HLA DNA typing: past, present, and future

25 years of the IPD-IMGT/HLA Database

Twenty-five years ago, in 1998, the HLA Informatics Group of the Anthony Nolan Research Institute released the IMGT/HLA Database. Since this time, this online resource has acted as the repository for the numerous variant sequences of HLA alleles named by the WHO Nomenclature Committee for Factors of the HLA System. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this work. During this time, the technology underlying HLA typing has undergone significant changes. Next generation sequencing (NGS) has superseded previous methodologies of HLA typing and can generate large amounts of high-resolution sequencing data. This has resulted in a drastic increase in the number and complexity of sequences submitted to the database. The challenge for the IPD-IMGT/HLA Database has been to maintain the highest standards of curation, while supporting the core set of tools and functionality to our users with increased numbers of submissions and sequences. Traditional methods of accessing and presenting data have been challenged and new methods utilising new computing technologies have had to be developed to keep pace and support a shifting user demographic.

Frequencies of HLA-B alleles in Indonesian Malay Ethnic

Background

The HLA-B alleles have been used as a marker to predict drug-induced adverse reactions and as a major contributor to hypersensitivity reactions. We examined the feasibility of HLA-B alleles as pharmacogenomic markers of drug-induced hypersensitivity in an Indonesian Malay Ethnic.

Methods

Fifty-eight Indonesian individuals of Malay ethnicity were enrolled in this study. HLA-B alleles were determined using reverse sequence-specific oligonucleotide probe coupled with xMAP technology.

Results

HLA-B*15:02 (15.52%), HLA-B*35:05 (9.48%), and HLA-B*07:05 (7.76%) were frequent alleles in the Indonesian Malay ethnic populations. We discovered at least eight pharmacogenomics markers of drug-induced hypersensitivity: HLA-B*15:02, HLA-B*15:21, HLA-B*13:01, HLA-B*35:05, HLA-B*38:02, HLA-B*51:01, HLA-B*57:01, and HLA-B*58:01. HLA-B*15:02 was in the same serotype group with HLA-B*15:21, which is a B-75 serotype associated with genetic predisposition for carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis. The Indonesian population, represented by Malay, Javanese, and Sundanese ethnicities, was similar to South East Asian, Han Chinese, and Taiwanese populations based on HLA-B*15:02 frequency as the most common allele found in Malay ethnics.

Conclusion

We provided valuable information on the frequency of drug hypersensitivity-associated HLA-B alleles in Indonesian Malay ethnic population, which can improve treatment safety.

Race, ethnicity, ancestry, and aspects that impact HLA data and matching for transplant

Race, ethnicity, and ancestry are terms that are often misinterpreted and/or used interchangeably. There is lack of consensus in the scientific literature on the definition of these terms and insufficient guidelines on the proper classification, collection, and application of this data in the scientific community. However, defining groups for human populations is crucial for multiple healthcare applications and clinical research. Some examples impacted by population classification include HLA matching for stem-cell or solid organ transplant, identifying disease associations and/or adverse drug reactions, defining social determinants of health, understanding diverse representation in research studies, and identifying potential biases. This article describes aspects of race, ethnicity and ancestry information that impact the stem-cell or solid organ transplantation field with particular focus on HLA data collected from donors and recipients by donor registries or transplant centers.

Advancements in HLA Typing Techniques and Their Impact on Transplantation Medicine

