Construction of a population-specific HLA imputation reference panel and its application to Graves' disease risk in Japanese

Germline variants and mosaic chromosomal alterations affect COVID-19 vaccine immunogenicity

Vaccine immunogenicity is influenced by the vaccinee's genetic background. Here, we perform a genome-wide association study of vaccine-induced SARS-CoV-2-specific immunoglobulin G (IgG) antibody titers and T cell immune responses in 1,559 mRNA-1273 and 537 BNT162b2 vaccinees of Japanese ancestry. SARS-CoV-2-specific antibody titers are associated with the immunoglobulin heavy chain (IGH) and major histocompatibility complex (MHC) locus, and T cell responses are associated with MHC. The lead variants at IGH contain a population-specific missense variant (rs1043109-C; p.Leu192Val) in the immunoglobulin heavy constant gamma 1 gene (IGHG1), with a strong decreasing effect (β = -0.54). Antibody-titer-associated variants modulate circulating immune regulatory proteins (e.g., LILRB4 and FCRL6). Age-related hematopoietic expanded mosaic chromosomal alterations (mCAs) affecting MHC and IGH also impair antibody production. MHC-/IGH-affecting mCAs confer infectious and immune disease risk, including sepsis and Graves' disease. Impacts of expanded mosaic loss of chromosomes X/Y on these phenotypes were examined. Altogether, both germline and somatic mutations contribute to adaptive immunity functions.

Association Between HLA-DRB1 Alleles and Graves' Disease in Asian Populations: A Meta-Analysis

Graves' disease (GD) is an autoimmune disease that primarily affects the thyroid gland. It is the most common cause of hyperthyroidism. Genetic studies have shown that human leukocyte antigen (HLA) plays an important role in the development of GD. In this article, we performed a meta-analysis determined to evaluate the relationship between HLA-DRB1 alleles and GD. This meta-analysis included 9 studies (3582 cases in the case group and 23070 cases in the control group) and 27 alleles was performed. The combined results showed that, compared with the control group, GD patients have a significant increase in the frequency of DRB1*1403 (OR=2.50, 95% CI=1.78-3.51, pc<0.0001) and have a significant decrease in frequencies of DRB1* 0101 (OR=0.45, 95% CI=0.34-0.59, pc<0.0001) and DRB1*0701 (OR=0.44, 95% CI=0.35-0.55, pc<0.0001). The meta-analysis indicated that, in Asian populations, DRB1*1403 is a risk allele for GD, and DRB1*0101 and DRB1*0701 are protective against the occurrence of GD. We surprisingly discovered that the susceptibility alleles for GD in Asian populations are completely different from Caucasians and the protective alleles for GD in Asians are quite similar to those of Caucasians. The results of our study may provide new opportunities for gene-targeted therapy for GD in Asian populations.

Efficient HLA imputation from sequential SNPs data by transformer

Human leukocyte antigen (HLA) genes are associated with a variety of diseases, yet the direct typing of HLA alleles is both time-consuming and costly. Consequently, various imputation methods leveraging sequential single nucleotide polymorphisms (SNPs) data have been proposed, employing either statistical or deep learning models, such as the convolutional neural network (CNN)-based model, DEEP*HLA. However, these methods exhibit limited imputation efficiency for infrequent alleles and necessitate a large size of reference dataset. In this context, we have developed a Transformer-based model to HLA allele imputation, named "HLA Reliable IMpuatioN by Transformer (HLARIMNT)" designed to exploit the sequential nature of SNPs data. We evaluated HLARIMNT's performance using two distinct reference panels; Pan-Asian reference panel (n = 530) and Type 1 Diabetes genetics Consortium (T1DGC) reference panel (n = 5225), alongside a combined panel (n = 1060). HLARIMNT demonstrated superior accuracy to DEEP*HLA across several indices, particularly for infrequent alleles. Furthermore, we explored the impact of varying training data sizes on imputation accuracy, finding that HLARIMNT consistently outperformed across all data size. These findings suggest that Transformer-based models can efficiently impute not only HLA types but potentially other gene types from sequential SNPs data.

Accurate multi-population imputation of MICA, MICB, HLA-E, HLA-F and HLA-G alleles from genome SNP data

In addition to the classical HLA genes, the major histocompatibility complex (MHC) harbors a high number of other polymorphic genes with less established roles in disease associations and transplantation matching. To facilitate studies of the non-classical and non-HLA genes in large patient and biobank cohorts, we trained imputation models for MICA, MICB, HLA-E, HLA-F and HLA-G alleles on genome SNP array data. We show, using both population-specific and multi-population 1000 Genomes references, that the alleles of these genes can be accurately imputed for screening and research purposes. The best imputation model for MICA, MICB, HLA-E, -F and -G achieved a mean accuracy of 99.3% (min, max: 98.6, 99.9). Furthermore, validation of the 1000 Genomes exome short-read sequencing-based allele calling against a clinical-grade reference data showed an average accuracy of 99.8%, testifying for the quality of the 1000 Genomes data as an imputation reference. We also fitted the models for Infinium Global Screening Array (GSA, Illumina, Inc.) and Axiom Precision Medicine Research Array (PMRA, Thermo Fisher Scientific Inc.) SNP content, with mean accuracies of 99.1% (97.2, 100) and 98.9% (97.4, 100), respectively.

Common and rare genetic variants predisposing females to unexplained recurrent pregnancy loss

Recurrent pregnancy loss (RPL) is a major reproductive health issue with multifactorial causes, affecting 2.6% of all pregnancies worldwide. Nearly half of the RPL cases lack clinically identifiable causes (e.g., antiphospholipid syndrome, uterine anomalies, and parental chromosomal abnormalities), referred to as unexplained RPL (uRPL). Here, we perform a genome-wide association study focusing on uRPL in 1,728 cases and 24,315 female controls of Japanese ancestry. We detect significant associations in the major histocompatibility complex (MHC) region at 6p21 (lead variant=rs9263738; P = 1.4 × 10-10; odds ratio [OR] = 1.51 [95% CI: 1.33-1.72]; risk allele frequency = 0.871). The MHC associations are fine-mapped to the classical HLA alleles, HLA-C*12:02, HLA-B*52:01, and HLA-DRB1*15:02 (P = 1.1 × 10-10, 1.5 × 10-10, and 1.2 × 10-9, respectively), which constitute a population-specific common long-range haplotype with a protective effect (P = 2.8 × 10-10; OR = 0.65 [95% CI: 0.57-0.75]; haplotype frequency=0.108). Genome-wide copy-number variation (CNV) calling demonstrates rare predicted loss-of-function (pLoF) variants of the cadherin-11 gene (CDH11) conferring the risk of uRPL (P = 1.3 × 10-4; OR = 3.29 [95% CI: 1.78-5.76]). Our study highlights the importance of reproductive immunology and rare variants in the uRPL etiology.

HLA-DQA1*01:03 and DQB1*06:01 are risk factors for severe COVID-19 pneumonia

The clinical spectrum of COVID-19 includes a wide range of manifestations, from mild symptoms to severe pneumonia. HLA system plays a pivotal role in immune responses to infectious diseases. The purpose of our study was to investigate the association between HLA and COVID-19 severity in a Japanese population. The study included 209 Japanese COVID-19 patients aged ≥20 years. Saliva samples were collected and used to determine the HLA genotype by HLA imputation through genome-wide association analyses. The association between HLA genotype and COVID-19 severity was then evaluated. The allele frequency was compared between patients with respiratory failure (severe group: 91 cases) and those without respiratory failure (non-severe group: 118 cases), categorising the data into three time periods: pre-Omicron epidemic period, Omicron epidemic period, and total period of this study (from January 2021 to May 2023). In comparing the severe and non-severe groups, the frequencies of the HLA-DQA1*01:03 (35.1% vs. 10.5%, odds ratio [OR] = 4.57, corrected p [pc] = 0.041) and -DQB1*06:01 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) alleles were significantly higher in the severe group during the pre-Omicron epidemic period. During the Omicron epidemic period, HLA-DQB1*06 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) was significantly higher in the severe group. During total period of this study, HLA-DQA1*01:03 (30.2% vs. 14.4%, OR = 2.57, corrected pc = 0.0013) and -DQB1*06:01 (44.5% vs. 26.7%, OR = 2.20, pc = 0.013) alleles were significantly higher in the severe group. HLA-DQB1*06:01 and -DQA1*01:03 were in strong linkage disequilibrium with each other (r2 = 0.91) during total period of this study, indicating that these two alleles form a haplotype. The frequency of the HLA-DQA1*01:03-DQB1*06:01 in the severe group was significantly higher than in the non-severe group during pre-Omicron epidemic period (32.4% vs. 7.9%, OR = 5.59, pc = 0.00072), and total period of this study (28.6% vs. 13.1%, OR = 2.63, pc = 0.0013). During Omicron epidemic period, the haplotype did not demonstrate statistical significance, although the odds ratio indicated a value greater 1. Frequencies of the HLA-DQA1*01:03 and -DQB1*06:01 alleles were significantly higher in severe COVID-19 patients, suggesting that these alleles are risk factors for severe COVID-19 pneumonia in the Japanese population.

