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Background: Although there are many possible causes for cervical dystonia (CD), a specific etiology cannot be identified in most cases. Prior studies have suggested a relationship between autoimmune disease and some cases of CD, pointing to possible immunological mechanisms., Objective: The goal was to explore the potential role of multiple different immunological mechanisms in CD., Methods: First, a broad screening test compared neuronal antibodies in controls and CD. Second, unbiased blood plasma proteomics provided a broad screen for potential biologic differences between controls and CD. Third, a multiplex immunoassay compared 37 markers associated with immunological processes in controls and CD. Fourth, relative immune cell frequencies were investigated in blood samples of controls and CD. Finally, sequencing studies investigated the association of HLA DQB1 and DRB1 alleles in controls versus CD., Results: Screens for anti-neuronal antibodies did not reveal any obvious abnormalities. Plasma proteomics pointed towards certain abnormalities of immune mechanisms, and the multiplex assay pointed more specifically towards abnormalities in T lymphocytes. Abnormal immune cell frequencies were identified for some CD cases, and these cases clustered together as a potential subgroup. Studies of HLA alleles indicated a possible association between CD and DRB1*15:03, which is reported to mediate the penetrance of autoimmune disorders., Conclusions: Altogether, the association of CD with multiple different blood-based immune measures point to abnormalities in cell-mediated immunity that may play a pathogenic role for a subgroup of individuals with CD., Competing Interests: Declaration of competing interest NO COI., (Copyright © 2024. Published by Elsevier Ltd.)

How human genetic variation contributes to vaccine effectiveness in infants is unclear, and data are limited on these relationships in populations with African ancestries. We undertook genetic analyses of vaccine antibody responses in infants from Uganda (n = 1391), Burkina Faso (n = 353) and South Africa (n = 755), identifying associations between human leukocyte antigen (HLA) and antibody response for five of eight tested antigens spanning pertussis, diphtheria and hepatitis B vaccines. In addition, through HLA typing 1,702 individuals from 11 populations of African ancestry derived predominantly from the 1000 Genomes Project, we constructed an imputation resource, fine-mapping class II HLA-DR and DQ associations explaining up to 10% of antibody response variance in our infant cohorts. We observed differences in the genetic architecture of pertussis antibody response between the cohorts with African ancestries and an independent cohort with European ancestry, but found no in silico evidence of differences in HLA peptide binding affinity or breadth. Using immune cell expression quantitative trait loci datasets derived from African-ancestry samples from the 1000 Genomes Project, we found evidence of differential HLA-DRB1 expression correlating with inferred protection from pertussis following vaccination. This work suggests that HLA-DRB1 expression may play a role in vaccine response and should be considered alongside peptide selection to improve vaccine design., (© 2024. The Author(s).)

The HLA-B*53:69 allele differs from HLA-B*53:01:01:01 by two nucleotide changes in exon 3., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Between January 2018 and June 2021, the Ezer Mizion recruited 223,960 donors. All donors were typed for their HLA class I and II alleles at high resolution by Next Generation Sequencing techniques. Comparison between the sequences obtained from these donors and those in the IPD-IMGT/HLA Database, revealed 122 Novel HLA alleles that were found in 133 donors. Most of the alleles, 94 (77%) were identified in the HLA class I genes (30, 35, and 29 in HLA-A, -B, and -C, respectively), and 28 (23%) were detected in the HLA class II genes (9 in HLA-DRB1 and -DQB1 and 10 in -DPB1). Most of these novel alleles, 106 (86.9%) comprised single nucleotide variation (SNV), 9 (7.4%) present multiple amino acids variation, 4 and 3 were generated because of deletions and insertions, respectively. Ten of these novel alleles were seen to be null alleles., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

