Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing.

BACKGROUND: Identification of human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology and extreme polymorphism of HLA genes. RESULTS: We present Orthanq, a novel statistical model and corresponding application for transparent and uncertainty-aware quantification of haplotypes. We utilize our approach to perform HLA typing while, for the first time, reporting uncertainty of predictions and transparently observing mutations beyond reported HLA types. Using 99 gold standard samples from 1000 Genomes, Illumina Platinum Genomes and Genome In a Bottle projects, we show that Orthanq can provide overall superior accuracy and shorter runtimes than state-of-the-art HLA typers. CONCLUSIONS: Orthanq is the first approach that allows to directly utilize existing pangenome alignments and type all HLA loci. Moreover, it can be generalized for usages beyond HLA typing, e.g. for virus lineage quantification. Orthanq is available under https://orthanq.github.io .

Epistatic interaction between ERAP2 and HLA modulates HIV-1 adaptation and disease outcome in an Australian population.

A strong genetic predictor of outcome following untreated HIV-1 infection is the carriage of specific alleles of human leukocyte antigens (HLAs) that present viral epitopes to T cells. Residual variation in outcome measures may be attributed, in part, to viral adaptation to HLA-restricted T cell responses. Variants of the endoplasmic reticulum aminopeptidases (ERAPs) influence the repertoire of T cell epitopes presented by HLA alleles as they trim pathogen-derived peptide precursors to optimal lengths for antigen presentation, along with other functions unrelated to antigen presentation. We investigated whether ERAP variants influence HLA-associated HIV-1 adaptation with demonstrable effects on overall HIV-1 disease outcome. Utilizing host and viral data of 249 West Australian individuals with HIV-1 subtype B infection, we identified a novel association between two linked ERAP2 single nucleotide polymorphisms (SNPs; rs2248374 and rs2549782) with plasma HIV RNA concentration (viral load) (P adjusted = 0.0024 for both SNPs). Greater HLA-associated HIV-1 adaptation in the HIV-1 Gag gene correlated significantly with higher viral load, lower CD4+ T cell count and proportion; P = 0.0103, P = 0.0061, P = 0.0061, respectively). When considered together, there was a significant interaction between the two ERAP2 SNPs and HLA-associated HIV-1 adaptation on viral load (P = 0.0111). In a comprehensive multivariate model, addition of ERAP2 haplotypes and HLA associated adaptation as an interaction term to known HLA and CCR5 determinants and demographic factors, increased the explanatory variance of population viral load from 17.67% to 45.1% in this dataset. These effects were not replicated in publicly available datasets with comparably sized cohorts, suggesting that any true global epistasis may be dependent on specific HLA-ERAP allelic combinations. Our data raises the possibility that ERAP2 variants may shape peptide repertoires presented to HLA class I-restricted T cells to modulate the degree of viral adaptation within individuals, in turn contributing to disease variability at the population level. Analyses of other populations and experimental studies, ideally with locally derived ERAP genotyping and HLA-specific viral adaptations are needed to elucidate this further.

Breast cancer, viruses, and human leukocyte antigen (HLA).

Several viruses have been implicated in breast cancer, including human herpes virus 4 (HHV4), human herpes virus 5 (HHV5), human papilloma virus (HPV), human JC polyoma virus (JCV), human endogenous retrovirus group K (HERVK), bovine leukemia virus (BLV) and mouse mammary tumor virus (MMTV). Human leukocyte antigen (HLA) is involved in virus elimination and has been shown to influence breast cancer protection/susceptibility. Here we investigated the hypothesis that the contribution of a virus to development of breast cancer would depend on the presence of the virus, which, in turn, would be inversely related to the success of its elimination. For that purpose, we estimated in silico predicted binding affinities (PBA) of proteins of the 7 viruses above to 127 common HLA alleles (69 Class I [HLA-I] and 58 Class II HLA-II]) and investigated the association of these binding affinities to the breast cancer-HLA (BC-HLA) immunogenetic profile of the same alleles. Using hierarchical tree clustering, we found that, for HLA-I, viruses BLV, JCV and MMTV were grouped with the BC-HLA, whereas, for HLA-II, viruses BLV, HERVK, HPV, JCV, and MMTV were grouped with BC-HLA. Finally, for both HLA classes, the average PBAs of the viruses grouped with the BC-HLA profile were significantly lower than those of the other, non BC-HLA associated viruses. Assuming that low PBAs are likely associated with slower viral elimination, these findings support the hypothesis that a defective/slower elimination and, hence, longer persistence and inefficient/delayed production of antibodies against them underlies the observed association of the low-PBA group with breast cancer.