HLA typing serves as a standard practice in hematopoietic stem cell transplantation to ensure compatibility between donors and recipients, preventing the occurrence of allograft rejection and graft-versus-host disease. Conventional laboratory methods that have been widely employed in the past few years, including sequence-specific primer PCR and sequencing-based typing (SBT), currently face the risk of becoming obsolete. This risk stems not only from the extensive diversity within HLA genes but also from the rapid advancement of next-generation sequencing and third-generation sequencing technologies. Third-generation sequencing systems like single-molecule real-time (SMRT) sequencing and Oxford Nanopore (ONT) sequencing have the capability to analyze long-read sequences that span entire intronic-exonic regions of HLA genes, effectively addressing challenges related to HLA ambiguity and the phasing of multiple short-read fragments. The growing dominance of these advanced sequencers in HLA typing is expected to solidify further through ongoing refinements, cost reduction, and error rate minimization. This review focuses on hematopoietic stem cell transplantation (HSCT) and explores prospective advancements and application of HLA DNA typing techniques. It explores how the adoption of third-generation sequencing technologies can revolutionize the field by offering improved accuracy, reduced ambiguity, and enhanced assessment of compatibility in HSCT. Embracing these cutting-edge technologies is essential to advancing the success rates and outcomes of hematopoietic stem cell transplantation. This review underscores the importance of staying at the forefront of HLA typing techniques to ensure the best possible outcomes for patients undergoing HSCT.

Integrative HLA typing of tumor and adjacent normal tissue can reveal insights into the tumor immune response

BACKGROUND

The HLA complex is the most polymorphic region of the human genome, and its improved characterization can help us understand the genetics of human disease as well as the interplay between cancer and the immune system. The main function of HLA genes is to recognize "non-self" antigens and to present them on the cell surface to T cells, which instigate an immune response toward infected or transformed cells. While sequence variation in the antigen-binding groove of HLA may modulate the repertoire of immunogenic antigens presented to T cells, alterations in HLA expression can significantly influence the immune response to pathogens and cancer.

METHODS

RNA sequencing was used here to accurately genotype the HLA region and quantify and compare the level of allele-specific HLA expression in tumors and patient-matched adjacent normal tissue. The computational approach utilized in the study types classical and non-classical Class I and Class II HLA alleles from RNA-seq while simultaneously quantifying allele-specific or personalized HLA expression. The strategy also uses RNA-seq data to infer immune cell infiltration into tumors and the corresponding immune cell composition of matched normal tissue, to reveal potential insights related to T cell and NK cell interactions with tumor HLA alleles.

RESULTS

The genotyping method outperforms existing RNA-seq-based HLA typing tools for Class II HLA genotyping. Further, we demonstrate its potential for studying tumor-immune interactions by applying the method to tumor samples from two different subtypes of breast cancer and their matched normal breast tissue controls.

CONCLUSIONS

The integrative RNA-seq-based HLA typing approach described in the study, coupled with HLA expression analysis, neoantigen prediction and immune cell infiltration, may help increase our understanding of the interplay between a patient's tumor and immune system; and provide further insights into the immune mechanisms that determine a positive or negative outcome following treatment with immunotherapy such as checkpoint blockade.

Label-Free and Real-Time Optical Detection of Affinity Binding of the Antibody on Adherent Live Cells

Oblique-incidence reflectivity difference (OIRD) is a novel real-time, label-free, and nondestructive optical detection method and exhibits encouraging application in the detection of antibody/DNA microarrays. In this study, for the first time, an OIRD label-free immunoassay was achieved by using adherent live cells as the probe. The cells were cultured on glass cells, and the affinity binding of antibodies targeted on the HLA class I antigen of the cell surface was detected with an OIRD. The results show that an OIRD is able to detect the binding process of anti-human HLA-A, B, and C antibodies on MDA-MB-231 cells and HUVEC cells. Control experiments and complementary fluorescence analysis confirmed the high detection specificity and good quantitative virtue of the OIRD label-free immunoassay. Label-free OIRD imaging analysis of cell microarrays was further demonstrated successfully, and the underlying optical mechanism was revealed by combining the theoretical modeling. This work explores the use of live cells as probes for an OIRD immunoassay, thus expanding the potential applications of the OIRD in the field of pathological analysis, disease diagnosis, and drug screening, among others.