A nucleotide mutation in codon 75 of HLA-C*04:01:01:01 results in a novel allele HLA-C*04:279N., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The identity of histocompatibility loci, besides human leukocyte antigen (HLA), remains elusive. The major histocompatibility complex (MHC) class I MICA gene is a candidate histocompatibility locus. Here, we investigate its role in a French multicenter cohort of 1,356 kidney transplants. MICA mismatches were associated with decreased graft survival (hazard ratio (HR), 2.12; 95% confidence interval (CI): 1.45-3.11; P < 0.001). Both before and after transplantation anti-MICA donor-specific antibodies (DSA) were strongly associated with increased antibody-mediated rejection (ABMR) (HR, 3.79; 95% CI: 1.94-7.39; P < 0.001; HR, 9.92; 95% CI: 7.43-13.20; P < 0.001, respectively). This effect was synergetic with that of anti-HLA DSA before and after transplantation (HR, 25.68; 95% CI: 3.31-199.41; P = 0.002; HR, 82.67; 95% CI: 33.67-202.97; P < 0.001, respectively). De novo-developed anti-MICA DSA were the most harmful because they were also associated with reduced graft survival (HR, 1.29; 95% CI: 1.05-1.58; P = 0.014). Finally, the damaging effect of anti-MICA DSA on graft survival was confirmed in an independent cohort of 168 patients with ABMR (HR, 1.71; 95% CI: 1.02-2.86; P = 0.041). In conclusion, assessment of MICA matching and immunization for the identification of patients at high risk for transplant rejection and loss is warranted., (© 2022. The Author(s).)

One nucleotide substitution in Codon 58 of HLA-C*06:02:01:01 results in a novel allele, HLA-C*06:195., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-A*68:227 differs from HLA-A*68:84 by two single nucleotide substitutions in codon 10 and 90., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DPB1*10:01:05 differs from HLA-DPB1*10:01:01:01 by a single synonymous nucleotide substitution in exon 2, 38 G>A., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 73 of HLA-A*01:01:01:01 results in a novel allele, HLA-A*01:211., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 112 of HLA-B*15:349:01 results in a novel allele, HLA-B*15:349:02., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 87 of HLA-DQB1*05:02:01:01 results in a novel allele, HLA-DQB1*05:116., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 38 of HLA-DQB1*06:01:01:01 results in a novel allele, HLA-DQB1*06:132., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 85 of HLA-DPB1*04:01:01:01 results in a novel allele, HLA-DPB1*454:01., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Nucleotide substitutions in codon 38 of HLA-DQB1*05:03:01:01 result in a novel allele, HLA-DQB1*05:66:01., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 89 of HLA-B*38:02:01:01 results in a novel allele, HLA-B*38:64., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide substitution in codon 84 of HLA-DPB1*02:01:02:01 results in a novel allele, HLA-DPB1*526:01., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

DNA substitutions from codons 69 to 71 of HLA-B*35:05:01:01 result in a novel allele, HLA-B*35:368., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Novel allele HLA-DPB1*906:01 is possibly a recombinant between DPB1*04:02:01:01 and DPB1*06:01:01:01., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

A catalog of common, intermediate and well-documented (CIWD) HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQB1 and -DPB1 alleles has been compiled from over 8 million individuals using data from 20 unrelated hematopoietic stem cell volunteer donor registries. Individuals are divided into seven geographic/ancestral/ethnic groups and data are summarized for each group and for the total population. P (two-field) and G group assignments are divided into one of four frequency categories: common (≥1 in 10 000), intermediate (≥1 in 100 000), well-documented (≥5 occurrences) or not-CIWD. Overall 26% of alleles in IPD-IMGT/HLA version 3.31.0 at P group resolution fall into the three CIWD categories. The two-field catalog includes 18% (n = 545) common, 17% (n = 513) intermediate, and 65% (n = 1997) well-documented alleles. Full-field allele frequency data are provided but are limited in value by the variations in resolution used by the registries. A recommended CIWD list is based on the most frequent category in the total or any of the seven geographic/ancestral/ethnic groups. Data are also provided so users can compile a catalog specific to the population groups that they serve. Comparisons are made to three previous CWD reports representing more limited population groups. This catalog, CIWD version 3.0.0, is a step closer to the collection of global HLA frequencies and to a clearer view of HLA diversity in the human population as a whole., (© 2020 The Authors. HLA published by John Wiley & Sons Ltd.)