Modelling Role of Protective and Nonprotective HLA Allele Inducing Different HIV Infection Outcomes.

Human immunodeficiency virus (HIV) infects CD4+ cells and causes progressive immune function failure, and CD8+ cells lyse infected CD4+ cell via recognising peptide presented by human leukocyte antigens (HLA). Variations in HLA allele lead to observed different HIV infection outcomes. Within-host HIV dynamics involves virus replication within infected cells and lysing of infected cells by CD8+ cells, but how variations in HLA alleles determine different infection outcomes was far from clear. Here, we used mathematical modelling and parameter inference with a new analysis of published virus inhibition assay data to estimate CD8+ cell lysing efficiency, and found that lysing efficiency fall in the gap between low bound (0.1-0.2 day-1 (Elemans et al. in PLoS Comput Biol 8(2):e1002381, 2012)) and upper boundary (6.5-8.4 day-1 (Wick et al. in J Virol 79(21):13579-13586, 2005)). Our outcomes indicate that both lysing efficiency and viral inoculum size jointly determine observed different infection outcomes. Low lysing rate associated with non-protective HLA alleles leads to monostable viral kinetic to high viral titre and oscillatory viral kinetics. High lysing rate associated with protective HLA alleles leads monostable viral kinetic to low viral titre and bistable viral kinetics; at a specific interval of CD8+ cell counts, small viral inoculum sizes are inhibited but not large viral inoculum sizes remain infectious. Further, with CD8+ cell recruitment, HIV kinetics always exhibit oscillatory kinetics, but lysing rate is negatively correlated with range of CD8+ cell count. Our finding highlights role of HLA allele determining different infection outcomes, thereby providing a potential mechanistic explanation for observed good and bad HIV infection outcomes induced by protective HLA allele.

[Effect of donor and recipient HLA mismatched locus on the prognosis of childhood with leukemia after umbilical cord blood transplantation].

