Genome-Wide Association Study Identifies IFIH1 and HLA-DQB1*05:02 Loci Associated With Anti-NMDAR Encephalitis.

BACKGROUND AND OBJECTIVES: Anti-N-methyl-d-aspartate receptor (NMDAR) encephalitis is a rare autoimmune neurologic disorder, the genetic etiology of which remains poorly understood. Our study aims to investigate the genetic basis of this disease in the Chinese Han population. METHODS: We performed a genome-wide association study and fine-mapping study within the major histocompatibility complex (MHC) region of 413 Chinese patients with anti-NMDAR encephalitis recruited from 6 large tertiary hospitals and 7,127 healthy controls. RESULTS: Our genome-wide association analysis identified a strong association at the IFIH1 locus on chromosome 2q24.2 (rs3747517, p = 1.06 × 10-8, OR = 1.55, 95% CI, 1.34-1.80), outside of the human leukocyte antigen (HLA) region. Furthermore, through a fine-mapping study of the MHC region, we discovered associations for 3 specific HLA class I and II alleles. Notably, HLA-DQB1*05:02 (p = 1.43 × 10-12; OR, 2.10; 95% CI 1.70-2.59) demonstrates the strongest association among classical HLA alleles, closely followed by HLA-A*11:01 (p = 4.36 × 10-7; OR, 1.52; 95% CI 1.29-1.79) and HLA-A*02:07 (p = 1.28 × 10-8; OR, 1.87; 95% CI 1.50-2.31). In addition, we uncovered 2 main HLA amino acid variation associated with anti-NMDAR encephalitis including HLA-DQß1-126H (p = 1.43 × 10-12; OR, 2.10; 95% CI 1.70-2.59), exhibiting a predisposing effect, and HLA-B-97R (p = 3.40 × 10-8; OR, 0.63; 95% CI 0.53-0.74), conferring a protective effect. Computational docking analysis suggested a close relationship between the NR1 subunit of NMDAR and DQB1*05:02. DISCUSSION: Our findings indicate that genetic variation in IFIH1, involved in the type I interferon signaling pathway and innate immunity, along with variations in the HLA class I and class II genes, has substantial implications for the susceptibility to anti-NMDAR encephalitis in the Chinese Han population.

The novel HLA-A*36:14 allele characterised by two different sequencing-based typing techniques.

The novel allele HLA-A*36:14 differs from HLA-A*36:01:01:01 by one non-synonymous nucleotide substitution in exon 4.

The novel HLA-A*30:01:23 allele characterised by two different sequencing-based typing techniques.

The novel allele HLA-A*30:01:23 differs from HLA-A*30:01:01:01 by one synonymous nucleotide substitution in exon 2.

Identification of the novel allele, HLA-A*30:01:22, in a Saudi individual.

A single nucleotide substitution in exon 5 of HLA-A*30:01:01:01 results in the novel HLA-A*30:01:22 allele.

Identification of the HLA-A*11:463 allele in a Chinese patient and his father.

HLA-A*11:463 has one nucleotide change from HLA-A*11:01:01:01 at nucleotide 508 changing Lysine (146) to Glutamine.

Selective pressure mediated by influenza virus M158-66 epitope-specific CD8+T cells promotes accumulation of extra-epitopic amino acid substitutions associated with viral resistance to these T cells.

Influenza viruses are notorious for their capacity to evade host immunity. Not only can they evade recognition by virus-neutralizing antibodies, there is also evidence that they accumulate mutations in epitopes recognized by virus-specific CD8+T cells. In addition, we have shown previously that human influenza A viruses were less well recognized than avian influenza viruses by CD8+T cells directed to the highly conserved, HLA-A*02:01 restricted M158-66 epitope located in the Matrix 1 (M1) protein. Amino acid differences at residues outside the epitope were responsible for the differential recognition, and it was hypothesized that this reflected immune adaptation of human influenza viruses to selective pressure exerted by M158-66-specific CD8+T cells in the human population. In the present study, we tested this hypothesis and investigated if selective pressure exerted by M158-66 epitope-specific CD8+T cells could drive mutations at the extra-epitopic residues in vitro. To this end, isogenic influenza A viruses with the M1 gene of a human or an avian influenza virus were serially passaged in human lung epithelial A549 cells that transgenically express the HLA-A*02:01 molecule or not, in the presence or absence of M158-66 epitope-specific CD8+T cells. Especially in the virus with the M1 gene of an avian influenza virus, variants emerged with mutations at the extra-epitopic residues associated with reduced recognition by M158-66-specific T cells as detected by Next Generation Sequencing. Although the emergence of these variants was observed in the absence of selective pressure exerted by M158-66 epitope-specific CD8+T cells, their proportion was much larger in the presence of this selective pressure.

