using complement-dependent cytotoxicity and polymerase chain reaction-based methodologies. The results revealed the distinct patterns of HLA-A, B, DRB1, and DQB1 alleles in the Moroccan population. Notably, alleles linked to favorable HCV outcomes, such as HLA-DQB1*0301, DQB1*0501, and DRB1*1101, were more prevalent. Conversely, alleles associated with increased HCV susceptibility and persistence, such as HLA-DQB1*02 and DRB1*03, were also prominent. Gender-specific variations in allele frequencies were observed, providing insights into genetic influences on HCV infection outcomes. The findings align with global trends in HLA allele associations with HCV infection outcomes. The study emphasizes the role of host genetics in HCV infection, highlighting the need for further research in the Moroccan community, including HCV-infected individuals. The prevalence of certain HLA alleles, both protective and susceptibility-linked, underscores the potential for a national HLA data bank in Morocco.

FASTMAP-a flexible and scalable immunopeptidomics pipeline for HLA- and antigen-specific T-cell epitope mapping based on artificial antigen-presenting cells.

The study of peptide repertoires presented by major histocompatibility complex (MHC) molecules and the identification of potential T-cell epitopes contribute to a multitude of immunopeptidome-based treatment approaches. Epitope mapping is essential for the development of promising epitope-based approaches in vaccination as well as for innovative therapeutics for autoimmune diseases, infectious diseases, and cancer. It also plays a critical role in the immunogenicity assessment of protein therapeutics with regard to safety and efficacy concerns. The main challenge emerges from the highly polymorphic nature of the human leukocyte antigen (HLA) molecules leading to the requirement of a peptide mapping strategy for a single HLA allele. As many autoimmune diseases are linked to at least one specific antigen, we established FASTMAP, an innovative strategy to transiently co-transfect a single HLA allele combined with a disease-specific antigen into a human cell line. This approach allows the specific identification of HLA-bound peptides using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Using FASTMAP, we found a comparable spectrum of endogenous peptides presented by the most frequently expressed HLA alleles in the world's population compared to what has been described in literature. To ensure a reliable peptide mapping workflow, we combined the HLA alleles with well-known human model antigens like coagulation factor VIII, acetylcholine receptor subunit alpha, protein structures of the SARS-CoV-2 virus, and myelin basic protein. Using these model antigens, we have been able to identify a broad range of peptides that are in line with already published and in silico predicted T-cell epitopes of the specific HLA/model antigen combination. The transient co-expression of a single affinity-tagged MHC molecule combined with a disease-specific antigen in a human cell line in our FASTMAP pipeline provides the opportunity to identify potential T-cell epitopes/endogenously processed MHC-bound peptides in a very cost-effective, fast, and customizable system with high-throughput potential.

The association of the killer cell immunoglobulin-like receptor (KIR) genotype distribution and HLA-C ligands in colorectal cancer in the eastern region of Saudi Arabia

Colorectal cancer (CRC) is the most common cause of cancer-related mortality globally. It ranks as the most common cancer among men and the third most prevalent among women in Saudi Arabia, especially in the eastern region. The immune system's response to cancer is significantly influenced by natural killer cells through their killer-cell immunoglobulin-like receptors (KIRs) interaction with human leukocyte antigen (HLA) molecules. Our research aimed to target a homogeneous ethnic group in the eastern region of Saudi Arabia, analyzing the distribution of 16 KIR genes and HLA-C1/C2 allotypes in 50 CRC patients and 63 healthy controls using the sequence-specific PCR amplification method. Findings revealed significantly lower frequencies of the 2DL2 and 3DL1 genes in CRC patients compared to controls (OR = 2.21; P = 0.04) and (OR = 7.46; P = 0.00009), respectively. Additionally, a higher prevalence of HLA-C2 was noted in CRC patients (84 %) versus controls (66.7 %) (OR = 2.26; P = 0.04). Conversely, the HLA-C1C2 combination showed a protective effect against CRC (OR = 0.38; P = 0.04). Our combinatorial analysis further identified specific gene combinations correlating with CRC risk or protection. Notably, the absence of KIR2DL2 combined with the presence of KIR2DS2 emerged as a significant risk factor, while various combinations involving KIR2DL2 and/or KIR2DS1 with HLA-C ligands were associated with either increased susceptibility or protection. The study underscores the protective role of KIR2DL2 against CRC in Saudi Arabia's eastern region and suggests that the absence of KIR2DL2, especially when KIR2DS2 is present, might increase CRC risk. This research contributes to understanding genetic influences on CRC susceptibility, emphasizing the potential of KIR and HLA interactions as biomarkers for CRC risk assessment.