Between 2008 and April 2018, we recruited more than 37 000 potential Arab donors to the Hadassah Bone Marrow Donor Registry, all of whom were typed for high resolution HLA-A, -B, and -DRB1. In addition, more than 22% of them were also typed for their HLA-C and -DQB1 alleles. A comparison of the sequences obtained from these donors with the IPD-IMGT/HLA Database showed 33 novel alleles from five loci (HLA-A, -B, -C, -DR, -DQ). All of these novel HLA alleles were detected in the local Arab communities; 79% of these alleles have not been described in other groups yet and remain unique to the local Arab communities., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Summary: HLA*LA implements a new graph alignment model for human leukocyte antigen (HLA) type inference, based on the projection of linear alignments onto a variation graph. It enables accurate HLA type inference from whole-genome (99% accuracy) and whole-exome (93% accuracy) Illumina data; from long-read Oxford Nanopore and Pacific Biosciences data (98% accuracy for whole-genome and targeted data) and from genome assemblies. Computational requirements for a typical sample vary between 0.7 and 14 CPU hours per sample., Availability and Implementation: HLA*LA is implemented in C++ and Perl and freely available as a bioconda package or from https://github.com/DiltheyLab/HLA-LA (GPL v3)., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

One nucleotide substitution in codon 46 of HLA-DQB1*05:01:01:01 results in a new allele, HLA-DQB1*05:115., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

HLA-DPB1*417:01:02 differs from HLA-DPB1*417:01:01 by a synonymous nucleotide substitution at codon 43., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

One nucleotide replacement in codon 50 of HLA-C*07:02:01:01 results in a novel allele, HLA-C*07:465., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Nucleotide substitutions at residues 105 and 106 of HLA-B*58:01:01:01 result in a novel allele, HLA-B*58:74., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Allogeneic hematopoietic cell transplantation (alloHCT) remains the sole curative therapy for patients with chronic lymphocytic leukemia (CLL), leading to 40% to 45% long-term survival. The impact of donor killer immunoglobulin-like receptor (KIR) genotype on outcomes of unrelated donor (URD) alloHCT for CLL is unknown. We examined 573 adult URD CLL recipient pairs. KIR genotype (presence/absence) was determined for each donor, and comprehensive modeling of interactions with recipient HLA class I loci (KIR ligands) was used to evaluate their effect on relapse and survival. Recipients had a median age of 56 years, and most were not in remission (65%). Both 8/8 HLA-matched (81%) or 7/8 HLA matched grafts (19%) were studied. Factors associated with improved overall survival (OS) were reduced-intensity conditioning (hazard ratio [HR] of death, .76) and good performance status (HR, .46), whereas alloHCT in nonremission (HR, 1.96) and mismatched donors (HR, 2.01) increased mortality. No models demonstrated a relationship between donor KIR genotype and transplant outcomes. Cox regression models comparing donors with A/A versus B/x KIR haplotypes and those with KIR gene content scores of 0 versus 1 versus ≥2 yielded similar rates of nonrelapse mortality, relapse, acute graft-versus-host disease (GVHD), and chronic GVHD and the same progression-free survival and OS. Relapse risk was not different for grafts from donors with KIR3DL1 transplanted into HLA C1/1 versus C2 recipients. This large analysis failed to demonstrate an association between URD KIR genotype and transplant outcome for patients with CLL, and thus KIR genotyping should not be used as a donor selection criterion in this setting., (Copyright © 2019 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.)

HLA-DPB1*835:01 differs from HLA-DPB1*23:01:01:01 and 72:01:01:01 by four non-synonymous nucleotide substitutions within exon 2., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The ABO and rhesus (Rh) blood group antigens are the most frequently studied genetic markers in a large group of people. Blood type frequencies vary in different racial/ethnic groups. Our objective was to investigate the distribution of the ABO and rhesus (Rh) blood groups by molecular typing method in a population of Saudi stem cell donors. Our data indicate that the most common blood group in our population is group O followed by group A then group B, and finally, the least common is group AB., (© 2018 John Wiley & Sons Ltd.)