Objective: The aim of the study was to investigate the impact of the sites of high-resolution human leukocyte antigen (HLA) mismatch on the prognosis of children with leukemia undergoing umbilical cord blood transplantation (UCBT). Methods: Clinical data and high-resolution HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 locus gene information were collected in the children who underwent the UCBT for the first time at Children's Hospital of Soochow University between January 2016 and June 2023. In each locus, according to whether the two genes were compatible, they were divided into a compatible group (two genes were perfectly matched) and a non-compatible group (one gene was not matched). In different loci, the differences in occurrence, recurrence, non-recurrence death and survival of acute graft versus host disease (aGVHD) were compared between the two groups. Multivariate Cox regression was employed to analyzed the influencing factors for overall survival rate, and Fine-Gray proportional hazards model was employed to analyze the influencing factors of other outcome events. Results: A total of 100 patients were enrolled (55 males and 45 females), whose age [M (Q1, Q3)] at the time of transplantation was 3.9 (2.0, 6.5) years. There were 55 cases in the HLA-A matched group and 45 cases in the mismatched group. The 5-year non-recurrence mortality (NRM) in the HLA-A matched group was lower than that in the mismatched group (P=0.024). The cumulative incidence of aGVHD within 100 days after transplantation in the HLA-A matched group was lower than that in the mismatched group (P=0.017), and there were no statistically significant differences in other outcome events between the groups (all P>0.05). There were 70 cases in the HLA-B matched group and 30 cases in the mismatched group. The 5-year cumulative recurrence rate in the HLA-B matched group was higher than that in the mismatched group (P=0.027). There were 79 cases in the HLA-C matched group and 21 cases in the mismatched group, and there were no statistically difference in the outcome events between the groups (P>0.05). There were 73 cases in HLA-DRB1 matched group and 27 cases in mismatched group. The 5-year overall survival rate in HLA-DRB1 matched group was higher than that in mismatched group (P=0.036), the 5-year cumulative recurrence rate in HLA-DRB1 matched group was higher than that in mismatched group (P=0.028), and the 5-year NRM in HLA-DRB1 matched group was lower than that in mismatched group (P=0.008). The cumulative incidence of aGVHD within 100 days after transplantation in the matched group was lower than that in the mismatched group (P=0.010), and and there were no statistically significant difference in other outcome events between the groups (P>0.05). There were 68 cases in HLA-DQB1 matched group and 32 cases in mismatched group. There was no statistical difference in outcome events between the two groups (all P>0.05). The risk of aGVHD in HLA-A mismatched group was higher than that in HLA-A matched group (HR=1.25, 95%CI: 1.12-1.38). The risk of recurrence in HLA-B mismatched group was lower than that in HLA-B matched group (HR=0.77, 95%CI: 0.63-0.91). Mismatched group at HLA-DRB1 compared with matched group at HLA-DRB1, had a higher risk of aGVHD (HR=1.37, 95%CI: 1.26-1.48), a higher risk of non-recurrence death (HR=1.39, 95%CI: 1.28-1.50), and a higher risk of death (HR=1.27, 95%CI: 1.18-1.36). No association was found between HLA-C and HLA-DQB1 locus with the risk of aGVHD, recurrence, non-recurrence death, and survival (all P>0.05). Conclusions: In UCBT, the risk of aGVHD in children with matching HLA-A sites of donor and recipient is lower than that in children with incompatible HLA-A sites. Compared with children with incompatible HLA-DRB1 sites, children with HLA-DRB1 matched sites has a lower risk of acute GVHD, a lower 5-year NRM, and a higher risk of death. The recurrence rate of children with matching HLA-B loci is higher than that of children without matching HLA-B loci.

Environmental Determinants of Islet Autoimmunity (ENDIA) longitudinal prospective pregnancy to childhood cohort study of Australian children at risk of type 1 diabetes: parental demographics and birth information.

INTRODUCTION: The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is an ongoing Australian prospective cohort study investigating how modifiable prenatal and early-life exposures drive the development of islet autoimmunity and type 1 diabetes (T1D) in children. In this profile, we describe the cohort's parental demographics, maternal and neonatal outcomes and human leukocyte antigen (HLA) genotypes. RESEARCH DESIGN AND METHODS: Inclusion criteria were an unborn child, or infant aged less than 6 months, with a first-degree relative (FDR) with T1D. The primary outcome was persistent islet autoimmunity, with children followed until a T1D diagnosis or 10 years of age. Demographic data were collected at enrollment. Lifestyle, clinical and anthropometric data were collected at each visit during pregnancy and clinical pregnancy and birth data were verified against medical case notes. Data were compared between mothers with and without T1D. HLA genotyping was performed on the ENDIA child and all available FDRs. RESULTS: The final cohort comprised 1473 infants born to 1214 gestational mothers across 1453 pregnancies, with 80% enrolled during pregnancy. The distribution of familial T1D probands was 62% maternal, 28% paternal and 11% sibling. The frequency of high-risk HLA genotypes was highest in T1D probands, followed by ENDIA infants, and lowest among unaffected family members. Mothers with T1D had higher rates of pregnancy complications and perinatal intervention, and larger babies of shorter gestation. Parent demographics were comparable to the Australian population for age, parity and obesity. A greater percentage of ENDIA parents were Australian born, lived in a major city and had higher socioeconomic advantage and education. CONCLUSIONS: This comprehensive profile provides the context for understanding ENDIA's scope, methodology, unique strengths and limitations. Now fully recruited, ENDIA will provide unique insights into the roles of early-life factors in the development of islet autoimmunity and T1D in the Australian environment. TRIAL REGISTRATION NUMBER: ACTRN12613000794707.