Identifying the genetic associations among the psoriasis patients in eastern India

Psoriasis is a multifactorial genetic disorder manifested by hyperproliferation and abnormal differentiation of epidermal keratinocytes, along with the infiltration of inflammatory cells into the skin. Although ~80 genetic susceptibility variants were reported in psoriasis, many loci showed population-specific associations, warranting the need for more population-specific association studies in psoriasis. We determined the association of forty single nucleotide polymorphisms (SNPs) among 2136 psoriasis patients and normal individuals from eastern India. We investigated the expression of corresponding genes and evaluated the protein structure stability for the genes with susceptible coding variants. We found fifteen SNPs significantly associated with psoriasis, while additional three SNPs showed significant association when we classified the patients based on the presence of HLA-Cw6 allele. Epistatic interaction between HLA-Cw6 and other associated loci showed significant association with the SNPs at PSORS1 region, along with other five SNPs outside PSORS1. Three genes showed significant differential expression in psoriatic tissues compared to the adjacent normal skin tissues but were not differential when classified the patients based on their genotypes. SNP rs495337 at SPATA2 (Spermatogenesis Associated 2) showed a 1.2-fold increased risk among the HLA-Cw6 patients compared to combined samples. We found significant downregulation of SPATA2 among the patients with risk genotypes and HLA-Cw6 allele compared to the non-risk genotypes. Protein structure stability analysis showed reduced structural stability for all the mutant residues caused by the associated coding variants. Our study evaluated the genetic associations of psoriasis-susceptible variants in India and evaluated the possible functional significance of these associated variants in psoriasis.

Optimal population-specific HLA imputation with dimension reduction

Human genomics has quickly evolved, powering genome-wide association studies (GWASs). SNP-based GWASs cannot capture the intense polymorphism of HLA genes, highly associated with disease susceptibility. There are methods to statistically impute HLA genotypes from SNP-genotypes data, but lack of diversity in reference panels hinders their performance. We evaluated the accuracy of the 1000 Genomes data as a reference panel for imputing HLA from admixed individuals of African and European ancestries, focusing on (a) the full dataset, (b) 10 replications from 6 populations, and (c) 19 conditions for the custom reference panels. The full dataset outperformed smaller models, with a good F1-score of 0.66 for HLA-B. However, custom models outperformed the multiethnic or population models of similar size (F1-scores up to 0.53, against up to 0.42). We demonstrated the importance of using genetically specific models for imputing populations, which are currently underrepresented in public datasets, opening the door to HLA imputation for every genetic population.

Neoself Antigens Presented on MHC Class II Molecules in Autoimmune Diseases

Major histocompatibility complex (MHC) class II molecules play a crucial role in immunity by presenting peptide antigens to helper T cells. Immune cells are generally tolerant to self-antigens. However, when self-tolerance is broken, immune cells attack normal tissues or cells, leading to the development of autoimmune diseases. Genome-wide association studies have shown that MHC class II is the gene most strongly associated with the risk of most autoimmune diseases. When misfolded self-antigens, called neoself antigens, are associated with MHC class II molecules in the endoplasmic reticulum, they are transported by the MHC class II molecules to the cell surface without being processed into peptides. Moreover, neoself antigens that are complexed with MHC class II molecules of autoimmune disease risk alleles exhibit distinct antigenicities compared to normal self-antigens, making them the primary targets of autoantibodies in various autoimmune diseases. Elucidation of the immunological functions of neoself antigens presented on MHC class II molecules is crucial for understanding the mechanism of autoimmune diseases.

Association of Genetic Variants of HLA-DQA1 with Bullous Pemphigoid Induced by Dipeptidyl Peptidase-4 Inhibitors

Bullous pemphigoid (BP) is the most common autoimmune blistering disorder. Several factors, including an antidiabetic (dipeptidyl peptidase-4 inhibitor [DPP-4i]), have been reported to trigger BP. To identify the genetic variants associated with BP, GWAS and HLA fine-mapping analyses were conducted. The 21 cases of noninflammatory BP induced by DPP-4i (i.e., DPP-4i-induced noninflammatory BP) and 737 controls (first cohort) and the 8 cases and 164 controls (second cohort) were included in the GWAS. Combining GWAS satisfied the genome-wide significant association of HLA-DQA1 (chromosome 6, rs3129763 [T/C]) with the risk of DPP-4i-induced noninflammatory BP (allele T carrier of 72.4% [21 of 29] in cases vs. 15.3% [138 of 901] in controls; dominant model, OR = 14, P = 1.8 × 10-9). HLA fine mapping revealed that HLA-DQA1∗05 with serine at position 75 of HLA-DQα1 (Ser75) had the most significant association with the combined cohort of DPP-4i-induced noninflammatory BP (79.3% [23 of 29] cases vs. 16.1% [145 of 901] controls; dominant model, OR = 21, P = 2.0 × 10-10). HLA-DQα1 Ser75 polymorphism was located inside the functional pocket of HLA-DQ molecules, suggesting the impact of HLA-DQα1 Ser75 on DPP-4i-induced noninflammatory BP.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Contribution of an Asian-prevalent HLA haplotype to the risk of HBV-related hepatocellular carcinoma

Liver cancer, particularly hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), is more common in Asians than in Caucasians. This is due, at least in part, to regional differences in the prevalence of exogenous factors such as HBV; however, endogenous factors specific to Asia might also play a role. Such endogenous factors include HLA (human leukocyte antigen) genes, which are considered candidates due to their high racial diversity. Here, we performed a pancancer association analysis of 147 alleles of HLA-class I/II genes (HLA-A, B, and C/DRB1, DQA1, DQB1, DPA1, and DPB1) in 31,727 cases of 12 cancer types, including 1684 liver cancer cases and 107,103 controls. HLA alleles comprising a haplotype prevalent in Asia were significantly associated with pancancer risk (e.g., odds ratio [OR] for a DRB1*15:02 allele = 1.12, P = 2.7 × 10-15), and the associations were particularly strong in HBV-related HCC (OR 1.95, P = 2.8 × 10-5). In silico prediction suggested that the DRB1*15:02 molecule encoded by the haplotype does not bind efficiently to HBV-derived peptides. RNA sequencing indicated that HBV-related HCC in carriers of the haplotype shows low infiltration by NK cells. These results indicate that the Asian-prevalent HLA haplotype increases the risk of HBV-related liver cancer risk by attenuating immune activity against HBV infection, and by reducing NK cell infiltration into the tumor.

Genome-Wide Association Study in Acute Tubulointerstitial Nephritis

SIGNIFICANCE STATEMENT

Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR β 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN.

BACKGROUND

Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design.

METHODS

We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations.

RESULTS

Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy.

CONCLUSIONS

We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.

