Human Leukocyte Antigen Molecules Research Articles

MHC Hammer reveals genetic and non-genetic HLA disruption in cancer evolution.

Disruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. We developed major histocompatibility complex loss of heterozygosity (LOH), allele-specific mutation and measurement of expression and repression (MHC Hammer). We identified extensive variability in HLA allelic expression and pervasive HLA alternative splicing in normal lung and breast tissue. In lung TRACERx and lung and breast TCGA cohorts, 61% of lung adenocarcinoma (LUAD), 76% of lung squamous cell carcinoma (LUSC) and 35% of estrogen receptor-positive (ER+) cancers harbored class I HLA transcriptional repression, while HLA tumor-enriched alternative splicing occurred in 31%, 11% and 15% of LUAD, LUSC and ER+ cancers. Consistent with the importance of HLA dysfunction in tumor evolution, in LUADs, HLA LOH was associated with metastasis and LUAD primary tumor regions seeding a metastasis had a lower effective neoantigen burden than non-seeding regions. These data highlight the extent and importance of HLA transcriptomic disruption, including repression and alternative splicing in cancer evolution.

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.

HLA-A01 and HLA-B27 Supertypes, but Not HLA Homozygocity, Correlate with Clinical Outcome among Patients with Non-Small Cell Lung Cancer Treated with Pembrolizumab in Combination with Chemotherapy.

Maximal heterozygosity on the human leukocyte antigen (HLA) loci has been found to be associated with improved survival and development of immune-related adverse events (irAEs) among NSCLC patients treated with immunotherapy. Here, we investigated the effect of germline HLA-I/-II on clinical outcomes among NSCLC patients treated with first-line pembrolizumab in combination with chemotherapy. We prospectively recruited patients with NSCLC who were commencing first-line pembrolizumab in combination with chemotherapy. DNA from white blood cells was used for high-resolution HLA-I/II typing. Of the 65 patients recruited, 53 complied with the inclusion criteria. We did not find an association between HLA-I/-II homozygosity and clinical outcome among the studied population. However, the presence of HLA-A01 was associated with unfavourable PFS (HR = 2.32, 95%CI 1.13-4.77, p = 0.022) and worsening OS (HR = 2.86, 95%CI 1.06-7.70, p = 0.038). The presence of HLA-B27 was associated with improved PFS (HR = 0.35, 95%CI 0.18-0.71, p = 0.004) and trends toward improving OS. None of the HLA-I supertypes were associated with the development or worsening of irAEs. The absence of association between genomic HLA-I/-II homozygosity and clinical outcome among patients with advanced NSCLC treated with pembrolizumab in combination with chemotherapy might reflect a diminished role for HLA molecules among patients with low or no PD-L1. HLA-A01 and HLA-B27 might have a role in predicting clinical outcomes among this cohort of patients. Further studies are needed to explore biomarkers for this group of patients.

Crucial Parameters for Immunopeptidome Characterization: A Systematic Evaluation.

Immunopeptidomics is the area of knowledge focused on the study of peptides assembled in the major histocompatibility complex (MHC), or human leukocyte antigen (HLA) in humans, which could activate the immune response via specific and selective T cell recognition. Advances in high-sensitivity mass spectrometry have enabled the detailed identification and quantification of the immunopeptidome, significantly impacting fields like oncology, infections, and autoimmune diseases. Current immunopeptidomics approaches primarily focus on workflows to identify immunopeptides from HLA molecules, requiring the isolation of the HLA from relevant cells or tissues. Common critical steps in these workflows, such as cell lysis, HLA immunoenrichment, and peptide isolation, significantly influence outcomes. A systematic evaluation of these steps led to the creation of an 'Immunopeptidome Score' to enhance the reproducibility and robustness of these workflows. This score, derived from LC-MS/MS datasets (ProteomeXchange identifier PXD038165), in combination with available information from public databases, aids in optimizing the immunopeptidome characterization process. The 'Immunopeptidome Score' has been applied in a systematic analysis of protein extraction, HLA immunoprecipitation, and peptide recovery yields across several tumor cell lines enabling the selection of peptides with optimal features and, therefore, the identification of potential biomarker and therapeutic targets.