Narrative Review Explaining the Role of HLA-A, -B, and -C Molecules in COVID-19 Disease in and around Africa.

The coronavirus disease 2019 (COVID-19) has left a devasting effect on various regions globally. Africa has exceptionally high rates of other infectious diseases, such as tuberculosis (TB), human immunodeficiency virus (HIV), and malaria, and was not impacted by COVID-19 to the extent of other continents Globally, COVID-19 has caused approximately 7 million deaths and 700 million infections thus far. COVID-19 disease severity and susceptibility vary among individuals and populations, which could be attributed to various factors, including the viral strain, host genetics, environment, lifespan, and co-existing conditions. Host genetics play a substantial part in COVID-19 disease severity among individuals. Human leukocyte antigen (HLA) was previously been shown to be very important across host immune responses against viruses. HLA has been a widely studied gene region for various disease associations that have been identified. HLA proteins present peptides to the cytotoxic lymphocytes, which causes an immune response to kill infected cells. The HLA molecule serves as the central region for infectious disease association; therefore, we expect HLA disease association with COVID-19. Therefore, in this narrative review, we look at the HLA gene region, particularly, HLA class I, to understand its role in COVID-19 disease.

Pretransplant, Th17 dominant alloreactivity in highly sensitized kidney transplant candidates

IntroductionSensitization to donor human leukocyte antigen (HLA) molecules prior to transplantation is a significant risk factor for delayed access to transplantation and to long-term outcomes. Memory T cells and their cytokines play a pivotal role in shaping immune responses, thereby increasing the risk of allograft rejection among highly sensitized patients. This study aims to elucidate the precise contribution of different CD4+ memory T cell subsets to alloreactivity in highly sensitized (HS) kidney transplant recipients.Methods and resultsStimulation of peripheral blood mononuclear cells (PBMC) with various polyclonal stimulating agents to assess non-specific immune responses revealed that HS patients exhibit elevated immune reactivity even before kidney transplantation, compared to non-sensitized (NS) patients. HS patients' PBMC displayed higher frequencies of CD4+ T cells expressing IFNγ, IL4, IL6, IL17A, and TNFα and secreted relatively higher levels of IL17A and IL21 upon stimulation with PMA/ionomycin. Additionally, PBMC from HS patients stimulated with T cell stimulating agent phytohemagglutinin (PHA) exhibited elevated expression levels of IFNγ, IL4 and, IL21. On the other hand, stimulation with a combination of resiquimod (R848) and IL2 for the activation of memory B cells demonstrated higher expression of IL17A, TNFα and IL21, as determined by quantitative real-time PCR. A mixed leukocyte reaction (MLR) assay, employing third-party donor antigen presenting cells (APCs), was implemented to evaluate the direct alloreactive response. HS patients demonstrated notably higher frequencies of CD4+ T cells expressing IL4, IL6 and IL17A. Interestingly, APCs expressing recall HLA antigens triggered a stronger Th17 response compared to APCs lacking recall HLA antigens in sensitized patients. Furthermore, donor APCs induced higher activation of effector memory T cells in HS patients as compared to NS patients.ConclusionThese results provide an assessment of pretransplant alloreactive T cell subsets in highly sensitized patients and emphasize the significance of Th17 cells in alloimmune responses. These findings hold promise for the development of treatment strategies tailored to sensitized kidney transplant recipients, with potential clinical implications.