Unrelated Stem Cell Donor HLA Match Likelihood in the US Registry Incorporating HLA-DPB1 Permissive Mismatching

Donor-recipient HLA matching at the DPB1 locus improves the outcomes of hematopoietic stem cell transplantation (HCT). Retrospective outcome studies found that in HCTs matched for all 8 alleles of the A, B, C, and DRB1 loci at high resolution (8/8 match), few transplantations were also allele-matched at the DPB1 locus. DPB1 allele matching was once thought to be logistically impractical; however, a DPB1-permissive mismatch model based on T cell epitope (TCE) reactivity expands the proportion of suitable donors. To understand the likelihood of finding a DPB1-permissive donor, we sought to expand population genetic match likelihood models for the US unrelated donor registry, the National Marrow Donor Program (NMDP). After extending HLA haplotype frequency estimates to include the DPB1 locus, our models found that the likelihood of having a DPB1-permissive donor was not much lower than likelihood of 8/8 matching. A maximum of 5 additional donors would need to be typed to find a more optimal DPB1-permissive donor at least 90% of the time. Linkage disequilibrium patterns between the DPB1 locus and other classical HLA loci varied markedly by haplotype and population, indicating that the known recombination hotspot between DQ and DP gene complexes has not had a uniform impact; thus, DPB1-permissive donors are easier to identify within minority populations. DPB1 TCE categories were highly predictable from HLA typing at other loci when imputed with extended haplotype frequency data. Our overall results indicate that registry search strategies that seek a more optimally matched HCT donor encompassing HLA-DPB1 permissibility are likely to be highly productive.

Control of naive and effector CD4 T cell receptor repertoires by rheumatoid-arthritis-risk HLA alleles

OBJECTIVE

Human Leukocyte Antigen (HLA) alleles regulate susceptibility to rheumatoid arthritis (RA) and immune-mediated diseases. This study aims to elucidate the impact of HLA alleles to T cell subsets.

METHODS

We performed genome-wide and HLA allele association analysis for T cell receptor (TCR) beta chain repertoire in 13 purified T cell subsets from the ImmuNexUT database, consisting of 407 donors with ten immune-mediated diseases and healthy controls.

RESULTS

HLA class II alleles were associated with TRBV gene usage and the public clones of CD4 T cells, while HLA class I alleles were associated with CD8 T cells. RA-risk and immune-mediated diseases-risk HLA alleles were associated with TRBV gene usage of naive and effector CD4 T cell subsets and public clones accumulating in Th17. Clonal diversity was independent of HLA alleles and was correlated with transcriptome changes that reflect TCR signaling.

CONCLUSION

This study revealed in vivo evidence that both HLA alleles and environmental factors shape naive and effector TCR repertoires in RA and immune-mediated diseases patients.

PGG.MHC: toward understanding the diversity of major histocompatibility complexes in human populations

The human leukocyte antigen (HLA) system, or the human version of the major histocompatibility complex (MHC), is known for its extreme polymorphic nature and high heterogeneity. Taking advantage of whole-genome and whole-exome sequencing data, we developed PGG.MHC to provide a platform to explore the diversity of the MHC in Asia as well as in global populations. PGG.MHC currently archives high-resolution HLA alleles of 53 254 samples representing 190 populations spanning 66 countries. PGG.MHC provides: (i) high-quality allele frequencies for eight classical HLA loci (HLA-A, -B, -C, -DQA1, -DQB1, -DRB1, -DPA1 and -DPB1); (ii) visualization of population prevalence of HLA alleles on global, regional, and country-wide levels; (iii) haplotype structure of 134 populations; (iv) two online analysis tools including 'HLA imputation' for inferring HLA alleles from SNP genotyping data and 'HLA association' to perform case/control studies for HLA-related phenotypes and (v) East Asian-specific reference panels for HLA imputation. Equipped with high-quality frequency data and user-friendly computer tools, we expect that the PGG.MHC database can advance the understanding and facilitate applications of MHC genomic diversity in both evolutionary and medical studies. The PGG.MHC database is freely accessible via https://pog.fudan.edu.cn/pggmhc or https://www.pggmhc.org/pggmhc.

Blood donor biobank and HLA imputation as a resource for HLA homozygous cells for therapeutic and research use

Background

Allogeneic therapeutic cells may be rejected if they express HLA alleles not found in the recipient. As finding cell donors with a full HLA match to a recipient requires vast donor pools, the use of HLA homozygous cells has been suggested as an alternative. HLA homozygous cells should be well tolerated by those who carry at least one copy of donor HLA alleles. HLA-A-B homozygotes could be valuable for HLA-matched thrombocyte products. We evaluated the feasibility of blood donor biobank and HLA imputation for the identification of potential cell donors homozygous for HLA alleles.

Methods

We imputed HLA-A, -B, -C, -DRB1, -DQA1, -DQB1 and -DPB1 alleles from genotypes of 20,737 Finnish blood donors in the Blood Service Biobank. We confirmed homozygosity by sequencing HLA alleles in 30 samples and by examining 36,161 MHC-located polymorphic DNA markers.

Results

Three hundred and seventeen individuals (1.5%), representing 41 different haplotypes, were found to be homozygous for HLA-A, -B, -C, -DRB1, -DQA1 and -DQB1 alleles. Ten most frequent haplotypes homozygous for HLA-A to -DQB1 were HLA-compatible with 49.5%, and three most frequent homozygotes to 30.4% of the Finnish population. Ten most frequent HLA-A-B homozygotes were compatible with 75.3%, and three most frequent haplotypes to 42.6% of the Finnish population. HLA homozygotes had a low level of heterozygosity in MHC-located DNA markers, in particular in HLA haplotypes enriched in Finland.

Conclusions

The present study shows that HLA imputation in a blood donor biobank of reasonable size can be used to identify HLA homozygous blood donors suitable for cell therapy, HLA-typed thrombocytes and research. The homozygotes were HLA-compatible with a large fraction of the Finnish population. Regular blood donors reported to have positive attitude to research donation appear a good option for these purposes. Differences in population frequencies of HLA haplotypes emphasize the need for population-specific collections of HLA homozygous samples.

Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method

The killer cell immunoglobulin-like receptor (KIR) recognizes human leukocyte antigen (HLA) class I molecules and modulates the function of natural killer cells. Despite its role in immunity, the complex genomic structure has limited a deep understanding of the KIR genomic landscape. Here we conduct deep sequencing of 16 KIR genes in 1,173 individuals. We devise a bioinformatics pipeline incorporating copy number estimation and insertion or deletion (indel) calling for high-resolution KIR genotyping. We define 118 alleles in 13 genes and demonstrate a linkage disequilibrium structure within and across KIR centromeric and telomeric regions. We construct a KIR imputation reference panel (n_reference = 689, imputation accuracy = 99.7%), apply it to biobank genotype (n_total = 169,907), and perform phenome-wide association studies of 85 traits. We observe a dearth of genome-wide significant associations, even in immune traits implicated previously to be associated with KIR (the smallest p = 1.5 × 10^-4). Our pipeline presents a broadly applicable framework to evaluate innate immunity in large-scale datasets.

Abrogation of self-tolerance by misfolded self-antigens complexed with MHC class II molecules

Specific MHC class II alleles are strongly associated with susceptibility to various autoimmune diseases. Although the primary function of MHC class II molecules is to present peptides to helper T cells, MHC class II molecules also function like a chaperone to transport misfolded intracellular proteins to the cell surface. In this study, we found that autoantibodies in patients with Graves' disease preferentially recognize thyroid-stimulating hormone receptor (TSHR) complexed with MHC class II molecules of Graves' disease risk alleles, suggesting that the aberrant TSHR transported by MHC class II molecules is the target of autoantibodies produced in Graves' disease. Mice injected with cells expressing mouse TSHR complexed with MHC class II molecules, but not TSHR alone, produced anti-TSHR autoantibodies. These findings suggested that aberrant self-antigens transported by MHC class II molecules exhibit antigenic properties that differ from normal self-antigens and abrogate self-tolerance, providing a novel mechanism for autoimmunity.