Imputation-Based HLA Typing with GWAS SNPs

SNP-based imputation approaches for human leukocyte antigen (HLA) typing take advantage of the haplotype structure within the major histocompatibility complex (MHC) region. These methods predict HLA classical alleles using dense SNP genotypes, commonly found on array-based platforms used in genome-wide association studies (GWAS). The analysis of HLA classical alleles can be conducted on current SNP datasets at no additional cost. Here, we describe the workflow of HIBAG, an imputation method with attribute bagging, to infer a sample's HLA classical alleles using SNP data. Two examples are offered to demonstrate the functionality using public HLA and SNP data from the latest release of the 1000 Genomes project: genotype imputation using pre-built classifiers in a GWAS, and model training to create a new prediction model. The GPU implementation facilitates model building, making it hundreds of times faster compared to the single-threaded implementation.

The history and evolution of HLA typing external proficiency testing schemes in UK NEQAS for H&I

The UK National External Quality Assessment Service (NEQAS) provide an external proficiency testing (EPT) service for clinical laboratories. UK NEQAS for Histocompatibility and Immunogenetics (H&I) has been providing EPT schemes for over 45 years and has grown during this time to provide 19 EPT schemes. Accurate human leucocyte antigen (HLA) typing is critical to support safe clinical services, including transplantation, therefore high quality, relevant EPT schemes are required as part of a laboratory's quality assurance. This article reviews the development of the HLA typing EPT schemes, from the first HLA phenotyping scheme in 1975, via the first HLA genotyping scheme in 1992, through to the introduction in 2017 of HLA third field assessment results from next-generation sequencing technology. In addition, the introduction of EPT schemes to cover HLA associated diseases and pharmacogenetic reactions, including HLA-B27, HLA*B*57:01 and HLA-DQ for coeliac disease are discussed. The accuracy of laboratory EPT results for HLA phenotyping are >96% (2018-2022), HLA genotyping >99% (2020-2022), HLA-B27 testing >99% (2018-2022) and B*57:01 testing >99% (2017-2022). However, for HLA genotyping for coeliac disease 22%-46% of laboratories made errors in 2020-2022. On investigation, the high rate of unsatisfactory performance was attributed to laboratories lacking specific knowledge to interpret HLA genotyping results and accurately report HLA types for coeliac disease. A misleading commercial kit insert was also identified. The assessment of scheme results has uncovered several issues which have been addressed with the intention of educating participants and improving clinical services. The UK NEQAS for H&I EPT schemes have evolved over the past four decades to reflect changes in HLA typing technology, laboratory clinical practice and to cover post-analytical interpretative elements of HLA typing.

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.

Detection of Nonsynonymous Single Variants in Human HLA-DRB1 Exon 2 Associated with Renal Transplant Rejection

Background: HLA-DRB1 is the most polymorphic gene in the human leukocyte antigen (HLA) class II, and exon 2 is critical because it encodes antigen-binding sites. This study aimed to detect functional or marker genetic variants of HLA-DRB1 exon 2 in renal transplant recipients (acceptance and rejection) using Sanger sequencing. Methods: This hospital-based case-control study collected samples from two hospitals over seven months. The 60 participants were equally divided into three groups: rejection, acceptance, and control. The target regions were amplified and sequenced by PCR and Sanger sequencing. Several bioinformatics tools have been used to assess the impact of non-synonymous single-nucleotide variants (nsSNVs) on protein function and structure. The sequences data that support the findings of this study with accession numbers (OQ747803-OQ747862) are available in National Center for Biotechnology Information (GenBank database). Results: Seven SNVs were identified, two of which were novel (chr6(GRCh38.p12): 32584356C>A (K41N) and 32584113C>A (R122R)). Three of the seven SNVs were non-synonymous and found in the rejection group (chr6(GRCh38.p12): 32584356C>A (K41N), 32584304A>G (Y59H), and 32584152T>A (R109S)). The nsSNVs had varying effects on protein function, structure, and physicochemical parameters and could play a role in renal transplant rejection. The chr6(GRCh38.p12):32584152T>A variant showed the greatest impact. This is because of its conserved nature, main domain location, and pathogenic effects on protein structure, function, and stability. Finally, no significant markers were identified in the acceptance samples. Conclusion: Pathogenic variants can affect intramolecular/intermolecular interactions of amino acid residues, protein function/structure, and disease risk. HLA typing based on functional SNVs could be a comprehensive, accurate, and low-cost method for covering all HLA genes while shedding light on previously unknown causes in many graft rejection cases.