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning.

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan's predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.

Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design.

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient's specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Abstract 1201: Pervasive HLA disruption fuels cancer evolution

Abstract Disruption of the human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. However, although genomic loss of HLA is frequent in non-small cell lung cancer (NSCLC) and in some types of breast cancer, the extent and importance of transcriptomic disruption to HLA presentation, including transcript repression and alternative splicing (AS), remains unclear. To address this, we developed MHC Hammer, a tool to call HLA allele-specific mutations, loss of heterozygosity (LOH), transcriptional repression, and alternative splicing. We first assessed HLA allelic expression and the prevalence of AS in normal tissue. Applying MHC Hammer to 510 normal lung samples and 407 normal breast samples from the Genotype-Tissue Expression cohort, we identified extensive heterogeneity in HLA allelic expression depending on both the allele and tissue type. In addition, HLA allelic AS, occurring in at least 20% of the allele transcripts, was observed in 19% of normal lung and 13% of normal breast samples. Next, we applied MHC Hammer to 413 TRACERx NSCLCs and 743 TCGA breast tumours. While mutations were uncommon, HLA LOH was a frequent event, occurring in 32% of lung adenocarcinomas (LUAD) and 57% of lung squamous cell carcinomas (LUSC). We observed a similar rate of HLA LOH in estrogen receptor positive (ER+) and negative (ER-) tumors (ER+: 14%, ER-: 15%), while in triple negative breast tumours we observed a higher rate of LOH (31%). Due to the heterogeneity in HLA expression observed in the normal samples, to measure tumor specific HLA repression and alternative splicing, we restricted our analysis to tumours with WES, tumor and tumor-adjacent normal RNAseq data. This resulted in a cohort of 88 NSCLCs from the TRACERx study as well as 44 ER+ breast tumours from the TCGA cohort. 61% of LUAD, 75% of LUSC and 35% of ER+ tumours harbored class I HLA transcriptional repression that could not be explained by underlying genomic loss. 27% of LUAD, 7% of LUSC and 55% of ER+ breast tumor patients exhibited no HLA disruption. Tumor specific AS affecting HLA exons 2, 3 or 4, potentially disrupting HLA antigen presentation, was identified in 8% of LUADs, 11% of LUSC and 7% of ER+ breast tumours. Tumor specific AS of exon 5, yielding soluble HLA molecules without a transmembrane domain was identified in 20% of LUAD, 14% of LUSCs and 18% of ER+ breast tumours. LUAD and LUSC tumor regions without HLA LOH or repression were enriched for somatic HLA AS events and alleles with somatic HLA AS had a higher neoantigen burden than those without. We found no relationship between survival and HLA expression or AS in the normal tissue. However, consistent with the importance of HLA dysfunction in tumor evolution, LUADs with low HLA expression in at least one tumor region were associated with shorter disease-free survival, HLA LOH was more common in LUAD’s that metastasized and HLA repression was enriched in LUSC primary regions seeding metastases. Citation Format: Clare Puttick, Thomas P. Jones, Michelle Leung, Oriol Pich, Felipe Galvez Cancino, Jiali Liu, Manuel Varas-Godoy, Andrew Rowan, Carlos Martinez-Ruiz, Robert Bentham, Krijn K. Dijkstra, Rachel Rosenthal, Nnennaya Kanu, Kevin Litchfield, Roberto Salgado, David A. Moore, Peter Van Loo, Mariam Jamal-Hanjani, Sergio A. Quezada, Nicholas McGranahan, Charles Swanton. Pervasive HLA disruption fuels cancer evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1201.

Biomarkers of transfusion transmitted occult hepatitis Bvirus infection: Where are we and what next?