Insights into Current Management Strategies for Dysthyroid Optic Neuropathy: A Review

Dysthyroid optic neuropathy (DON) is a potentially sight-threatening eye disease associated with Graves’ orbitopathy (GO). DON is not common in GO patients, reportedly occurring in only about 5% of patients. The pathogenesis of severe DON is considered to involve both muscular nerve strangulation and impaired blood flow. There is some objective grading of physical examination findings and the severity of GO, including a clinical activity score (CAS) and EUropean Group On Graves’ Orbitopathy (EUGOGO), but no specialized protocol completely characterizes DON. Most clinicians have decided that the combination of clinical activity findings, including visual acuity, color vision, and central critical fusion frequency, and radiological findings, including magnetic resonance imaging (MRI), can be used to diagnose DON. MRI has the most useful findings, with T2-weighted and fat-suppressed images using short-tau inversion recovery (STIR) sequences enabling detection of extraocular changes including muscle and/orbital fat tissue swelling and inflammation and, therefore, disease activity. The first-choice treatment for DON is intravenous administration of steroids, with or without radiotherapy. Unfortunately, refractoriness to this medical treatment may indicate the need for immediate orbital decompression within 2 weeks. Especially in the acute phase of DON, thyroid function is often unstable, and the surgeon must always assume the risk of general anesthesia and intra- and post-operative management. In addition, there are currently many possible therapeutic options, including molecular-targeted drugs. The early introduction and combination of these immunomodulators, including Janus kinase inhibitors and insulin-like growth factor-1 receptor antibody (teprotumumab), may be effective for GO with DON. However, this is still under investigation, and the number of case reports is small. It is possible that these options could reduce systemic adverse events due to unfocused glucocorticoid administration. The pathophysiology of DON is not yet fully understood, and further studies of its treatment and long-term visual function prognosis are needed.

Fine Mapping Analysis of the MHC Region to Identify Variants Associated With Chinese Vitiligo and SLE and Association Across These Diseases

The important role of MHC in the pathogenesis of vitiligo and SLE has been confirmed in various populations. To map the most significant MHC variants associated with the risk of vitiligo and SLE, we conducted fine mapping analysis using 1117 vitiligo cases, 1046 SLE cases and 1693 healthy control subjects in the Han-MHC reference panel and 1000 Genomes Project phase 3. rs113465897 (P=1.03×10^-13, OR=1.64, 95%CI =1.44–1.87) and rs3129898 (P=4.21×10^-17, OR=1.93, 95%CI=1.66–2.25) were identified as being most strongly associated with vitiligo and SLE, respectively. Stepwise conditional analysis revealed additional independent signals at rs3130969(p=1.48×10^-7, OR=0.69, 95%CI=0.60–0.79), HLA-DPB1*03:01 (p=1.07×10^-6, OR=1.94, 95%CI=1.49–2.53) being linked to vitiligo and HLA-DQB1*0301 (P=4.53×10^-7, OR=0.62, 95%CI=0.52-0.75) to SLE. Considering that epidemiological studies have confirmed comorbidities of vitiligo and SLE, we used the GCTA tool to analyse the genetic correlation between these two diseases in the HLA region, the correlation coefficient was 0.79 (P=5.99×10^-10, SE=0.07), confirming their similar genetic backgrounds. Our findings highlight the value of the MHC region in vitiligo and SLE and provide a new perspective for comorbidities among autoimmune diseases.

Low MICA Gene Expression Confers an Increased Risk of Graves' Disease: A Mendelian Randomization Study

Background: Expression of natural killer group 2 member D (NKG2D) ligand (NKG2DL) plays a major role as a "danger signal" on stressed cells to promote removal of the latter by NKG2D-expressing cytotoxic lymphocytes. NKG2DL expression has been found in peripheral immune cells as well, such as in macrophages; however, the effect of this expression is yet to be determined. Methods: We determined instrumental variables (IVs; R² <0.01 in linkage disequilibrium), explaining the major variance in major histocompatibility complex class I chain-related protein A (MICA) and B (MICB) gene expression levels from the expression-quantitative trait locus (eQTL) of NKG2DLs based on the RNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from 381 Japanese. Simultaneously, the target outcomes were filtered by PheWAS from 58 health risks, using a community-based cohort study composed of 44,739 Japanese residents. Finally, we estimated the causal effect of gene expression levels on the outcomes using the Mendelian randomization approach. Results: We determined nine and four IVs, explaining 87.6% and 33.0% of MICA and MICB gene expression levels, respectively. In the association test, we identified 10 or 13 significant outcomes associated with the MICA or MICB eQTLs, respectively, as well as the causal effect of MICA expression on Graves' disease (GD) (p = 4.2 × 10^-3; odds ratio per 1 S.D. difference in the expression: 0.983 [confidence interval: 0.971-0.995]), using the weighted median estimator, without significant pleiotropy (p > 0.05), and the results were consistent across the sensitivity analyses. Conclusions: Our study provide novel evidence associating NKG2DL expression with GD, an autoimmune thyroiditis; direction of the effect indicated the immunoregulatory role of MICA expression in PBMCs, suggesting the importance of further functional assays in inflammatory diseases.

Phenome-wide association study of the major histocompatibility complex region in the Korean population identifies novel association signals

Human leukocyte antigen (HLA) gene variants in the major histocompatibility complex (MHC) region are associated with numerous complex human diseases and quantitative traits. Previous phenome-wide association studies (PheWAS) for this region demonstrated that HLA association patterns to the phenome have both population-specific and population-shared components. We performed MHC PheWAS in the Korean population by analyzing associations between phenotypes and genetic variants in the MHC region using the Korea Biobank Array project data samples from the Korean Genome and Epidemiology Study (KoGES) cohorts. Using this single-population dataset, we curated and analyzed 82 phenotypes for 125 673 Korean individuals after imputing HLA using CookHLA, a recently developed imputation framework. More than one-third of these phenotypes showed significant associations, confirming 56 known associations and discovering 13 novel association signals that were not reported previously. In addition, we analyzed heritability explained by the variants in the MHC region and genetic correlations among phenotypes based on the MHC variants.

Transethnic analysis of psoriasis susceptibility in South Asians and Europeans enhances fine-mapping in the MHC and genomewide

Because transethnic analysis may facilitate prioritization of causal genetic variants, we performed a genomewide association study (GWAS) of psoriasis in South Asians (SAS), consisting of 2,590 cases and 1,720 controls. Comparison with our existing European-origin (EUR) GWAS showed that effect sizes of known psoriasis signals were highly correlated in SAS and EUR (Spearman ρ = 0.78; p < 2 × 10-14). Transethnic meta-analysis identified two non-MHC psoriasis loci (1p36.22 and 1q24.2) not previously identified in EUR, which may have regulatory roles. For these two loci, the transethnic GWAS provided higher genetic resolution and reduced the number of potential causal variants compared to using the EUR sample alone. We then explored multiple strategies to develop reference panels for accurately imputing MHC genotypes in both SAS and EUR populations and conducted a fine-mapping of MHC psoriasis associations in SAS and the largest such effort for EUR. HLA-C*06 was the top-ranking MHC locus in both populations but was even more prominent in SAS based on odds ratio, disease liability, model fit and predictive power. Transethnic modeling also substantially boosted the probability that the HLA-C*06 protein variant is causal. Secondary MHC signals included coding variants of HLA-C and HLA-B, but also potential regulatory variants of these two genes as well as HLA-A and several HLA class II genes, with effects on both chromatin accessibility and gene expression. This study highlights the shared genetic basis of psoriasis in SAS and EUR populations and the value of transethnic meta-analysis for discovery and fine-mapping of susceptibility loci.

HLA imputation and its application to genetic and molecular fine-mapping of the MHC region in autoimmune diseases

Variations of human leukocyte antigen (HLA) genes in the major histocompatibility complex region (MHC) significantly affect the risk of various diseases, especially autoimmune diseases. Fine-mapping of causal variants in this region was challenging due to the difficulty in sequencing and its inapplicability to large cohorts. Thus, HLA imputation, a method to infer HLA types from regional single nucleotide polymorphisms, has been developed and has successfully contributed to MHC fine-mapping of various diseases. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of accuracy and computational performance. Additionally, advances in HLA reference panels by next-generation sequencing technologies have enabled higher resolution and a more reliable imputation, allowing a finer-grained evaluation of the association between sequence variations and disease risk. Risk-associated variants in the MHC region would affect disease susceptibility through complicated mechanisms including alterations in peripheral responses and central thymic selection of T cells. The cooperation of reliable HLA imputation methods, informative fine-mapping, and experimental validation of the functional significance of MHC variations would be essential for further understanding of the role of the MHC in the immunopathology of autoimmune diseases.