Validation of a genotyping technique for a surrogate marker of HLA-B∗58:01 for allopurinol-induced Stevens-Johnson syndrome and toxic epidermal necrolysis in the Japanese population

Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS/TEN) are rare but severe cutaneous adverse drug reactions. Certain human leukocyte antigen (HLA) types have been associated with SJS/TEN onset, e.g., HLA-B^∗58:01 with allopurinol-induced SJS/TEN, but HLA typing is time-consuming and expensive; thus, it is not commonly used in clinical situations. In the previous work, we demonstrated that the single-nucleotide polymorphisms (SNP) rs9263726 was in absolute linkage disequilibrium with HLA-B^∗58:01 in the Japanese population, and can be used as a surrogate marker for the HLA. Here, we developed a new genotyping method for the surrogate SNP using the single-stranded tag hybridization chromatographic printed-array strip (STH-PAS) technique and performed an analytical validation. The results of genotyping rs9263726 using STH-PAS correlated well with those obtained using the TaqMan SNP Genotyping Assay for 15 HLA-B^∗58:01-positive and 13 HLA-B^∗58:01-negative patients (analytical sensitivity and specificity were both 100%). Additionally, at least 1.11 ng of genomic DNA was sufficient to digitally and manually detect positive signals on the strip. Robustness studies showed that the annealing temperature (66 °C) was the most important condition related to reliable results. Collectively, we developed an STH-PAS method that can rapidly and easily detect rs9263726 for predicting SJS/TEN onset.

The immunogenetics of COVID-19

The worldwide coronavirus disease 2019 pandemic was sparked by the severe acute respiratory syndrome caused by coronavirus 2 (SARS-CoV-2) that first surfaced in December 2019 (COVID-19). The effects of COVID-19 differ substantially not just between patients individually but also between populations with different ancestries. In humans, the human leukocyte antigen (HLA) system coordinates immune regulation. Since HLA molecules are a major component of antigen-presenting pathway, they play an important role in determining susceptibility to infectious disease. It is likely that differential susceptibility to SARS-CoV-2 infection and/or disease course in COVID-19 in different individuals could be influenced by the variations in the HLA genes which are associated with various immune responses to SARS-CoV-2. A growing number of studies have identified a connection between HLA variation and diverse COVID-19 outcomes. Here, we review research investigating the impact of HLA on individual responses to SARS-CoV-2 infection and/or progression, also discussing the significance of MHC-related immunological patterns and its use in vaccine design.

Recent Advances of Human Leukocyte Antigen (HLA) Typing Technology Based on High-Throughput Sequencing

The major histocompatibility complex (MHC) in humans is a genetic region consisting of cell surface proteins located on the short arm of chromosome 6. This is also known as the human leukocyte antigen (HLA) region. The HLA region consists of genes that exhibit complex genetic polymorphisms, and are extensively involved in immune responses. Each individual has a unique set of HLAs. Donor-recipient HLA allele matching is an important factor for organ transplantation. Therefore, an established rapid and accurate HLA typing technology is instrumental to preventing graft-verses-host disease (GVHD) in organ recipients. As of recent, high-throughput sequencing has allowed for an increase read length and higher accuracy and throughput, thus achieving complete and high-resolution full-length typing. With more advanced nanotechnology used in high-throughput sequencing, HLA typing is more widely used in third-generation single-molecule sequencing. This review article summarizes some of the most widely used sequencing typing platforms and evaluates the latest developments in HLA typing kits and their clinical applications.