Blood transfusion is a vital procedure, where transfusion-transmitted infection of hepatitis B virus (HBV) remains an important issue, especially from blood donors with occult hepatitis B virus infection (OBI). Occult hepatitis B virus infection is a complex entity to detect using surrogate blood biomarkers for intrahepatic viral transcriptional activity, requiring a continually refined battery of tests utilised for screening. This review aims to critically evaluate the latest advances in the current blood biomarkers to guide the identification of OBI donors and discuss novel HBV markers that could be introduced in future diagnostic practice. Challenges in detecting low HBV surface antigen levels, mutants, and complexes necessitate ultrasensitive multivalent dissociation assays, whilst HBV DNA testing requires improved sensitivity but worsens inaccessibility. Anti-core antibody assays defer almost all potentially infectious donations but have low specificity, and titres of anti-surface antibodies that prevent infectivity are poorly defined with suboptimal sensitivity. The challenges associated with these traditional blood HBV markers create an urgent need for alternative biomarkers that would help us better understand the OBI. Emerging viral biomarkers, such as pre-genomic RNA and HBV core-related antigen, immunological HBV biomarkers of T-cell reactivity and cytokine levels, and host biomarkers of microRNA and human leucocyte antigen molecules, present potential advances to gauge intrahepatic activity more accurately. Further studies on these markers may uncover an optimal diagnostic algorithm for OBI using quantification of various novel and traditional blood HBV markers. Addressing critical knowledge gaps identified in this review would decrease the residual risk of transfusion-transmitted HBV infection without compromising the sustainability of blood supplies.

Investigating the genetic makeup of the major histocompatibility complex (MHC) in the United Arab Emirates population through next-generation sequencing

The Human leukocyte antigen (HLA) molecules are central to immune response and have associations with the phenotypes of various diseases and induced drug toxicity. Further, the role of HLA molecules in presenting antigens significantly affects the transplantation outcome. The objective of this study was to examine the extent of the diversity of HLA alleles in the population of the United Arab Emirates (UAE) using Next-Generation Sequencing methodologies and encompassing a larger cohort of individuals. A cohort of 570 unrelated healthy citizens of the UAE volunteered to provide samples for Whole Genome Sequencing and Whole Exome Sequencing. The definition of the HLA alleles was achieved through the application of the bioinformatics tools, HLA-LA and xHLA. Subsequently, the findings from this study were compared with other local and international datasets. A broad range of HLA alleles in the UAE population, of which some were previously unreported, was identified. A comparison with other populations confirmed the current population’s unique intertwined genetic heritage while highlighting similarities with populations from the Middle East region. Some disease-associated HLA alleles were detected at a frequency of > 5%, such as HLA-B*51:01, HLA-DRB1*03:01, HLA-DRB1*15:01, and HLA-DQB1*02:01. The increase in allele homozygosity, especially for HLA class I genes, was identified in samples with a higher level of genome-wide homozygosity. This highlights a possible effect of consanguinity on the HLA homozygosity. The HLA allele distribution in the UAE population showcases a unique profile, underscoring the need for tailored databases for traditional activities such as unrelated transplant matching and for newer initiatives in precision medicine based on specific populations. This research is part of a concerted effort to improve the knowledge base, particularly in the fields of transplant medicine and investigating disease associations as well as in understanding human migration patterns within the Arabian Peninsula and surrounding regions.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes.

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPSeq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPSeq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells.

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPSeq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPSeq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

Tracking Circulating HLA-Specific IgG-Producing Memory B Cells with the B-Cell ImmunoSpot Assay.

Donor-specific antibodies (DSA) against human leukocyte antigen (HLA) molecules are a major risk factor for rejection of transplanted organs (in antibody-mediated rejection [ABMR]), particularly in patients who have prior sensitization or receive insufficient immunosuppression through minimization or noncompliance. These DSA are measured routinely in the serum of patients prior to transplantation mainly using bead-based technologies or cell-based assays. However, the absence of detectable serum DSA does not always reflect the absence of sensitization or histologically defined ABMR, and so it has been proposed that the detection and measurement of memory B cells capable of secreting antibodies against donor HLA antigens could be carried out using B-cell ImmunoSpot, to better inform the degree of immune sensitization of transplant patients prior to as well as after transplantation. Such an assay is described here.