CoMM-S4: A Collaborative Mixed Model Using Summary-Level eQTL and GWAS Datasets in Transcriptome-Wide Association Studies

Motivation: Genome-wide association studies (GWAS) have achieved remarkable success in identifying SNP-trait associations in the last decade. However, it is challenging to identify the mechanisms that connect the genetic variants with complex traits as the majority of GWAS associations are in non-coding regions. Methods that integrate genomic and transcriptomic data allow us to investigate how genetic variants may affect a trait through their effect on gene expression. These include CoMM and CoMM-S², likelihood-ratio-based methods that integrate GWAS and eQTL studies to assess expression-trait association. However, their reliance on individual-level eQTL data render them inapplicable when only summary-level eQTL results, such as those from large-scale eQTL analyses, are available. Result: We develop an efficient probabilistic model, CoMM-S⁴, to explore the expression-trait association using summary-level eQTL and GWAS datasets. Compared with CoMM-S², which uses individual-level eQTL data, CoMM-S⁴ requires only summary-level eQTL data. To test expression-trait association, an efficient variational Bayesian EM algorithm and a likelihood ratio test were constructed. We applied CoMM-S⁴ to both simulated and real data. The simulation results demonstrate that CoMM-S⁴ can perform as well as CoMM-S² and S-PrediXcan, and analyses using GWAS summary statistics from Biobank Japan and eQTL summary statistics from eQTLGen and GTEx suggest novel susceptibility loci for cardiovascular diseases and osteoporosis. Availability and implementation: The developed R package is available at https://github.com/gordonliu810822/CoMM.

A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance.

An immunogenetic view of COVID-19

Meeting the challenges brought by the COVID-19 pandemic requires an interdisciplinary approach. In this context, integrating knowledge of immune function with an understanding of how genetic variation influences the nature of immunity is a key challenge. Immunogenetics can help explain the heterogeneity of susceptibility and protection to the viral infection and disease progression. Here, we review the knowledge developed so far, discussing fundamental genes for triggering the innate and adaptive immune responses associated with a viral infection, especially with the SARS-CoV-2 mechanisms. We emphasize the role of the HLA and KIR genes, discussing what has been uncovered about their role in COVID-19 and addressing methodological challenges of studying these genes. Finally, we comment on questions that arise when studying admixed populations, highlighting the case of Brazil. We argue that the interplay between immunology and an understanding of genetic associations can provide an important contribution to our knowledge of COVID-19.

Genome-wide association study reveals an association between the HLA-DPB1∗02:01:02 allele and wheat-dependent exercise-induced anaphylaxis

Wheat-dependent exercise-induced anaphylaxis (WDEIA) is a life-threatening food allergy triggered by wheat in combination with the second factor such as exercise. The identification of potential genetic risk factors for this allergy might help high-risk individuals before consuming wheat-containing food. We aimed to identify genetic variants associated with WDEIA. A genome-wide association study was conducted in a discovery set of 77 individuals with WDEIA and 924 control subjects via three genetic models. The associations were confirmed in a replication set of 91 affected individuals and 435 control individuals. Summary statistics from the combined set were analyzed by meta-analysis with a random-effect model. In the discovery set, a locus on chromosome 6, rs9277630, was associated with WDEIA in the dominant model (OR = 3.95 [95% CI, 2.31-6.73], p = 7.87 × 10-8). The HLA-DPB1∗02:01:02 allele displayed the most significant association with WDEIA (OR = 4.51 [95% CI, 2.66-7.63], p = 2.28 × 10-9), as determined via HLA imputation following targeted sequencing. The association of the allele with WDEIA was confirmed in replication samples (OR = 3.82 [95% CI, 2.33-6.26], p = 3.03 × 10-8). A meta-analysis performed in the combined set revealed that the HLA-DPB1∗02:01:02 allele was significantly associated with an increased risk of WDEIA (OR = 4.13 [95% CI, 2.89-5.93], p = 1.06 × 10-14). Individuals carrying the HLA-DPB1∗02:01:02 allele have a significantly increased risk of WDEIA. Further validation of these findings in independent multiethnic cohorts is needed.

Trans-Ethnic Fine-Mapping of the Major Histocompatibility Complex Region Linked to Parkinson's Disease

BACKGROUND

Despite evidence for the role of human leukocyte antigen (HLA) in the genetic predisposition to Parkinson's disease (PD), the complex haplotype structure and highly polymorphic feature of the major histocompatibility complex (MHC) region has hampered a unified insight on the genetic risk of PD. In addition, a majority of the reports focused on Europeans, lacking evidence on other populations.

OBJECTIVES

The aim of this study is to elucidate the genetic features of the MHC region associated with PD risk in trans-ethnic cohorts.

METHODS

We conducted trans-ethnic fine-mapping of the MHC region for European populations (14,650 cases and 1,288,625 controls) and East Asian populations (7712 cases and 27,372 controls). We adopted a hybrid fine-mapping approach including both HLA genotype imputation of genome-wide association study (GWAS) data and direct imputation of HLA variant risk from the GWAS summary statistics.

RESULTS

Through trans-ethnic MHC fine-mapping, we identified the strongest associations at amino acid position 13 of HLA-DRβ1 (P = 6.0 × 10-15 ), which explains the majority of the risk in HLA-DRB1. In silico prediction revealed that HLA-DRB1 alleles with histidine at amino acid position 13 (His13) had significantly weaker binding affinity to an α-synuclein epitope than other alleles (P = 9.6 × 10-4 ). Stepwise conditional analysis suggested additional independent associations at Ala69 in HLA-B (P = 1.0 × 10-7 ). A subanalysis in Europeans suggested additional independent associations at non-HLA genes in the class III MHC region (EHMT2; P = 2.5 × 10-7 ).

CONCLUSIONS

Our study highlights the shared and distinct genetic features of the MHC region in patients with PD across ethnicities. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Genetic susceptibility to multiple sclerosis: interactions between conserved extended haplotypes of the MHC and other susceptibility regions

BACKGROUND

To study the accumulation of MS-risk resulting from different combinations of MS-associated conserved-extended-haplotypes (CEHs) of the MHC and three non-MHC "risk-haplotypes" nearby genes EOMES, ZFP36L1, and CLEC16A. Many haplotypes are MS-associated despite having population-frequencies exceeding the percentage of genetically-susceptible individuals. The basis of this frequency-disparity requires explanation.

METHODS

The SNP-data from the WTCCC was phased at the MHC and three non-MHC susceptibility-regions. CEHs at the MHC were classified into five haplotype-groups: (HLA-DRB1*15:01 ~ DQB1*06:02 ~ a1)-containing (H +); extended-risk (ER); all-protective (AP); neutral (0); and the single-CEH (c1). MS-associations for different "risk-combinations" at the MHC and other non-MHC "risk-loci" and the appropriateness of additive and multiplicative risk-accumulation models were assessed.

RESULTS

Different combinations of "risk-haplotypes" produce a final MS-risk closer to additive rather than multiplicative risk-models but neither model was consistent. Thus, (H +)-haplotypes had greater impact when combined with (0)-haplotypes than with (H +)-haplotypes, whereas, (H +)-haplotypes had greater impact when combined with a (c1)-haplotypes than with (0)-haplotypes. Similarly, risk-genotypes (0,H +), (c1,H +), (H + ,H +) and (0,c1) were additive with risks from non-MHC risk-loci, whereas risk-genotypes (ER,H +) and (AP,c1) were unaffected.

CONCLUSIONS

Genetic-susceptibility to MS is essential for MS to develop but actually developing MS depends heavily upon both an individual's particular combination of "risk-haplotypes" and how these loci interact.

Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population

Elucidation of natural selection signatures and relationships with phenotype spectra is important to understand adaptive evolution of modern humans. Here, we conducted a genome-wide scan of selection signatures of the Japanese population by estimating locus-specific time to the most recent common ancestor using the ascertained sequentially Markovian coalescent (ASMC), from the biobank-based large-scale genome-wide association study data of 170,882 subjects. We identified 29 genetic loci with selection signatures satisfying the genome-wide significance. The signatures were most evident at the alcohol dehydrogenase (ADH) gene cluster locus at 4q23 (P_ASMC = 2.2 × 10⁻³⁶), followed by relatively strong selection at the FAM96A (15q22), MYOF (10q23), 13q21, GRIA2 (4q32), and ASAP2 (2p25) loci (P_ASMC < 1.0 × 10⁻¹⁰). The additional analysis interrogating extended haplotypes (integrated haplotype score) showed robust concordance of the detected signatures, contributing to fine-mapping of the genes, and provided allelic directional insights into selection pressure (e.g., positive selection for ADH1B-Arg48His and HLA-DPB1*04:01). The phenome-wide selection enrichment analysis with the trait-associated variants identified a variety of the modern human phenotypes involved in the adaptation of Japanese. We observed population-specific evidence of enrichment with the alcohol-related phenotypes, anthropometric and biochemical clinical measurements, and immune-related diseases, differently from the findings in Europeans using the UK Biobank resource. Our study demonstrated population-specific features of the selection signatures in Japanese, highlighting a value of the natural selection study using the nation-wide biobank-scale genome and phenotype data.