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma

BackgroundTreatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood.MethodsThe differential expression of ALOX5AP was evaluated based on public Databases. Kaplan–Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray.ResultALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma.ConclusionALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Immunogenicity of a peptide-based vaccine for measles: a pilot evaluation in a mouse model

Although neutralizing antibody is an established correlate of protection for measles, T cell-mediated responses play at least two critical roles in immunity to measles: first, through provision of ‘help’ enabling robust humoral immune responses; and second, through clearance of measles virus-infected cells. Previously, we identified 13 measles-derived peptides that bound to human leukocyte antigen (HLA) molecules in Priess cells infected with measles virus. In this study, we evaluated the immunogenicity of these peptides in a transgenic mouse model. Our results demonstrated that these peptides induced Th1-biased immune responses at varying levels. Of the 13 peptides, the top four immunogenic peptides were further selected for a viral challenge study in mice. A vaccine based on a combination of these four peptides reduced morbidity and weight loss after viral challenge compared to placebo. Our results emphasize the potential of T cell-mediated, peptide-based vaccines against measles.

Understanding and Therapeutic Application of Immune Response in Major Histocompatibility Complex (MHC) Diversity Using Multimodal Artificial Intelligence

Human Leukocyte Antigen (HLA) is like a device that monitors the internal environment of the body. T lymphocytes immediately recognize the HLA molecules that are expressed on the surface of the cells of the different individual, attacking it defeats microorganisms that is one of the causes of rejection in organ transplants performed between people with unmatched HLA types. Over 2850 and 3580 different polymorphisms have been reported for HLA-A and HLA-B respectively, around the world. HLA genes are associated with the risk of developing a variety of diseases, including autoimmune diseases, and play an important role in pathological conditions. By using a deep learning method called multi-task learning to simultaneously predict the gene sequences of multiple HLA genes, it is possible to improve accuracy and shorten execution time. Some new systems use a model called convolutional neural network (CNNs) in deep learning, which uses neural networks consisting of many layers and can learn complex correlations between SNP information and HLA gene sequences based on reference data for HLA imputation, which serves as training data. The learned model can output predicted values of HLA gene sequences with high accuracy using SNP information as input. To investigate which part of the input information surrounding the HLA gene is used to make learning predictions, predictions were made using not only a small number of nearby SNP information but also many SNP information distributed over a wider area by visualizing the learning information of the model. While conventional methods are strong at learning using nearly SNP information and not good at learning using SNP information located at distant locations, some new systems are thought that prediction accuracy may have improved because this problem was overcome. HLA genes are involved in the onset of a variety of diseases and are attracting attention. As an important area from the perspective of elucidating pathological conditions and realizing personalized medicine. The applied multi-task learning to two different HLA imputation reference panels—a Japanese panel (n = 1118) and type I diabetes genetics consortium panel (n = 5122). Through 10-fold cross-validation on these panels, the multi-task learning achieved higher imputation accuracy than conventional methods, especially for imputing low-frequency and rare HLA alleles. The increased prediction accuracy of HLA gene sequences is expected to increase the reliability of HLA analysis, including integrated analysis between different racial populations, and is expected to greatly contribute to the identification of HLA gene sequences associated with diseases and further elucidation of pathological conditions.

Analysis of HLA Alleles in Different Cohorts of Patients Infected by L. infantum from Southern Spain.

Leishmaniasis is an infectious disease caused by protozoa of the genus Leishmania, which is endemic in certain areas of Europe, such as southern Spain. The disease manifests in various clinical phenotypes, including visceral, cutaneous, mucosal, or asymptomatic leishmaniasis. This diversity in clinical outcomes may be influenced by the host immune response, with human leukocyte antigen (HLA) molecules playing a crucial role in determining susceptibility and progression of the infection. This study explores the association between specific HLA variants and Leishmania infantum infection. We recruited four cohorts: a control group, asymptomatic individuals, patients with symptomatic disease, and cohabitants of infected individuals. HLA typing was performed for all participants, followed by an association analysis with infection status and disease progression. Our findings indicate that the HLA-B*38 and HLA-C*03 alleles are associated with protection against L. infantum infection. These results contribute to a better understanding of the disease's progression, offer potential for new therapeutic approaches such as vaccines, and expand the existing knowledge in the literature.