Interaction Between Genetic Susceptibility and COVID-19 Pathogenesis in Pediatric Multisystem Inflammatory Disorders: The Role of Immune Responses.

Numerous studies have highlighted the emergence of coronavirus disease (COVID-19) symptoms reminiscent of Kawasaki disease in children, including fever, heightened multisystem inflammation, and multiorgan involvement, posing a life-threatening complication. Consequently, extensive research endeavors in pediatric have aimed to elucidate the intricate relationship between COVID-19 infection and the immune system. COVID-19 profoundly impacts immune cells, culminating in a cytokine storm that particularly inflicts damage on the pulmonary system. The gravity and vulnerability to COVID-19 are closely intertwined with the vigor of the immune response. In this context, the human leukocyte antigen (HLA) molecule assumes pivotal significance in shaping immune responses. Genetic scrutiny of HLA has unveiled the presence of at least one deleterious allele in children afflicted with multisystem inflammatory syndrome in children (MIS-C). Furthermore, research has demonstrated that COVID-19 exploits the angiotensin-converting enzyme 2 (ACE-2) receptor, transmembrane serine protease type 2, and various other genes to gain entry into host cells, with individuals harboring ACE-2 polymorphisms being at higher risk. Pediatric studies have employed diverse genetic methodologies, such as genome-wide association studies (GWAS) and whole exome sequencing, to scrutinize target genes. These investigations have pinpointed two specific genomic loci linked to the severity and susceptibility of COVID-19, with the HLA locus emerging as a notable risk factor. In this comprehensive review article, we endeavor to assess the available evidence and consolidate data, offering insights into current clinical practices and delineating avenues for future research. Our objective is to advance early diagnosis, stabilization, and appropriate management strategies to mitigate genetic susceptibility's impact on the incidence of COVID-19 in pediatric patients with multisystem inflammation.

Prevalence of Anti-HLA Antibodies in Multiply Transfused Patients with Hematologic Malignancy

Background: Human leukocyte antigen (HLA) alloimmunization can be induced by exposure to non-self HLA molecules, such as foreign tissue during transplantation, pregnancy, and blood products. Antibodies against HLA lead to serious complications in patients receiving blood transfusions. Objective: The present study aimed to determine the prevalence and risk factors for HLA alloimmunization in multiple transfused patients with hematologic malignancies at Siriraj Hospital. Materials and Methods: The present research was a cross-sectional study. The samples comprised 100 cases of hematologic malignancy patients who had a history of at least three episodes of transfusion with cellular blood components. All patients were tested for anti-HLA class I and class II antibodies by Luminex assay. Results: The overall prevalence of HLA alloimmunization in multiple transfused patients with hematologic malignancies was 40%. Anti-HLA class I, class II, and both class I and class II antibodies were detected in 35%, 30%, and 25% of the patients, respectively. Factors related to the development of anti-HLA antibodies were previous pregnancy (OR 4.82, 95% CI 1.62 to 14.35, p=0.005), five or more transfusions (OR 7.82, 95% CI 2.22 to 27.55, p=0.001), and diagnoses with myelodysplastic syndromes (MDS) antibodies (OR 5.88, 95% CI 1.98 to 17.47, p=0.001). Conclusion: Patients with hematologic malignancies who required long-term blood transfusion support could be at high risk for the development of anti-HLA antibodies. Important risk factors are pregnancy, multiple transfusions, and MDS. Keywords: HLA alloimmunization, Anti-HLA antibodies, Blood transfusions, Hematologic malignancy

The effect of HLA-DP gene polymorphisms in Plasmodium Vivax-induced malaria susceptibility