[Pharmacogenetic testing for prevention of severe cutaneous adverse drug reactions].

Pharmacogenetic testing benefits patients by predicting drug efficacy and risk of adverse drug reactions (ADRs). Pharmacogenetic biomarkers useful in clinical practice include drug-metabolizing enzyme and drug transporter genes and human leukocyte antigen (HLA) genes. HLA genes, which are important molecules involved in human immunity, have long been analyzed for associations with ADRs, such as skin rash, drug-induced liver injury, and agranulocytosis. HLA is composed of many genes, each of which has dozens of different types (alleles), and many HLA alleles associated with ADRs have been reported. The odds ratios in the association of HLA alleles range from approximately 5 to several thousand, indicating a very large impact on the risk of ADRs. Thus, HLA genetic testing prior to initiation of drug therapy is expected to make a significant contribution to avoiding ADRs, but to demonstrate the clinical utility, it is necessary to prospectively show the effects of medical interventions based on the test results. We conducted the GENCAT study, a prospective, multicenter, single-arm clinical trial to investigate the impact of a therapeutic intervention based on the HLA-A*31:01 test on the incidence of carbamazepine-induced skin rash. HLA-A*31:01-positive patients were treated with an alternative drug such as valproic acid, and the study showed an approximately 60% reduction in the incidence of carbamazepine-induced skin rash. It is expected that the genetic test, which has demonstrated clinical utility, will lead to the establishment of safer and more appropriate stratified medicine by reflecting the information in clinical practice guidelines.

Discovery of the novel HLA-A*01:01:01:112 allele in a Greek volunteer bone marrow donor.

HLA-A*01:01:01:112 differs from the HLA-A*01:01:01:01 allele by one nucleotide substitution in the 5'UTR.

[Establishment and validation of prediction models for human leukocyte antigen haplotypes and human leukocyte antigen genotypes].

Objective: To establish prediction models for human leukocyte antigen (HLA) haplotypes and HLA genotypes, and verify the prediction accuracy. Methods: The prediction models were established based on the characteristic of HLA haplotype inheritance and linkage disequilibrium (LD), as well as the invention patents and software copyrights obtained. The models include algorithm and reference databases such as HLA A-C-B-DRB1-DQB1 high-resolution haplotypes database, B-C and DRB1-DQB1 LD database, G group alleles table, and NMDP Code alleles table. The prediction algorithm involves data processing, comparison with reference data, filtering results, probability calculation and ranking, confidence degree estimation, and output of prediction results. The accuracy of the predictions was verified by comparing them with the correct results, and the relationship between prediction accuracy and the probability distribution and confidence degree of the predicted results was analyzed. Results: The HLA haplotypes and genotypes prediction models were established. The prediction algorithm included the prediction of A-C-B-DRB1-DQB1 haplotypes according to HLA-A, B, DRB1, C, DQB1 genotypes, the prediction of C and DQB1 high-resolution results according to A, B and DRB1 high-resolution results, and the prediction of A, B, DRB1, C and DQB1 high resolution results according to the A, B and DRB1 intermediate or low resolution results. Validation results of "Predicting A-C-B-DRB1-DQB1 haplotypes basing on HLA-A, B, DRB1, C, DQB1 genotypes" model: for 787 data, the accuracy was 94.0% (740/787) with 740 correct predictions, 34 incorrect predictions, and 13 instances with no predicted results. For 847 data, the accuracy was 100% (847/847). The 2 411 and 2 594 haplotype combinations predicted from 787 and 847 data were grouped according to confidence degree, the accuracy was 100% (48/48, 114/114) for a confidence degree of 1, 96.2% (303/315) and 97.8% (409/418) for a confidence degree of 2 respectively. Validation results of "Predicting A, B, DRB1 and C, DQB1 high-resolution genotypes basing on HLA-A, B, DRB1 high, intermediate, or low resolution genotypes" model: when predicting C and DQB1 high resolution genotypes basing on A, B, and DRB1 high resolution genotypes, 89.3% (1 459/1 634) of the predictions were correct. The accuracy for the top 2 predicted probability (GPP) ranking was 79.2% (1 156/1 459), and for the top 10, it was 95.0% (1 386/1 459). Furthermore, when GPP≥90% and GPP 50%-90%, the prediction accuracy was 81.3% (209/257) and 72.8% (447/614) respectively. The accuracy of predicting C and DQB1 high resolution genotypes basing on the results of A, B, and DRB1 high resolution genotypes from the China Marrow Donor Program was 87.0% (20/23). The accuracy of predicting A, B, DRB1, C, and DQB1 high resolution genotypes basing on the results of A, B, and DRB1 intermediate or low-resolution genotypes was 70.0% (7/10) and 52.5% (21/40) respectively. When predicting whether the patient is likely to have a HLA 10/10 matched donor, the accuracy of the top 2 GPP combinations with a proportion of ≥50% was 85.7% (6/7). Conclusions: When using A, B, DRB1, C, DQB1 genotypes to predict A-C-B-DRB1-DQB1 haplotype combinations, the results with a confidence degree of 1 and 2 are reliable. When predicting C and DQB1 genotypes according to A, B and DRB1 genotypes, the top 10 results ranked by GPP are reliable, and the top 2 results with GPP≥50% are more reliable.