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes

Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce the reliability of trans-ethnic major histocompatibility complex (MHC) fine-mapping due to inter-ethnic heterogeneity in allele frequency spectra. We develop DEEP*HLA, a deep learning method for imputing HLA genotypes. Through validation using the Japanese and European HLA reference panels (n = 1,118 and 5,122), DEEP*HLA achieves the highest accuracies with significant superiority for low-frequency and rare alleles. DEEP*HLA is less dependent on distance-dependent linkage disequilibrium decay of the target alleles and might capture the complicated region-wide information. We apply DEEP*HLA to type 1 diabetes GWAS data from BioBank Japan (n = 62,387) and UK Biobank (n = 354,459), and successfully disentangle independently associated class I and II HLA variants with shared risk among diverse populations (the top signal at amino acid position 71 of HLA-DRβ1; P = 7.5 × 10^-120). Our study illustrates the value of deep learning in genotype imputation and trans-ethnic MHC fine-mapping.

Human leucocyte antigen alleles confer susceptibility and progression to Graves' ophthalmopathy in a Southern Chinese population

Purpose

To evaluate the contributions of human leucocyte antigen (HLA) class I and II genes in the development of Graves’ ophthalmopathy (GO) in a Southern Chinese population.

Methods

Eight HLA loci were genotyped and analysed in 272 unrelated patients with Graves’ disease (GD) or the proptosis and myogenic phenotypes of GO, and 411 ethnically matched control subjects.

Results

The allele frequencies of HLA-DRB1*16:02 and -DQB1*05:02 in the GD, proptosis and myogenic groups, HLA-B*38:02 and -DQA1*01:02 in the myogenic group were significantly higher than those in the control group, respectively (all corrected p values <0.05, OR >2.5). The haplotype frequencies of HLA-DRB1*16:02-DQA1*01:02-DQB1*05:02 and HLA-DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*05:01 in the proptosis and myogenic groups, and HLA-A*02:03-B*38:02-C*07:02 and HLA-A*02:03-B*38:02-C*07:02-DRB1*16:02-DQA1*01:02-DQB1*05:02-DPA1*02:02-DPB1*05:01 in the myogenic group were significantly higher than those in the control group respectively (all corrected p values <0.05, OR >2.5). The potential epitopes (‘FLGIFNTGL’ of TSHR, ‘IRHSHALVS’, ‘ILYIRTNAS’ and ‘FVFARTMPA’ of IGF-1R) were fitted exactly in the peptide-binding groove between HLA-DRA1-DRB1*16:02 heterodimer, and the epitopes (‘ILEITDNPY’ of THSR, ‘NYALVIFEM’ and ‘NYSFYVLDN’ of IGF-1R) were also fitted exactly in the peptide-binding groove between HLA-DQA1*01:02-DQB1*05:02 heterodimer.

Conclusions

The HLA-DRB1*16:02 and -DQB1*01:02 alleles might be risk factors for GD including the proptosis and myogenic phenotypes of GO. The alleles HLA-B*38:02, -DQA1*01:02, the HLA haplotypes consisting of HLA-B*38:02, -DRB1*16:02, -DQA1*01:02 and -DQB1*05:02 might be susceptibility risk factors for GO. Simultaneously, some epitopes of TSHR and IGF-1R tightly binding to groove of HLA-DRA1-DRB1*16:02 or HLA-DQA1*01:02-DQB1*05:02 heterodimers might provide some hints on presenting the pathological antigen in GO.

Copy number variations in BOLA-DQA2, BOLA-DQB, and BOLA-DQA5 show the genomic architecture and haplotype frequency of major histocompatibility complex class II genes in Holstein cows

Bovine major histocompatibility complex (MHC) class II region contains many genes. The bovine leukocyte antigen (BoLA)-DRB3 was reportedly associated with susceptibility of various phenotypes of infections including bovine leukemia virus-induced lymphoma. However, the association of the remaining genes with various phenotypes has not been clarified due to the complicated genomic structure of the MHC class II region. Thus, in this study, we elucidated the MHC class II genomic structure, including the novel alleles and copy number variations (CNVs). We determined the copy numbers of BOLA-DQA2 (DQA2), BOLA-DQB (DQB2), BOLA-DQA5 (DQA5), BLA-DQB (DQB1), LOC100848815 (DQA1), and BOLA-DRB3 (DRB3) in 127 unrelated Holstein cows by TaqMan copy number assay. The genomes were sequenced using target next-generation sequencing (NGS) based on multiplex polymerase chain reaction. Combining the results of the copy numbers and alleles, we identified the BoLA alleles directly without haplotype estimation. Pairwise linkage disequilibrium (LD) analysis between alleles and genes were performed. The CNVs of DQA2, DQB2, and DQA5 in Holstein cows were detected. The frequency of the whole gene deletion in DQA2, DQB2, and DQA5 was 35.4%, 93.7%, and 93.7%, respectively. After target NGS, we identified 37 alleles in the six genes. Fifteen novel alleles (40.5%) were not registered in the IPD-MHC Database. LD analysis showed strong LD among the DQB2*deletion, DQA5*deletion, and DRB3*27:03 alleles. Our findings will provide important insights into the identification of the BoLA genes associated with various infection-related phenotypes.

Fine Mapping of the Major Histocompatibility Complex Region and Association of the HLA-B*52:01 Allele With Cervical Cancer in Japanese Women

IMPORTANCE

Understanding the genetic contribution of the major histocompatibility complex (MHC) region to the risk of cervical cancer (CC) will help understand how immune responses to infection with human papillomaviruses are associated with CC.

OBJECTIVE

To determine whether the HLA-B*52:01 allele is associated with CC in Japanese women.

DESIGN, SETTING, AND PARTICIPANTS

This was a multicenter genetic association study. Genotype and phenotype data were obtained from BioBank Japan Project. Additional patients with CC were enrolled from the Aichi Cancer Center Research Institute. An MHC fine-mapping study was conducted on CC risk in the Japanese population by applying a human leukocyte antigen (HLA) imputation method to the large-scale CC genome-wide association study data of using the Japanese population-specific HLA reference panel. Participants included 540 women in BioBank Japan Project with CC or 39 829 women without gynecologic diseases, malignant neoplasms, and MHC-related diseases as controls. An additional 168 patients with CC were recruited from Aichi Cancer Center Research Institute. Histopathological subtypes and clinical stages were not considered. Participants with low genotype call rate, closely related participants, and outliers in the principal component analysis were excluded. Data analysis was performed from August 2018 to January 2020.

MAIN OUTCOMES AND MEASURES

Loci within the MHC region associated with CC risk, and the direction and size of association.

RESULTS

A total of 704 CC cases and 39 556 controls were analyzed. All participants were Japanese women with a median (range) age of 67 (18 to 100) years. One of the class I HLA alleles of HLA-B*52:01 was significantly associated with CC risk (odds ratio, 1.60; 95% CI, 1.38-1.86; P = 7.4 × 10-10). Allele frequency spectra of HLA-B*52:01 are heterogeneous among worldwide populations with high frequency in Japanese populations (0.109 in controls), suggesting its population-specific risk associated with CC. The conditional analysis suggested that HLA-B*52:01 could explain most of the MHC risk associated with CC because no other HLA alleles remained significant after conditioning on the HLA-B*52:01. The HLA amino acid residue-based analysis suggested that HLA-B p.Tyr171His located in the peptide-binding groove was associated with the most significant CC risk (odds ratio, 1.47; 95% CI, 1.30-1.66; P = 1.2 × 10-9).

CONCLUSIONS AND RELEVANCE

The results of this study contribute to understanding of the genetic background of CC. The results suggest that immune responses mediated by class I HLA molecules are associated with susceptibility to CC.