Plasmodium vivax is the second most common Plasmodium parasite causing clinically serious symptoms and death from malaria. It is an important cause of morbidity and mortality, especially in Asia, the Middle East, and South America. Human leukocyte antigen molecules are responsible for presenting foreign antigens to T cells. Polymorphisms in HLA genes affect antigen presentation. HLA alleles involved in the presentation of P. vivax antigens affect the antibody response. The present study aimed to reveal the relationship of rs3077 and rs9277535 polymorphisms in HLA-DP genes with malaria caused by P. vivax for the first time in the worldwide. In the present research, rs3077 and rs9277535 polymorphisms were investigated in a case–control study of 124 patients with P. vivax-induced malaria and 211 healthy persons by using a real-time polymerase chain reaction (RT-PCR). The results showed that the G alleles of rs3077 and rs9277535 polymorphisms were detected as protective alleles, while the A alleles of both polymorphisms increase the risk of susceptibility to malaria disease. The results of the present study showed that both polymorphisms have a major effect on the susceptibility to malaria caused by P. vivax. We recommend that this study should be conducted in a different population with a larger sample size to confirm our results.

High maternal-fetal HLA eplet compatibility is associated with severe manifestation of preeclampsia.

Preeclampsia is responsible for more than 70 000 and 500 000 maternal and fetal deaths, respectively each year. Incomplete remodelling of the spiral arteries in placenta is the most accepted theory of preeclampsia pathogenesis. However, the process is complexed with immunological background, as pregnancy resembles allograft transplantation. Fetus expresses human leukocyte antigens (HLA) inherited from both parents, thus is semiallogeneic to the maternal immune system. Therefore, induction of fetal tolerance is crucial for physiological outcome of pregnancy. Noteworthy, the immunogenicity of discordant HLA antigens is determined by functional epitopes called eplets, which are continuous and discontinuous short sequences of amino acids. This way various HLA molecules may express the same eplet and some HLA incompatibilities can be more immunogenic due to different eplet combination. Therefore, we hypothesized that maternal- fetal HLA incompatibility may be involved in the pathogenesis of gestational hypertension and its progression to preeclampsia. We also aimed to test if particular maternal-fetal eplet mismatches are more prone for induction of anti- fetal HLA antibodies in gestational hypertension and preeclampsia. High resolution next-generation sequencing of HLA-A, -B, -C, -DQB1 and -DRB1 antigens was performed in mothers and children from physiological pregnancies (12 pairs) and from pregnancies complicated with gestational hypertension (22 pairs) and preeclampsia (27 pairs). In the next step HLA eplet identification and analysis of HLA eplet incompatibilities was performed with in silico approach HLAMatchmaker algorithm. Simultaneously maternal sera were screened for anti-fetal HLA class I, class II and anti-MICA antibodies with Luminex, and data were analyzed with HLA-Fusion software. We observed that high HLA-C, -B, and DQB1 maternal-fetal eplet compatibility was associated with severe preeclampsia (PE) manifestation. Both quantity and quality of HLA epletmismatches affected the severity of PE. Mismatches in HLA-B eplets: 65QIA+76ESN, 70IAO, 180E, HLA-C eplets: 193PL3, 267QE, and HLA-DRB1 eplet: 16Y were associated with a mild outcome of preeclampsia if the complication occurred. High HLA-C, HLA-DQB1 and HLA-B eplet compatibility between mother and child is associated with severe manifestation of preeclampsia. Both quantity and quality of maternal-fetal HLA eplet mismatches affects severity of preeclampsia.