Characterization of the novel HLA-A*32:177 allele by sequencing-based typing.

HLA-A*32:177 differs from HLA-A*32:01:01:01 by one nucleotide substitution in codon -16 in exon 1.

Contribution of HLA class I (A, B, C) and HLA class II (DRB1, DQA1, DQB1) alleles and haplotypes in exploring ethnic origin of central Tunisians.

BACKGROUND: Estimation of HLA (Human leukocyte Antigen) alleles' frequencies in populations is essential to explore their ethnic origin. Anthropologic studies of central Tunisian population were rarely reported. Then, in this work, we aimed to explore the origin of central Tunisian population using HLA alleles and haplotypes frequencies. METHODS: HLA class I (A, B, C) and HLA class II (DRB1, DQA1, DQB1) loci genotyping of 272 healthy unrelated organ donors was performed by Polymerase Chain Reaction-Sequence Specific Oligonucleotide (PCR-SSO). We compared central Tunisians with other populations (Arabs, Berbers, Mediterraneans, Europeans, Africans, etc.) using alleles and haplotypes frequencies, genetic distances, Neighbour-Joining dendrogram and correspondence analysis. RESULTS: Among the 19 HLA A alleles, the 26 HLA B alleles, the 13 HLA C alleles, the 15 HLA DRB1 alleles, the 6 HLA DQA1 alleles and the 5 HLA DQB1 alleles identified in the studied population, HLA A*02 (22.8%), HLA B*50 (13.1%), HLA C*06 (21.8%), HLA DRB1*07 (17.8%), HLA DQA1*01 (32.1%) and HLA DQB1*03 (31.6%) were the most frequent alleles. The extended haplotypes HLA A*02-B*50-C*06-DRB1*07-DQA1*02-DQB1*02 (1.97%) was the most frequent HLA six-loci haplotype. CONCLUSION: Central Tunisians were very close to other Tunisian populations, to Iberians and North Africans. They were rather distant from sub-Saharan populations and eastern Mediterraneans especially Arabs although the strong cultural and religious impact of Arabs in this population.

Genomic full-length sequence of the novel HLA-A*02:1100 allele.

HLA-A*02:1100 differs from HLA-A*02:01:01:01 by a single non-synonymous nucleotide substitution in codon 76 of exon 2.

The recognition of three novel HLA-A alleles: HLA-A*02:1041Q, -A*02:1042, and -A*02:1043.

Three novel HLA-A alleles HLA-A*02:1041Q, -A*02:1042, and -A*02:1043 alleles detected during routine next generation sequencing.

Interlocus gene conversion: Identification of HLA-A*23:128 in a Brazilian bone marrow donor.

Identification of novel HLA-A*23:128 allele generated by interlocus gene conversion in Brazilian bone marrow donor.

A single nucleotide substitution in intron 3 generated the novel HLA-A*11:01:01:68 allele.

HLA-A*11:01:01:68 differs from HLA-A*11:01:01:01 by one nucleotide change in intron 3 at position 1474 (G > A).

Recognition of the HLA-A*02:840 allele, a variant of A*02:07:01:01, in a Taiwanese individual.

Two nucleotide substitutions in exon 3 of HLA-A*02:07:01:01 result in the novel allele, HLA-A*02:840.

Complete HLA genotyping of type 1 diabetes patients and controls from Mali reveals both expected and novel disease associations.