An Intronic HCP5 Variant Is Associated With Age of Onset and Susceptibility to Graves Disease in UK and Polish Cohorts

CONTEXT

The genetic background of young-onset Graves disease (GD) remains largely unknown. An intronic variant in human leukocyte antigen (HLA) complex P5 (HCP5) has previously been associated with GD susceptibility and age of onset in a cohort of Polish patients.

OBJECTIVE

We aimed to investigate the association of the HCP5 variant rs3094228 with GD susceptibility and age of onset in a UK cohort and conduct a meta-analysis of UK and Polish data.

DESIGN AND PARTICIPANTS

rs3094228 was genotyped in 469 UK patients with GD using Taqman chemistry. Genotype frequencies were compared with genotypic data available from the Wellcome Trust case-control consortium using logistic regression analysis. To determine whether rs3094228 is independently associated with age of GD onset, the HLA DRB1*0301 tagging variant, rs535777, was also genotyped.

RESULTS

The C allele of rs3094228 was overrepresented in the UK GD cohort compared with controls (P allele=5.08 × 10-9, odds ratio 1.76; [95% confidence interval, 1.46-2.13]). This association was more marked in young-onset GD (<30 years) (P allele=1.70 × 10-10 vs P allele=0.0008). The meta-analysis of UK and Polish data supported the association of the C allele with GD susceptibility (P allele=1.79 × 10-5) and age of onset (P allele=5.63 × 10-8). Haplotype analysis demonstrated that rs3094228 is associated with age of GD onset (P = 2.39 × 10-6) independent of linkage disequilibrium with HLA DRB1*0301.

CONCLUSION

The rs3094228 HCP5 polymorphism is independently associated with GD susceptibility and age of onset in a UK GD cohort. Our findings indicate a potential role of long noncoding ribonucleic acids, including HCP5, in GD pathogenesis, particularly in the younger population.

The complex pattern of genetic associations of leprosy with HLA class I and class II alleles can be reduced to four amino acid positions

Leprosy is a chronic disease caused by Mycobacterium leprae. Worldwide, more than 200,000 new patients are affected by leprosy annually, making it the second most common mycobacterial disease after tuberculosis. The MHC/HLA region has been consistently identified as carrying major leprosy susceptibility variants in different populations at times with inconsistent results. To establish the unambiguous molecular identity of classical HLA class I and class II leprosy susceptibility factors, we applied next-generation sequencing to genotype with high-resolution 11 HLA class I and class II genes in 1,155 individuals from a Vietnamese leprosy case-control sample. HLA alleles belonging to an extended haplotype from HLA-A to HLA-DPB1 were associated with risk to leprosy. This susceptibility signal could be reduced to the HLA-DRB1*10:01~ HLA-DQA1*01:05 alleles which were in complete linkage disequilibrium (LD). In addition, haplotypes containing HLA-DRB3~ HLA-DRB1*12:02 and HLA-C*07:06~ HLA-B*44:03~ HLA-DRB1*07:01 alleles were found as two independent protective factors for leprosy. Moreover, we replicated the previously associated HLA-DRB1*15:01 as leprosy risk factor and HLA-DRB1*04:05~HLA-DQA1*03:03 as protective alleles. When we narrowed the analysis to the single amino acid level, we found that the associations of the HLA alleles were largely captured by four independent amino acids at HLA-DRβ1 positions 57 (D) and 13 (F), HLA-B position 63 (E) and HLA-A position 19 (K). Hence, analyses at the amino acid level circumvented the ambiguity caused by strong LD of leprosy susceptibility HLA alleles and identified four distinct leprosy susceptibility factors.

Despite global efforts to eliminate leprosy over the past 25 years, more than 200,000 new cases are reported annually, and leprosy still represents a major public health problem in endemic regions. Leprosy presents a strong link with the host genetic background. The most significant susceptibility factors are located in the MHC region and likely involve classical HLA genes. However, the molecular identity of the HLA class I/II-leprosy risk factor(s) has been a matter of longstanding scientific dispute. By conducting a comprehensive sequenced-based analysis of HLA class I and class II genes, we are able to provide a unifying view of the complex relationship of leprosy susceptibility and HLA alleles. In addition, we show that four amino acid polymorphisms in HLA-DRβ1, HLA-B and HLA-A are sufficient to explain the majority of leprosy-HLA associations which opens the way for select protein-HLA peptide binding studies.

SNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomics

Genome‐wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA) polymorphisms and their combination as haplotypes. To circumvent the effort and high costs of HLA typing, statistical solutions have been developed to infer HLA alleles from single‐nucleotide polymorphism (SNP) genotyping data. Though HLA imputation methods have been developed, no unified effort has yet been undertaken to share large and diverse imputation models, or to improve methods. By training the HIBAG software on SNP + HLA data generated by the Consortium on Asthma among African‐ancestry Populations in the Americas (CAAPA) to create reference panels, we highlighted the importance of (a) the number of individuals in reference panels, with a twofold increase in accuracy (from 10 to 100 individuals) and (b) the number of SNPs, with a 1.5‐fold increase in accuracy (from 500 to 24,504 SNPs). Results showed improved accuracy with CAAPA compared to the African American models available in HIBAG, highlighting the need for precise population‐matching. The SNP‐HLA Reference Consortium is an international endeavor to gather data, enhance HLA imputation and broaden access to highly accurate imputation models for the immunogenomics community.

The current landscape of psoriasis genetics in 2020

Psoriasis is an immune-mediated disease associated with skin and joint inflammation that affects large proportions of populations worldwide. It is a heritable disease: individuals' genetic backgrounds modulate their susceptibility. In genetics, multiple human leukocyte antigen (HLA) genes are most strongly associated with the risk of psoriasis, especially HLA-C*06:02. In the last 10 years, large-scale genome-wide association studies (GWASs) of psoriasis have been conducted in multiple populations, and these have substantially increased the number of genetic loci associated with psoriasis susceptibility (n > 80). Understanding the genetic background of psoriasis is important for understanding the disease's biology, identifying clinical biomarkers, discovering novel drug targets, and accelerating the journey towards personalized medicine. However, the application of whole-genome and long-read sequencing technology in psoriasis genetic analysis is still developing. Moreover, achieving practical strategies for translating psoriasis risk-associated genetic variants into functional annotations and clinical applications remains challenging. In this review, we detail the current and future landscape of psoriasis genetics and introduce the cutting-edge use of large-scale GWAS data, especially in the Japanese population.

Increasing accuracy of HLA imputation by a population-specific reference panel in a FinnGen biobank cohort

The HLA genes, the most polymorphic genes in the human genome, constitute the strongest single genetic susceptibility factor for autoimmune diseases, transplantation alloimmunity and infections. HLA imputation via statistical inference of alleles based on single-nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with alleles is a powerful first-step screening tool. Due to different LD structures between populations, the accuracy of HLA imputation may benefit from matching the imputation reference with the study population. To evaluate the potential advantage of using population-specific reference in HLA imputation, we constructed an HLA reference panel consisting of 1150 Finns with 5365 major histocompatibility complex region SNPs consistent between genome builds. We evaluated the accuracy of the panel against a European panel in an independent test set of 213 Finnish subjects. We show that the Finnish panel yields a lower imputation error rate (1.24% versus 1.79%). More than 30% of imputation errors occurred in haplotypes enriched in Finland. The frequencies of imputed HLA alleles were highly correlated with clinical-grade HLA allele frequencies and allowed accurate replication of established HLA–disease associations in ∼102 000 biobank participants. The results show that a population-specific reference increases imputation accuracy in a relatively isolated population within Europe and can be successfully applied to biobank-scale genome data collections.

HLA-IMPUTER: an easy to use web application for HLA imputation and association analysis using population-specific reference panels

SUMMARY

HLA allele imputation from SNP genotypes has become increasingly useful, but its accuracy is heavily dependent on the reference panels used. HLA-IMPUTER implements HIBAG algorithm for HLA imputation with different population specific reference panels, including a new Han Chinese reference panel derived from 10 689 samples. We provide a convenient platform for researchers to impute HLA alleles and perform association analysis.