Development of an Immortalized Porcine Fibroblast Cell Panel With Different Swine Leukocyte Antigen Genotypes

Immortalized cell lines are valuable resources to expand the molecular characterization of major histocompatibility complex genes and their presented antigens. We generated a panel of immortalized cell lines by transfecting human telomerase reverse transcriptase (hTERT) into primary fibroblast cells prepared from ear, fetal, and lung tissues of 10 pigs from five breeds and successfully cultured them for 30-45 passages. The cell growth characteristic of the immortalized fibroblasts was similar to that of primary fibroblast, which was unable to form colonies on soft agar. The genotypes of major swine leukocyte antigen (SLA) genes, including three classical class I (SLA-1, -2, and -3) and three class II genes (DQB1, DRB1, and DQA), were determined using high-resolution typing. A total of 58 alleles, including a novel allele for SLA-2, were identified. Each cell line was unique. A cell line derived from a National Institutes of Health miniature pig was homozygous across the six major SLA genes. The expression levels of SLA classical class I genes varied among the cell lines and were slightly upregulated in the immortalized compared to the primary cells based on semiquantitative reverse transcription polymerase chain reaction. The immortalized porcine fibroblast cell lines with diverse SLA haplotypes that were developed in this study have potential to be applied in studies regarding the molecular characteristics and genetic structure of SLA genes and epitope-major histocompatibility complex interactions in pigs.

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.

A real-life overview of a hematopoietic cell transplant program throughout a four-year period, including prospective registry, exclusion causes and final donor selection

Traceability of patients who are candidates for Hematopoietic cell transplant (HCT) is crucial to ensure HCT program quality. Continuous knowledge of both a detailed registry from a HCT program and final exclusion causes can contribute to promoting a real-life vision and optimizing patient and donor selection. We analyzed epidemiological data reported in a 4 year-monocentric prospective registry, which included all patients presented as candidates for autologous (Auto) and/or allogeneic (Allo) HCT. A total of 543 patients were considered for HCT: 252 (42.4%) for Allo and 291 (57.6%) for Auto. A total of 98 (38.9%) patients were excluded from AlloHCT due to basal disease progression more commonly (18.2%). Seventy-six (30.2%) patients had an HLA identical sibling, whereas 147 (58.3%) patients had only Haplo. UD research was performed in 106 (42%) cases, significantly more often in myeloid than lymphoid malignancies (57% vs 28.7%, p < 0.001) but 61.3% were finally canceled, due to donor or disease causes in 72.4%. With respect to Auto candidates, a total of 60 (20.6%) patients were finally excluded; progression was the most common cause (12%). Currently, Haplo is the most frequent donor type. The high cancellation rate of UD research should be revised to optimize further donor algorithms.

A Comprehensive Review of HLA and Severe Cutaneous Adverse Drug Reactions: Implication for Clinical Pharmacogenomics and Precision Medicine

Human leukocyte antigen (HLA) encoded by the HLA gene is an important modulator for immune responses and drug hypersensitivity reactions as well. Genetic polymorphisms of HLA vary widely at population level and are responsible for developing severe cutaneous adverse drug reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), maculopapular exanthema (MPE). The associations of different HLA alleles with the risk of drug induced SJS/TEN, DRESS and MPE are strongly supportive for clinical considerations. Prescribing guidelines generated by different national and international working groups for translation of HLA pharmacogenetics into clinical practice are underway and functional in many countries, including Thailand. Cutting edge genomic technologies may accelerate wider adoption of HLA screening in routine clinical settings. There are great opportunities and several challenges as well for effective implementation of HLA genotyping globally in routine clinical practice for the prevention of drug induced SCARs substantially, enforcing precision medicine initiatives.

Identification of the novel allele, HLA-B*44:256, in an individual from West Bengal in Eastern India

Next generation sequencing based HLA typing has led to the identification of a novel allele HLA-B*44:256. The novel allele HLA-B*44:256 differs from B*44:02:01:01 by eight nucleotides in exon 3.