HLA genotyping was performed on 99 type 1 diabetes (T1D) patients and 200 controls from Mali. Next-generation sequencing of the classical HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and -DPB1 loci revealed strong T1D association for all loci except HLA-C and -DPA1. Class II association is stronger than class I association, with most observed associations predisposing or protective as expected based on previous studies. For example, HLA-DRB1*03:01, HLA-DRB1*09:01, and HLA-DRB1*04:05 predispose for T1D, whereas HLA-DRB1*15:03 is protective. HLA-DPB1*04:02 (OR = 12.73, p = 2.92 × 10-05 ) and HLA-B*27:05 (OR = 21.36, p = 3.72 × 10-05 ) appear highly predisposing, although previous studies involving multiple populations have reported HLA-DPB1*04:02 as T1D-protective and HLA-B*27:05 as neutral. This result may reflect the linkage disequilibrium between alleles on the extended HLA-A*24:02~HLA-B*27:05~HLA-C*02:02~HLA-DRB1*04:05~HLA-DRB4*01:03~HLA-DQB1*02:02~HLA-DQA1*02:01~HLA-DPB1*04:02~HLA-DPA1*01:03 haplotype in this population rather than an effect of either allele itself. Individual amino acid (AA) analyses are consistent with most T1D association attributable to HLA class II rather than class I in this data set. AA-level analyses reveal previously undescribed differences of the HLA-C locus from the HLA-A and HLA-B loci, with more polymorphic positions, spanning a larger portion of the gene. This may reflect additional mechanisms for HLA-C to influence T1D risk, for example, through expression differences or through its role as the dominant ligand for killer cell immunoglobulin-like receptors (KIR). Comparison of these data to those from larger studies and on other populations may facilitate T1D prediction and help elucidate elusive mechanisms of how HLA contributes to T1D risk and autoimmunity.

Confirmation and extension of 18 HLA alleles identified in donors from the Russian bone marrow registry.

Eighteen HLA allele sequences were confirmed and extended: 3 HLA-A, 6 HLA-B, 3 HLA-C, 2 HLA-DRB1, and 4 HLA-DQB1 alleles.

Characterization of novel HLA-A*24:608N allele discovered in Koreans.

A novel null HLA-A*24 allele, HLA-A*24:608N, was identified in five Korean subjects including three from a family and two separate individuals. This study was performed to discern its immunological function in transplantation settings. Because this null variant had deletions of approximately 12 k base pairs from intron 3 to 3' end of the HLA-A gene, low resolution HLA typing and amplicon-based next generation sequencing (NGS) typing methods had failed to assign it. Hybrid capture-based NGS method confirmed that this novel variant had a large deletion. T-lymphocyte crossmatching by complement-dependent lymphocytotoxicity and flow cytometry with a serum consisting anti-HLA-A24 antibody revealed negative results, implying that an individual with this allele would not carry a functioning A24 antigen. These findings highlight the importance of identifying a null HLA allele by employing appropriate molecular method and providing expected crossmatching outcomes in a real-world transplantation setting.

Recruiting refugees and migrants as potential hematopoietic stem cell donors to serve patients of comparable ethnicities with rare human leucocyte antigen patterns - The BluStar.NRW project in North Western Germany.

Currently, approximately 19 million people with a migration background live in Germany. The majority of those descend from regions where the population has a genetically different distribution of HLA antigens when compared to the HLA frequencies usually found in North Western Europe. In case of severe haematological disorders of these individuals, allogeneic stem cell transplantation may be the treatment of choice. However, finding appropriate histocompatible hematopoietic stem cell donors continues to be a major challenge. If no matching sibling donors are available, there are only few suitable donors with a similar genetic background available in international blood stem cell donor registries. The "BluStar.NRW" project aimed to recruit new blood and hematopoietic stem cell donors with a migration background and to noticeably increase the number of suitable donors for patients within this group. Since December 2017, a total number of 9100 blood and stem cell donors with a migration background were recruited and typed for this project. HLA typing for HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1 was performed by Next Generation Sequencing. We assessed the proportion of rare alleles according to HLA frequency tables, as defined by a frequency of <1:1000. The rare HLA allele frequencies according to HLA frequency tables of the BluStar.NRW cohort were compared with a matched control donor cohort: Rare HLA-A, -B, -C, -DRB1 and -DQB1 alleles occurred three times more frequent than in the control group, but rare HLA-DPB1 alleles occurred more frequently in the control cohort. This difference was highly significant for all HLA alleles (p < 0.0001 for HLA-A, -B, -C, -DRB1, -DPB1; p = 0.0002 for HLA-DQB1). In addition, the distribution of rare alleles differed between the two groups. To date, 29 work-ups were initiated, 12 PBSC, one BM and three DLI were collected so far out of the BluStar.NRW cohort. The apheresis probability is twofold higher (0.18% vs. 0.07%) compared to the control group which clearly shows a serious medical need. However, 13 work-ups were cancelled in the BluStar.NRW donor cohort which represents an almost twice as higher cancellation rate (45% vs. 25%). This single registry analysis with a large sample cohort clearly indicates that hematopoietic stem cell donors with a migration background represent an adequate donor pool to serve patients of comparable ethnicity.