HLA class I glycoproteins contain the functional sites that bind peptide antigens and engage lymphocyte receptors. Recently, clinical application of sequence-based HLA typing has uncovered an unprecedented number of novel HLA class I alleles. Here we define the nature and extent of the variation in 3,489 HLA-A, 4,356 HLA-B and 3,111 HLA-C alleles. This analysis required development of suites of methods, having general applicability, for comparing and analyzing large numbers of homologous sequences. At least three amino-acid substitutions are present at every position in the polymorphic α1 and α2 domains of HLA-A, -B and -C. A minority of positions have an incidence >1% for the 'second' most frequent nucleotide, comprising 70 positions in HLA-A, 85 in HLA-B and 54 in HLA-C. The majority of these positions have three or four alternative nucleotides. These positions were subject to positive selection and correspond to binding sites for peptides and receptors. Most alleles of HLA class I (>80%) are very rare, often identified in one person or family, and they differ by point mutation from older, more common alleles. These alleles with single nucleotide polymorphisms reflect the germ-line mutation rate. Their frequency predicts the human population harbors 8-9 million HLA class I variants. The common alleles of human populations comprise 42 core alleles, which represent all selected polymorphism, and recombinants that have assorted this polymorphism.

Genetic variation at the Human Leucocyte Antigen (HLA) genes is associated with many autoimmune and infectious disease phenotypes, is an important element of the immunological distinction between self and non-self, and shapes immune epitope repertoires. Determining the allelic state of the HLA genes (HLA typing) as a by-product of standard whole-genome sequencing data would therefore be highly desirable and enable the immunogenetic characterization of samples in currently ongoing population sequencing projects. Extensive hyperpolymorphism and sequence similarity between the HLA genes, however, pose problems for accurate read mapping and make HLA type inference from whole-genome sequencing data a challenging problem. We describe how to address these challenges in a Population Reference Graph (PRG) framework. First, we construct a PRG for 46 (mostly HLA) genes and pseudogenes, their genomic context and their characterized sequence variants, integrating a database of over 10,000 known allele sequences. Second, we present a sequence-to-PRG paired-end read mapping algorithm that enables accurate read mapping for the HLA genes. Third, we infer the most likely pair of underlying alleles at G group resolution from the IMGT/HLA database at each locus, employing a simple likelihood framework. We show that HLA*PRG, our algorithm, outperforms existing methods by a wide margin. We evaluate HLA*PRG on six classical class I and class II HLA genes (HLA-A, -B, -C, -DQA1, -DQB1, -DRB1) and on a set of 14 samples (3 samples with 2 x 100bp, 11 samples with 2 x 250bp Illumina HiSeq data). Of 158 alleles tested, we correctly infer 157 alleles (99.4%). We also identify and re-type two erroneous alleles in the original validation data. We conclude that HLA*PRG for the first time achieves accuracies comparable to gold-standard reference methods from standard whole-genome sequencing data, though high computational demands (currently ~30-250 CPU hours per sample) remain a significant challenge to practical application., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: ATD and GM are partners in Peptide Groove, LLP. GM is a founder and shareholder of Genomics, Ltd. NC has ownership and management interest in Histogenetics.

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and Sequence Based Typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

This communication describes our experience in large-scale G group-level high resolution HLA typing using three different DNA sequencing platforms - ABI 3730 xl, Illumina MiSeq and PacBio RS II. Recent advances in DNA sequencing technologies, so-called next generation sequencing (NGS), have brought breakthroughs in deciphering the genetic information in all living species at a large scale and at an affordable level. The NGS DNA indexing system allows sequencing multiple genes for large number of individuals in a single run. Our laboratory has adopted and used these technologies for HLA molecular testing services. We found that each sequencing technology has its own strengths and weaknesses, and their sequencing performances complement each other. HLA genes are highly complex and genotyping them is quite challenging. Using these three sequencing platforms, we were able to meet all requirements for G group-level high resolution and high volume HLA typing., (Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.)

Three new HLA-C alleles were identified by sequence-based typing method (SBT) in donors for the Saudi Bone Marrow Donor Registry (SBMDR). HLA-C*14:02:13 differs from HLA-C*14:02:01 by a silent G to A substitution at nucleotide position 400 in exon 2, where lysine at position 66 remains unchanged. HLA-C*15:72 differs from HLA-C*15:22 by a nonsynonymous C to A substitution at nucleotide position 796 in exon 3, resulting in an amino acid change from phenylalanine to leucine at position 116. HLA-C*15:74 differs from HLA-C*15:08 by a nonsynonymous C to T substitution at nucleotide position 914 in exon 3, resulting in an amino acid change from arginine to tryptophan at position 156., (© 2015 John Wiley & Sons Ltd.)