HLA genetic polymorphism in patients with Coronavirus Disease 2019 in Midwestern United States

The experience of individuals with Coronavirus Disease 2019 (COVID‐19) ranges from asymptomatic to life threatening multi‐organ dysfunction. Specific HLA alleles may affect the predisposition to severe COVID‐19 because of their role in presenting viral peptides to launch the adaptive immune response to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). In this population‐based case–control study in the midwestern United States, we performed high‐resolution HLA typing of 234 cases hospitalized for COVID‐19 in the St. Louis metropolitan area and compared their HLA allele frequencies with those of 22,000 matched controls from the National Marrow Donor Program (NMDP). We identified two predisposing alleles, HLA‐DRB1*08:02 in the Hispanic group (OR = 9.0, 95% confidence interval: 2.2–37.9; adjusted p = 0.03) and HLA‐A*30:02 in younger African Americans with ages below the median (OR = 2.2, 1.4–3.6; adjusted p = 0.01), and several candidate alleles with potential associations with COVID‐19 in African American, White, and Hispanic groups. We also detected risk‐associated amino acid residues in the peptide binding grooves of some of these alleles, suggesting the presence of functional associations. These findings support the notion that specific HLA alleles may be protective or predisposing factors to COVID‐19. Future consortium analysis of pooled cases and controls is warranted to validate and extend these findings, and correlation with viral peptide binding studies will provide additional evidence for the functional association between HLA alleles and COVID‐19.

"It's harder for the likes of us": racially minoritised stem cell donation as ethico-racial imperative

How best are we to understand appeals to participate in a biomedical project that are based both on invoking shared racial identity, and on framing engagement as the clear moral course of action? Stem cell donor recruitment, which often focuses on engaging racially minoritised communities, provides useful insight into this question. This article proposes that it is not an essential mutual racial identity between the person asking and the person asked at play. Rather, it is the creative 'doing' of relatedness between people at the scale of race as well as family that coalesces into powerful appeals to participate. Through analysis of ethnographic, documentary and social media data, the paper argues that this work relies at least partly on framing donation as a duty of being part of a racialised community, which I describe here as an ethico-racial imperative, in which both race and responsibility become intertwined to compel participation in the biomedical project of donor registration.

Supplementary Information

The online version contains supplementary material available at 10.1057/s41292-021-00241-9.

Immune system regulation and role of the human leukocyte antigen in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a debilitating condition that adversely affect mental and physical health. Recent studies have increasingly explored the role of the immune system in risk for PTSD and its related symptoms. Dysregulation of the immune system may lead to central nervous system tissue damage and impair learning and memory processes. Individuals with PTSD often have comorbid inflammatory or auto-immune disorders. Evidence shows associations between PTSD and multiple genes that are involved in immune-related or inflammatory pathways. In this review, we will summarize the evidence of immune dysregulation in PTSD, outlining the contributions of distinct cell types, genes, and biological pathways. We use the Human Leukocyte Antigen (HLA) locus to illustrate the contribution of genetic variation to function in different tissues that contribute to PTSD etiology, severity, and comorbidities.

Heater Integrated Lab-on-a-Chip Device for Rapid HLA Alleles Amplification towards Prevention of Drug Hypersensitivity

HLA-B*15:02 screening before administering carbamazepine is recommended to prevent life-threatening hypersensitivity. However, the unavailability of a point-of-care device impedes this screening process. Our research group previously developed a two-step HLA-B*15:02 detection technique utilizing loop-mediated isothermal amplification (LAMP) on the tube, which requires two-stage device development to translate into a portable platform. Here, we report a heater-integrated lab-on-a-chip device for the LAMP amplification, which can rapidly detect HLA-B alleles colorimetrically. A gold-patterned micro-sized heater was integrated into a 3D-printed chip, allowing microfluidic pumping, valving, and incubation. The performance of the chip was tested with color dye. Then LAMP assay was conducted with human genomic DNA samples of known HLA-B genotypes in the LAMP-chip parallel with the tube assay. The LAMP-on-chip results showed a complete match with the LAMP-on-tube assay, demonstrating the detection system's concurrence.