AVAILABILITY AND IMPLEMENTATION

http://wyanglab.org: 3838/RefPanelWebsite/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-wide Association Study Identifies HLA-DPB1 as a Significant Risk Factor for Severe Aplastic Anemia

Severe aplastic anemia (SAA) is a rare disorder characterized by hypoplastic bone marrow and progressive pancytopenia. The etiology of acquired SAA is not understood but is likely related to abnormal immune responses and environmental exposures. We conducted a genome-wide association study of individuals with SAA genetically matched to healthy controls in discovery (359 cases, 1,396 controls) and validation sets (175 cases, 1,059 controls). Combined analyses identified linked SNPs in distinct blocks within the major histocompatibility complex on 6p21. The top SNP encodes p.Met76Val in the P4 binding pocket of the HLA class II gene HLA-DPB1 (rs1042151A>G, odds ratio [OR] 1.75, 95% confidence interval [CI] 1.50-2.03, p = 1.94 × 10-13) and was associated with HLA-DP cell surface expression in healthy individuals (p = 2.04 × 10-6). Phylogenetic analyses indicate that Val76 is not monophyletic and likely occurs in conjunction with different HLA-DP binding groove conformations. Imputation of HLA-DPB1 alleles revealed increased risk of SAA associated with Val76-encoding alleles DPB1∗03:01, (OR 1.66, p = 1.52 × 10-7), DPB1∗10:01 (OR 2.12, p = 0.0003), and DPB1∗01:01 (OR 1.60, p = 0.0008). A second SNP near HLA-B, rs28367832G>A, reached genome-wide significance (OR 1.49, 95% CI 1.22-1.78, p = 7.27 × 10-9) in combined analyses; the association remained significant after excluding cases with clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes (8.6% of cases and 0% of controls). SNPs in the HLA class II gene HLA-DPB1 and possibly class I (HLA-B) are associated with SAA. The replacement of Met76 to Val76 in certain HLA-DPB1 alleles might influence risk of SAA through mechanisms involving DP peptide binding specificity, expression, and/or other factors affecting DP function.

Construction and benchmarking of a multi-ethnic reference panel for the imputation of HLA class I and II alleles

Genotype imputation of the human leukocyte antigen (HLA) region is a cost-effective means to infer classical HLA alleles from inexpensive and dense SNP array data. In the research setting, imputation helps avoid costs for wet lab-based HLA typing and thus renders association analyses of the HLA in large cohorts feasible. Yet, most HLA imputation reference panels target Caucasian ethnicities and multi-ethnic panels are scarce. We compiled a high-quality multi-ethnic reference panel based on genotypes measured with Illumina’s Immunochip genotyping array and HLA types established using a high-resolution next generation sequencing approach. Our reference panel includes more than 1,300 samples from Germany, Malta, China, India, Iran, Japan and Korea and samples of African American ancestry for all classical HLA class I and II alleles including HLA-DRB3/4/5. Applying extensive cross-validation, we benchmarked the imputation using the HLA imputation tool HIBAG, our multi-ethnic reference and an independent, previously published data set compiled of subpopulations of the 1000 Genomes project. We achieved average imputation accuracies higher than 0.924 for the commonly studied HLA-A, -B, -C, -DQB1 and -DRB1 genes across all ethnicities. We investigated allele-specific imputation challenges in regard to geographic origin of the samples using sensitivity and specificity measurements as well as allele frequencies and identified HLA alleles that are challenging to impute for each of the populations separately. In conclusion, our new multi-ethnic reference data set allows for high resolution HLA imputation of genotypes at all classical HLA class I and II genes including the HLA-DRB3/4/5 loci based on diverse ancestry populations.

Correlation between eosinophil count, its genetic background and body mass index: The Nagahama Study

BACKGROUND

Obesity affects the pathogenesis of various chronic diseases, including asthma. Research on correlations between obesity/BMI and eosinophilic inflammation in asthma has yielded contradictory results, which could be partly ascribed to the absence of epidemiological data on the correlations. We aimed to elucidate the correlations between blood eosinophil count, its genetic backgrounds, and BMI in the general population.

METHODS

This community-based Nagahama study in Japan enrolled 9789 inhabitants. We conducted self-reporting questionnaires, lung function tests, and blood tests in the baseline and 5-year follow-up studies. A genome-wide association study (GWAS) was performed in 4650 subjects at the baseline and in 4206 of these at the follow-up to determine single-nucleotide polymorphisms for elevated blood eosinophil counts. We assessed the correlations between BMI and eosinophil counts using a multifaceted approach, including the cluster analysis.

RESULTS

Eosinophil counts positively correlated with BMI, observed upon the interchange of an explanatory variable, except for subjects with the highest quartile of eosinophils (≥200/μL), in whom BMI negatively correlated with eosinophil counts. GWAS and human leukocyte antigen (HLA) imputation identified rs4713354 variant (MDC1 on chromosome 6p21) for elevated eosinophil counts, independent of BMI and IgE. Rs4713354 was accumulated in a cluster characterized by elevated eosinophil counts (mean, 498 ± 178/μL) but normal BMI.

CONCLUSIONS

Epidemiologically, there may be a positive association between blood eosinophil counts and BMI in general, but there was a negative correlation in the population with high eosinophil counts. Factors other than BMI, particularly genetic backgrounds, may contribute to elevated eosinophil counts in such populations.

Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis

Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.

Grimon: graphical interface to visualize multi-omics networks

Summary

Rapid advances in high-throughput sequencing technologies have enabled more efficient acquisition of massive amount of multi-omics data. However, interpretation of the underlying relationships across multi-omics networks has not been fully succeeded, partly due to the lack of effective methods in visualization. To aid interpretation of the results from such multi-omics data, we here present Grimon (Graphical interface to visualize multi-omics networks), an R package that visualizes high-dimensional multi-layered data sets in three-dimensional parallel coordinates. Grimon enables users to intuitively and interactively explore their analyzed data, helping their understanding of multiple inter-layer connections embedded in high-dimensional complex data.

Availability and implementation

Grimon is freely available at https://github.com/mkanai/grimon as an R package with example omics data sets.

Supplementary information

Supplementary data are available at bioinformatics online.

IgG4-related disease in the Japanese population: a genome-wide association study

BACKGROUND

IgG4-related disease is a newly recognised immunopathological entity that includes autoimmune pancreatitis, IgG4-related sialadenitis, and IgG4-related kidney disease. To understand the genetic landscape of IgG4-related disease, we did a genome-wide association study.

METHODS

We did a genome-wide association study of Japanese individuals, initially screening 857 patients with IgG4-related disease at 50 Japanese research institutions and DNA samples from 2082 healthy control participants from the Nagahama Prospective Genome Cohort for the Comprehensive Human Bioscience. From Oct 27, 2008, to July 22, 2014, we enrolled 835 patients and used data from 1789 healthy participants. Only patients with confirmed diagnosis of IgG4-related disease according to the international diagnostic criteria were included. Genotyping was done with the Infinium HumanOmni5Exome, HumanOmni2.5Exome, or HumanOmni2.5 Illumina arrays, and genomic distributions were compared between case and control samples for 958 440 single nucleotide polymorphisms. The HLA region was extensively analysed using imputation of HLA alleles and aminoacid residues. Fine mapping of the FCGR2B region was also done. Associations between clinical manifestations of disease and the genetic variations identified in these two genes were examined.

FINDINGS

We identified the HLA-DRB1 (p=1·1×10-11) and FCGR2B (p=2·0×10-8) regions as susceptibility loci for IgG4-related disease. We also identified crucial aminoacid residues in the β domain of the peptide-binding groove of HLA-DRB1, in which the seventh aminoacid residue showed the strongest association signal with IgG4-related disease (p=1·7×10-14), as has been reported with other autoimmune diseases. rs1340976 in FCGR2B showed an association with increased FCGR2B expression (p=2·7×10-10) and was in weak linkage disequilibrium with rs1050501, a missense variant of FCGR2B previously associated with systemic lupus erythematosus. Furthermore, rs1340976 was associated with the number of swollen organs at diagnosis (p=0·011) and IgG4 concentration at diagnosis (p=0·035).

INTERPRETATION

Two susceptibility loci for IgG4-related disease were identified. Both FCGR2B and HLA loci might have important roles in IgG4-related disease development. Common molecular mechanisms might underlie IgG4-related disease and other immune-related disorders FUNDING: The Japanese Ministry of Health, Labour, and Welfare, the Japanese Agency of Medical Research and Development, and Kyoto University Grant for Top Global University Japan Project.