Interindividual HLA Evolutionary Divergence in Single HLA-Mismatched Unrelated Donor Hematopoietic Cell Transplantation for Malignant Hematological Disorders: A Report on Behalf of the Cellular Therapy and Immunobiology Working Party of the EBMT

In allogeneic hematopoietic cell transplantation (allo-HCT), alloreactive T-cell responses (graft versus leukemia - GvL and graft versus host disease - GvHD) are mediated by the interaction between recipient antigens and donor lymphocytes via human leukocyte antigen (HLA) molecules. HLA evolutionary divergence (HED) is a metric recently implemented as a functional proxy for the structural variability between two homologous HLA alleles at their peptide binding sites, mirroring quantitative differences in pathogen and cancer-related immunopeptidomes ( A). 1 Here, we hypothesize that differences in and between donor and recipient HEDs at given loci may modulate the direction and the intensity of alloreactivity, informing on post-transplant outcomes. We tested this hypothesis in onco-hematologic patients undergoing allo-HCT from a single HLA-A, -B, -C, -DRB1, or -DQB1 (9/10) mismatched unrelated donor (MMUD) at EBMT centers. We included patients with selected hematological malignancies, receiving a thymoglobulin-based T cell depletion, for whom complete clinical and HLA information was available in the EBMT database. We deployed individual locus-specific recipient/donor HED (HED-R, HED-D) metrics as previously described 1, and conceptualized two novel interindividual HED scores accounting for functional differences at the mismatched HLA loci ( A). The latter were considered as: 1) DeltaHED, quantifying the relative directional difference between HED-D and HED-R and informing on differences in immunopeptidome sizes, potentially capturing the direction and the intensity of the alloreactive response (GvH or HvG); 2) HEDmismatch, describing the HED of the mismatched locus as a proxy for the qualitative differences in immunopeptidomes between donor and recipient ( B). Using multivariable Cox regression (cause-specific) models adjusted for relevant clinical variables, we investigated the associations of HED-R, DeltaHED and HEDmismatch, analyzed as continuous variables, with relapse free survival (RFS), overall survival (OS), non-relapse mortality (NRM), relapse and grade II-IV acute and chronic GvHD. For each outcome and in each mismatched subgroup, we built separate models for these immunogenetic parameters and checked for proportional hazards assumption (PHA). To account for multiple comparisons, only p-values <0.01 were considered significant. Overall, 4639 adult patients, with available HLA data, received a 9/10 MMUD allo-HCT between 2010 and 2019 for acute leukemia (N=3853, 83%), myelodysplastic syndromes or myeloproliferative neoplasms (N=786, 17%). Median recipient age was 53.5 (IQR 40.2-61.9) with a male/female ratio of 1.28, whilst median donor age was 33.1 (IQR 24.5-40). Majority of patients (90%) received peripheral blood stem cells and were mismatched with their donors for locus A (33%), followed by C (21%), B (15%), DQB1 (14%) and DRB1 (6%). When analyzing the impact of HED-related parameters in each model, we observed that most recurrent associations with outcomes occurred with DRB1-related metrics. In the DRB1-mismatched subgroup (N=276), a time-varying association was found for HEDmismatch of DRB1 locus with higher HEDmismatch leading to worse RFS [HR:1.25 at t=0, (95% CI 1.1-1.42), p<0.001] and lower OS [HR:1.23 at t=0, (95%CI 1.08-1.41), p=0.002]. The strength of this associations declined over time for both endpoints (respectively RFS: HR:0.91, 95% CI 0.86-0.97, p=0.005 and OS: HR:0.93, 95% CI 0.88-0.98, p=0.013). The (directional) DeltaHED DRB1 measure instead did not display any impact on outcomes. In the same subgroup, higher HED-R in the locus C showed also a time-varying association with NRM at transplant [HR:1.89, (95% CI 1.29-2.85), p=0.002], progressively declining over time (HR:0.77, 95% CI 0.65-0.92, p=0.003). Furthermore, DRB1 HED-R modulated the probability of survival in B-mismatched subgroup, being higher scores associated with reduced OS [HR:1.03, (95%CI 1.01-1.06), p=0.009]. Here, we provide an immunogenetic benchmark to explore donor-recipient interactions in MMUD allo-HCT, demonstrating how different HLA configurations within the mismatched loci, in particular for DRB1 genes, can influence post-transplant outcomes. Given the peculiar associations observed, HED may have a role in driving early GvL effects, informing on future donor selection strategies in high-risk patients.