Association of HLA alleles with cephalosporin allergy in the Taiwanese population

Cephalosporin antibiotics are widely used in clinical settings, but they can cause hypersensitivity reactions, which may be influenced by genetic factors such as the expression of Human leukocyte antigen (HLA) molecules. This study aimed to investigate whether specific HLA alleles were associated with an increased risk of adverse reactions to cephalosporins among individuals in the Taiwanese population. This retrospective case–control study analyzed data from the Taiwan Precision Medicine Initiative (TPMI) on 27,933 individuals who received cephalosporin exposure and had HLA allele genotyping information available. Using logistic regression analyses, we examined the associations between HLA genotypes, comorbidities, allergy risk, and severity. Among the study population, 278 individuals had cephalosporin allergy and 2780 were in the control group. Our results indicated that certain HLA alleles, including HLA-B*55:02 (OR = 1.76, 95% CI 1.18–2.61, p = 0.005), HLA-C*01:02 (OR = 1.36, 95% CI 1.05–1.77, p = 0.018), and HLA-DQB1*06:09 (OR = 2.58, 95% CI 1.62–4.12, p < 0.001), were significantly associated with an increased risk of cephalosporin allergy reactions. Additionally, the HLA-C*01:02 allele genotype was significantly associated with a higher risk of severe allergy (OR = 2.33, 95% CI 1.05–5.15, p = 0.04). This study identified significant associations between HLA alleles and an increased risk of cephalosporin allergy, which can aid in early detection and prediction of adverse drug reactions to cephalosporins. Furthermore, our study highlights the importance of HLA typing in drug safety and expanding our knowledge of drug hypersensitivity syndromes.

HLA topography enforces shared and convergent immunodominant B cell and antibody alloresponses in transplant recipients.

Donor-specific antibody (DSA) responses against human leukocyte antigen (HLA) proteins mismatched between kidney transplant donors and recipients cause allograft loss. The rules governing the immunogenicity of non-self donor HLA are poorly understood. Using single-cell, molecular, structural, and proteomic techniques, we profiled the HLA-specific B cell response in the kidney and blood of a transplant recipient with antibody-mediated rejection (AMR). We observed an immunodominant B cell antibody response focused on topographically exposed, solvent-accessible mismatched HLA residues along the peptide-binding groove - a subregion comprising only 20% of the HLA molecule. We further demonstrated that, even within a diverse cohort of transplant recipients, the B cell alloresponse consistently converges on this same immunodominant subregion on the crown of the HLA molecule. Based on these findings, we propose that B cell immunodominance in transplant rejection relies on antigenic topography, and we suggest that this link could be exploited for organ matching and therapeutics.

A human autoimmune organoid model reveals IL-7 function in coeliac disease.

In vitro models of autoimmunity are constrained by an inability to culture affected epithelium alongside the complex tissue-resident immune microenvironment. Coeliac disease (CeD) is an autoimmune disease in which dietary gluten-derived peptides bind to the major histocompatibility complex (MHC) class II human leukocyte antigen molecules (HLA)-DQ2 or HLA-DQ8 to initiate immune-mediated duodenal mucosal injury1-4. Here, we generated air-liquid interface (ALI) duodenal organoids from intact fragments of endoscopic biopsies that preserve epithelium alongside native mesenchyme and tissue-resident immune cells as a unit without requiring reconstitution. The immune diversity of ALI organoids spanned T cells, B and plasma cells, natural killer (NK) cells and myeloid cells, with extensive T-cell and B-cell receptor repertoires. HLA-DQ2.5-restricted gluten peptides selectively instigated epithelial destruction in HLA-DQ2.5-expressing organoids derived from CeD patients, and this was antagonized by blocking MHC-II or NKG2C/D. Gluten epitopes stimulated a CeD organoid immune network response in lymphoid and myeloid subsets alongside anti-transglutaminase 2 (TG2) autoantibody production. Functional studies in CeD organoids revealed that interleukin-7 (IL-7) is a gluten-inducible pathogenic modulator that regulates CD8+ T-cell NKG2C/D expression and is necessary and sufficient for epithelial destruction. Furthermore, endogenous IL-7 was markedly upregulated in patient biopsies from active CeD compared with remission disease from gluten-free diets, predominantly in lamina propria mesenchyme. By preserving the epithelium alongside diverse immune populations, this human in vitro CeD model recapitulates gluten-dependent pathology, enables mechanistic investigation and establishes a proof of principle for the organoid modelling of autoimmunity.