Vaccinomics: Paving the Way for Personalized Immunization.

Vaccines are one of the most important medical advancements in human history. They have been successfully used to control and limit the spread of many of the lethal diseases that have plagued us, such as smallpox and polio. Previous vaccine design methodologies were based on the model of "isolate-inactivateinject", which amounts to giving the same vaccine dose to everyone susceptible to infection. In recent years, the importance of how the host genetic background alters vaccine response necessitated the introduction of vaccinomics, which is aimed at studying the variability of vaccine efficacy by associating genetic variability and immune response to vaccination. Despite the rapid developments in variant screening, data obtained from association studies is often inconclusive and cannot be used to guide the new generation of vaccines. This review aims to compile the polymorphisms in HLA and immune system genes and examine the link with their immune response to vaccination. The compiled data can be used to guide the development of new strategies for vaccination for vulnerable groups. Overall, the highly polymorphic HLA locus had the highest correlation with vaccine response variability for most of the studied vaccines, and it was linked to variation in multiple stages of the immune response to the vaccines for both humoral and cellular immunity. Designing new vaccine technologies and immunization regiments to accommodate for this variability is an important step for reaching a vaccinomics-based approach to vaccination.

Elucidating the Mechanisms Underlying Interindividual Differences in the Onset of Adverse Drug Reactions.

Idiosyncratic drug toxicities (IDTs) pose a significant challenge; they are marked by life-threatening adverse reactions that emerge aftermarket release and are influenced by intricate genetic and environmental variations. Recent genome-wide association studies have highlighted a strong correlation between specific human leukocyte antigen (HLA) polymorphisms and IDT onset. This review provides an overview of current research on HLA-mediated drug toxicities. In the last six years, HLA-transgenic (Tg) mice have been instrumental in advancing our understanding of these underlying mechanisms, uncovering systemic immune reactions that replicate human drug-induced immune stimulation. Additionally, the potential role of immune tolerance in shaping individual differences in adverse effects highlights its relevance to the interplay between HLA polymorphisms and IDTs. Although HLA-Tg mice offer valuable insights into systemic immune reactions, further exploration is essential to decipher the intricate interactions that lead to organ-specific adverse effects, especially in organs such as the skin or liver. Navigating the intricate interplay of HLA, which may potentially trigger intracellular immune responses, this review emphasizes the need for a holistic approach that integrates findings from both animal models and molecular/cellular investigations. The overarching goal is to enhance our comprehensive understanding of HLA-mediated IDTs and identify factors shaping individual variations in drug reactions. This review aims to facilitate the development of strategies to prevent severe adverse effects, address existing knowledge gaps, and provide guidance for future research initiatives in the field of HLA-mediated IDTs.

Homozygosity in any HLA locus is a risk factor for specific antibody production: the taboo concept 2.0.

Objective: In a cooperative study of the University Hospital Leipzig, University of Leipzig, and the Charité Berlin on kidney transplant patients, we analysed the occurrence of HLA-specific antibodies with respect to the HLA setup of the patients. We aimed at the definition of specific HLA antigens towards which the patients produced these antibodies. Methods: Patients were typed for the relevant HLA determinants using mainly the next-generation technology. Antibody screening was performed by the state-of-the-art multiplex-based technology using microspheres coupled with the respective HLA alleles of HLA class I and II determinants. Results: Patients homozygous for HLA-A*02, HLA-A*03, HLA-A*24, HLA-B*07, HLA-B*18, HLA-B*35, HLA-B*44, HLA-C*03, HLA-C*04, and HLA-C*07 in the class I group and HLA-DRB1*01, HLA-DRB1*03, HLA-DRB1*07, HLA-DRB1*15, HLA-DQA1*01, HLA-DQA1*05, HLA-DQB1*02, HLA-DQB1*03(7), HLA-DQB1*06, HLA-DPA1*01, and HLA-DPB1*04 in the class II group were found to have a significant higher antibody production compared to the heterozygous ones. In general, all HLA determinants are affected. Remarkably, HLA-A*24 homozygous patients can produce antibodies towards all HLA-A determinants, while HLA-B*18 homozygous ones make antibodies towards all HLA-B and selected HLA-A and C antigens, and are associated with an elevation of HLA-DRB1, parts of DQB1 and DPB1 alleles. Homozygosity for the HLA class II HLA-DRB1*01, and HLA-DRB1*15 seems to increase the risk for antibody responses against most of the HLA class I antigens (HLA-A, HLA-B, and HLA-C) in contrast to HLA-DQB1*03(7) where a lower risk towards few HLA-A and HLA-B alleles is found. The widely observed differential antibody response is therefore to be accounted to the patient's HLA type. Conclusion: Homozygous patients are at risk of producing HLA-specific antibodies hampering the outcome of transplantation. Including this information on the allocation procedure might reduce antibody-mediated immune reactivity and prevent graft loss in a patient at risk, increasing the life span of the transplanted organ.

Conservation of HLA Spike Protein Epitopes Supports T Cell Cross-Protection in SARS-CoV-2 Vaccinated Individuals against the Potentially Zoonotic Coronavirus Khosta-2.

Heterologous vaccines, which induce immunity against several related pathogens, can be a very useful and rapid way to deal with new pandemics. In this study, the potential impact of licensed COVID-19 vaccines on cytotoxic and helper cell immune responses against Khosta-2, a novel sarbecovirus that productively infects human cells, was analyzed for the 567 and 41 most common HLA class I and II alleles, respectively. Computational predictions indicated that most of these 608 alleles, covering more than 90% of the human population, contain sufficient fully conserved T-cell epitopes between the Khosta-2 and SARS-CoV-2 spike-in proteins. Ninety percent of these fully conserved peptides for class I and 93% for class II HLA molecules were verified as epitopes recognized by CD8+ or CD4+ T lymphocytes, respectively. These results show a very high correlation between bioinformatic prediction and experimental assays, which strongly validates this study. This immunoinformatics analysis allowed a broader assessment of the alleles that recognize these peptides, a global approach at the population level that is not possible with experimental assays. In summary, these findings suggest that both cytotoxic and helper cell immune protection elicited by currently licensed COVID-19 vaccines should be effective against Khosta-2 virus infection. Finally, by being rapidly adaptable to future coronavirus pandemics, this study has potential public health implications.

A multi-ethnic reference panel to impute HLA classical and non-classical class I alleles in admixed samples: Testing imputation accuracy in an admixed sample from Brazil.

The MHC class I region contains crucial genes for the innate and adaptive immune response, playing a key role in susceptibility to many autoimmune and infectious diseases. Genome-wide association studies have identified numerous disease-associated SNPs within this region. However, these associations do not fully capture the immune-biological relevance of specific HLA alleles. HLA imputation techniques may leverage available SNP arrays by predicting allele genotypes based on the linkage disequilibrium between SNPs and specific HLA alleles. Successful imputation requires diverse and large reference panels, especially for admixed populations. This study employed a bioinformatics approach to call SNPs and HLA alleles in multi-ethnic samples from the 1000 genomes (1KG) dataset and admixed individuals from Brazil (SABE), utilising 30X whole-genome sequencing data. Using HIBAG, we created three reference panels: 1KG (n = 2504), SABE (n = 1171), and the full model (n = 3675) encompassing all samples. In extensive cross-validation of these reference panels, the multi-ethnic 1KG reference exhibited overall superior performance than the reference with only Brazilian samples. However, the best results were achieved with the full model. Additionally, we expanded the scope of imputation by developing reference panels for non-classical, MICA, MICB and HLA-H genes, previously unavailable for multi-ethnic populations. Validation in an independent Brazilian dataset showcased the superiority of our reference panels over the Michigan Imputation Server, particularly in predicting HLA-B alleles among Brazilians. Our investigations underscored the need to enhance or adapt reference panels to encompass the target population's genetic diversity, emphasising the significance of multiethnic references for accurate imputation across different populations.