GIHP: Graph convolutional neural network based interpretable pan-specific HLA-peptide binding affinity prediction.

Accurately predicting the binding affinities between Human Leukocyte Antigen (HLA) molecules and peptides is a crucial step in understanding the adaptive immune response. This knowledge can have important implications for the development of effective vaccines and the design of targeted immunotherapies. Existing sequence-based methods are insufficient to capture the structure information. Besides, the current methods lack model interpretability, which hinder revealing the key binding amino acids between the two molecules. To address these limitations, we proposed an interpretable graph convolutional neural network (GCNN) based prediction method named GIHP. Considering the size differences between HLA and short peptides, GIHP represent HLA structure as amino acid-level graph while represent peptide SMILE string as atom-level graph. For interpretation, we design a novel visual explanation method, gradient weighted activation mapping (Grad-WAM), for identifying key binding residues. GIHP achieved better prediction accuracy than state-of-the-art methods across various datasets. According to current research findings, key HLA-peptide binding residues mutations directly impact immunotherapy efficacy. Therefore, we verified those highlighted key residues to see whether they can significantly distinguish immunotherapy patient groups. We have verified that the identified functional residues can successfully separate patient survival groups across breast, bladder, and pan-cancer datasets. Results demonstrate that GIHP improves the accuracy and interpretation capabilities of HLA-peptide prediction, and the findings of this study can be used to guide personalized cancer immunotherapy treatment. Codes and datasets are publicly accessible at: https://github.com/sdustSu/GIHP.

The Human Neonatal Skin Fibroblast, an Available Cell Source for Tissue Production and Transplantation, Exhibits Low Risk of Immunogenicity In Vitro.

The immunogenicity of allogeneic skin fibroblasts in transplantation has been controversial. Whether this controversy comes from a natural heterogeneity among fibroblast subsets or species-specific differences between human and mouse remains to be addressed. In this study, we sought to investigate whether fibroblasts derived from either adult or neonatal human skin tissues could induce different immune responses toward phagocytosis and T cell activation using in vitro co-culture models. Our results indicate that both phagocytosis and T cell proliferation are reduced in the presence of neonatal skin fibroblasts compared to adult skin fibroblasts. We also show that neonatal skin fibroblasts secrete paracrine factors that are responsible for reduced T cell proliferation. In addition, we show that neonatal skin fibroblasts express less class II human leukocyte antigen (HLA) molecules than adult skin fibroblasts after interferon gamma priming, which might also contribute to reduced T cell proliferation. In conclusion, this study supports the use of allogeneic neonatal skin fibroblasts as a readily available cell source for tissue production and transplantation to treat patients with severe injuries.

Unveiling the Significance of HLA and KIR Diversity in Underrepresented Populations.

Human leukocyte antigen (HLA) molecules and their relationships with natural killer (NK) cells, specifically through their interaction with killer-cell immunoglobulin-like receptors (KIRs), exhibit robust associations with the outcomes of diverse diseases. Moreover, genetic variations in HLA and KIR immune system genes offer limitless depths of complexity. In recent years, a surge of high-powered genome-wide association studies (GWASs) utilizing single nucleotide polymorphism (SNP) arrays has occurred, significantly advancing our understanding of disease pathogenesis. Additionally, advances in HLA reference panels have enabled higher resolution and more reliable imputation, allowing for finer-grained evaluation of the association between sequence variations and disease risk. However, it is essential to note that the majority of these GWASs have focused primarily on populations of Caucasian and Asian origins, neglecting underrepresented populations in Latin America and Africa. This omission not only leads to disparities in health care access but also restricts our knowledge of novel genetic variants involved in disease pathogenesis within these overlooked populations. Since the KIR and HLA haplotypes prevalent in each population are clearly modelled by the specific environment, the aim of this review is to encourage studies investigating HLA/KIR involvement in infection and autoimmune diseases, reproduction, and transplantation in underrepresented populations.

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.

Sensitization 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. Stimulation 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. These 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.