Prognostic Role of Human Leukocyte Antigen Alleles and Cytokine Single-Nucleotide Polymorphisms in Patients with Chronic Myeloid Leukemia Treated with Tyrosine Kinase Inhibitor Drugs.

Tyrosine kinase inhibitor (TKI) drugs have significantly improved chronic myeloid leukemia (CML) outcomes. Neopeptides from CML cells may induce specific immune responses, which are crucial for deep molecular (DMR) and treatment-free remission (TFR). In this study of Ethiopian patients with CML (n = 162), the HLA alleles and single-nucleotide polymorphisms of five cytokines revealed significant associations with clinical outcomes. Clinically unfavorable outcomes correlated with HLA alleles A*03:01/02, A*23:17:01, B*57:01/02/03, and HLA-DRB4*01:01 (p-value = 0.0347, p-value = 0.0285, p-value = 0.037, and p-value = 0.0127, respectively), while HLA-DRB4*01:03:01 was associated with favorable outcomes (p-value = 0.0058). After assigning values for the 'low', 'intermediate', and 'high' gene expression of the SNPs' respective cytokine genes, Kaplan-Meier estimates for relapse-free survival, adjusted for age, treatment duration, and relapse risk among patients after the administration of TKIs, indicated that a gene expression ratio above the overall median of TNF-α, IL-6, and the combination of TGF-ß1/IL-10, IFNγ, and IL-6/IL-10 TGF-ß1 was correlated with a higher likelihood of treatment failure ((RR: 3.01; 95% CI: 1.1-8.3; p-value = 0.0261) and (RR: 2.4; 95% CI: 1.1-5.2; p-value = 0.022), respectively). Multi-SNPs, surpassing single-SNPs, and HLA allele polymorphisms showed promise in predicting outcomes of patients with CML during TKI treatment, prompting further exploration into their potential utility.

HLA investigation in ICI-induced T1D and isolated ACTH deficiency including meta-analysis.

OBJECTIVE: Widespread use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in the number of reported cases of immunotherapy-related endocrinopathies. This study aimed to analyze and compare human leukocyte antigen (HLA) signatures associated with ICI-induced type 1 diabetes (ICI-T1D) and isolated adrenocorticotropic hormone deficiency (ICI-IAD) in patients with both conditions. METHODS: HLA signatures were examined for their frequencies of occurrence in 22 patients with ICI-T1D without concurrent IAD, including 16 patients from nationwide reports (ICI-T1D group) and 14 patients with ICI-IAD without concurrent T1D (ICI-IAD group). The HLA signatures were also compared for their respective frequencies in 11 patients with ICI-T1D and ICI-IAD, including eight from nationwide reports (ICI-T1D/IAD group). RESULTS: In the ICI-T1D group, HLA-DRB1*09:01-DQB1*03:03 and DQA1*03:02, which are in linkage disequilibrium with DRB1*09:01-DQB1*03:03 and DRB1*13:02-DQB1*06:04, were susceptible to ICI-T1D, whereas DRB1*15:02-DQB1*06:01 was protective against ICI-T1D. In the ICI-IAD group, DPB1*09:01, C*12:02-B*52:01, and DRB1*15:02-DRB1*06:01, which are in strong linkage disequilibrium, were associated with susceptibility to ICI-IAD. Moreover, DRB1*15:02-DRB1*06:01 was not detected in the ICI-T1D/IAD group. CONCLUSIONS: This study revealed specific HLA signatures associated with ICI-T1D and ICI-IAD. Moreover, HLA-DRB1*15:02-DRB1*06:01, an ICI-IAD-susceptible HLA haplotype, coincides with the ICI-T1D-protective HLA haplotype, suggesting that the presence of DRB1*15:02-DRB1*06:01 may protect against the co-occurrence of T1D in patients with ICI-IAD.

HLA alleles, haplotypes frequencies, and their association with hematological disorders: a report from 1550 families whose patients underwent allogeneic bone marrow transplantation in Egypt.

HLA alleles are representative of ethnicities and may play important roles in predisposition to hematological disorders. We analyzed DNA samples for HLA-A, -B, -C, -DRB1, and -DQB1 loci, from 1550 patients and 4450 potential related donors by PCR-SSO (Polymerase chain reaction sequence-specific oligonucleotides) and estimated allele frequencies in donors and patients from 1550 families who underwent bone marrow transplantation (BMT) in Egypt. We also studied the association between HLA allele frequencies and incidence of acute myeloid leukemia, acute lymphoblastic leukemia, and severe aplastic anemia. The most frequently observed HLA class I alleles were HLA- A*01:01 (16.9%), A*02:01 (16.1%), B*41:01 (8.7%), B*49:01 (7.3%), C*06:02 (25.1%), and C*07:01 (25.1%), and the most frequently observed class II alleles were HLA-DRB1*11:01 (11.8%), DRB1*03:01 (11.6%), DQB1*03:01 (27.5%), and DQB1*05:01 (18.9%). The most frequently observed haplotypes were A*33:01~B*14:02 ~ DRB1*01:02 (2.35%) and A*01:01~B*52:01~DRB1*15:01 (2.11%). HLA-DRB1*07:01 was associated with higher AML odds (OR, 1.26; 95% CI, 1.02-1.55; p = 0.030). Only HLA-B38 antigen showed a trend towards increased odds of ALL (OR, 1.52; 95% CI, 1.00-2.30; p = 0.049) HLA-A*02:01, -B*14:02, and -DRB1*15:01 were associated with higher odds of SAA (A*02:01: OR, 1.35; 95% CI, 1.07-1.70; p = 0.010; B*14:02: OR, 1.43; 95% CI, 1.06-1.93; p = 0.020; DRB1*15:01: OR, 1.32; 95% CI, 1.07-1.64; p = 0.011). This study provides estimates of HLA allele and haplotype frequencies and their association with hematological disorders in an Egyptian population.

The impact of MICB mismatches in unrelated haematopoietic stem cell transplantation.

MICA polymorphisms have been associated with increased incidence of acute GvHD and adverse outcome in allogeneic haematopoietic stem cell transplantation (HSCT). MICB is another expressed member of MHC class I-related chain genes and its impact on HSCT outcome is yet to be fully defined. We typed a large cohort of patients and donors for MICB polymorphisms and investigated the impact of MICB matching on outcome after unrelated HSCT. 69.2% of the patients were 10/10 human leukocyte antigen (HLA) matched and 30.8% were 9/10 HLA matched. MICB typing was performed using a short amplicon-based NGS typing assay on the Illumina MiSeq platform. Differences in proteins were considered as mismatches. MICA polymorphisms were identified as possible confounder and were therefore included as parameter in the multivariate analyses. Due to the strong linkage disequilibrium with the classical HLA-genes, sub-stratification for HLA matching status was necessary, and no effect of MICB mismatches was seen in the 10/10 HLA matched group when compared to the MICB matched cases. However, in the 9/10 HLA matched group, MICB mismatched cases showed significantly worse disease free survival (DFS), GvHD and relapse free survival (GRFS) compared to the MICB matched cases (DFS: HR 1.24, p = 0.011; GRFS: HR 1.26, p = 0.002). MICA mismatches had no impact on any outcome parameter. According to our findings, effects previously attributed to MICA differences may have been confounded by MICB polymorphisms. We show that MICB differences contribute a small but relevant effect in 9/10 HLA-matched transplantations, which in turn highlights the possible usefulness of MICB typing in donor selection among similarly suitable 9/10 matched donors, especially when HLA-B mismatches have to be accepted.

AmpliSAS and AmpliHLA: Web Server and Local Tools for MHC Typing of Non-model Species and Human Using NGS Data.

AmpliSAS and AmpliHLA are tools for automatic genotyping of MHC genes from high-throughput sequencing data. AmpliSAS is designed specifically to analyze amplicon sequencing data from non-model species and it is able to perform de novo genotyping without any previous knowledge of the reference alleles. AmpliHLA is a human specific version; it performs HLA typing by comparing sequenced variants against human reference alleles from the IMGT/HLA database. Both tools are available in AmpliSAT web-server as well as scripts for local/server installation. Here we describe the installation and deployment of AmpliSAS and AmpliHLA Perl scripts and dependencies on a local or a server computer. We will show how to run them in the command line using as examples four genotyping protocols: the first two use amplicon sequencing data to genotype the MHC genes of a passerine bird and human respectively; the third and fourth present the HLA typing of a human cell line starting from RNA and exome sequencing data respectively.

Submitting Novel Full-Length HLA, MIC, and KIR Alleles with TypeLoader2.

The Immuno Polymorphism Database (IPD) plays a pivotal role for immunogenetics. Due to technical limitations, genotyping often focuses on specific key regions like the antigen recognition domain (ARD) for HLA genotyping, and the databases are populated accordingly. More recently, though, modern next generation sequencing (NGS) assays allow using larger gene segments or even complete genes for genotyping. It is therefore essential that the databases are updated with complete genetic reference sequences to fully serve current and future applications. However, the process of manually annotating and submitting full-length allele sequences to IPD is time-consuming and error-prone, which may discourage HLA-genotyping laboratories or researchers from submitting full-length sequences of novel alleles.Here, we detail the process of preparing and submitting novel HLA, MIC, and KIR alleles to ENA and IPD using TypeLoader2, a convenient software tool developed to streamline this process by automating the sequence annotation, the creation of all necessary files, as well as parts of the submission process itself. The software is freely available from GitHub ( https://github.com/DKMS-LSL/typeloader ).

NanoHLA: A Method for Human Leukocyte Antigen Class I Genes Typing Without Error Correction Based on Nanopore Sequencing Data.

Human leukocyte antigen (HLA) typing is of great importance in clinical applications such as organ transplantation, blood transfusion, disease diagnosis and treatment, and forensic analysis. In recent years, nanopore sequencing technology has emerged as a rapid and cost-effective option for HLA typing. However, due to the principles and data characteristics of nanopore sequencing, there was a scarcity of robust and generalizable bioinformatics tools for its downstream analysis, posing a significant challenge in deciphering the thousands of HLA alleles present in the human population. To address this challenge, we developed NanoHLA as a tool for high-resolution typing of HLA class I genes without error correction based on nanopore sequencing. The method integrated the concepts of HLA type coverage analysis and the data conversion techniques employed in Nano2NGS, which was characterized by applying nanopore sequencing data to NGS-liked data analysis pipelines. In validation with public nanopore sequencing datasets, NanoHLA showed an overall concordance rate of 84.34% for HLA-A, HLA-B, and HLA-C, and demonstrated superior performance in comparison to existing tools such as HLA-LA. NanoHLA provides tools and solutions for use in HLA typing related fields, and look forward to further expanding the application of nanopore sequencing technology in both research and clinical settings. The code is available at https://github.com/langjidong/NanoHLA .