Concurrent typing of over 4000 samples by long-range PCR amplicon-based NGS and rSSO revealed the need to verify NGS typing for HLA allelic dropouts

Hematopoietic stem cell transplantation (HSCT) from HLA-matched donors significantly decreases the risks of graft-rejection and graft-versus-host disease. Long-range PCR- amplicon-based next-generation sequencing (NGS) is increasingly used as a standalone method in clinical laboratories to determine HLA compatibility for HSCT and solid-organ transplantation. We hypothesized that an allelic dropout is a frequent event in the long-range PCR amplicon-based NGS HLA typing method. To test the hypothesis, we typed 4,006 samples concurrently using a commercially available long-range PCR amplicon-based NGS-typing and short exon-specific amplicon-based reverse sequence-specific oligonucleotide (rSSO) methods. The concordance between the NGS and rSSO typing results was 100% at HLA-A, -B, -C, -DRB1, -DRB3, -DRB5, -DQA1, DPA1 loci. However, 4.5% of the samples (179/4006) showed allelic-dropouts at one of the other three loci: HLA-DRB4 (3.9%), HLA-DPB1 (0.4%), and HLA-DQB1*(0.15%). The allelic-dropouts are not associated with specific haplotypes, and some dropouts can be reagent lot-specific. Although DRB1-DRB3/4/5-DQB1 linkages help to diagnose these allelic-dropouts in some cases, the rSSO typing was crucial to identify the dropouts in DQB1 and DPB1 loci. These results uncover the critical limitations of using long-range PCR amplicon-based NGS as a standalone method in clinical histocompatibility laboratories and advocate the need for strategies to diagnose and resolve allelic-dropouts.

In-Vitro Approaches to Predict and Study T-Cell Mediated Hypersensitivity to Drugs

Mitigating the risk of drug hypersensitivity reactions is an important facet of a given pharmaceutical, with poor performance in this area of safety often leading to warnings, restrictions and withdrawals. In the last 50 years, efforts to diagnose, manage, and circumvent these obscure, iatrogenic diseases have resulted in the development of assays at all stages of a drugs lifespan. Indeed, this begins with intelligent lead compound selection/design to minimize the existence of deleterious chemical reactivity through exclusion of ominous structural moieties. Preclinical studies then investigate how compounds interact with biological systems, with emphasis placed on modeling immunological/toxicological liabilities. During clinical use, competent and accurate diagnoses are sought to effectively manage patients with such ailments, and pharmacovigilance datasets can be used for stratification of patient populations in order to optimise safety profiles. Herein, an overview of some of the in-vitro approaches to predict intrinsic immunogenicity of drugs and diagnose culprit drugs in allergic patients after exposure is detailed, with current perspectives and opportunities provided.

HLA-DRB1 Alleles Associated with Lower Leishmaniasis Susceptibility Share Common Amino Acid Polymorphisms and Epitope Binding Repertoires

Susceptibility for leishmaniasis is largely dependent on host genetic and immune factors. Despite the previously described association of human leukocyte antigen (HLA) gene cluster variants as genetic susceptibility factors for leishmaniasis, little is known regarding the mechanisms that underpin these associations. To better understand this underlying functionality, we first collected all known leishmaniasis-associated HLA variants in a thorough literature review. Next, we aligned and compared the protection- and risk-associated HLA-DRB1 allele sequences. This identified several amino acid polymorphisms that distinguish protection- from risk-associated HLA-DRB1 alleles. Subsequently, T cell epitope binding predictions were carried out across these alleles to map the impact of these polymorphisms on the epitope binding repertoires. For these predictions, we used epitopes derived from entire proteomes of multiple Leishmania species. Epitopes binding to protection-associated HLA-DRB1 alleles shared common binding core motifs, mapping to the identified HLA-DRB1 amino acid polymorphisms. These results strongly suggest that HLA polymorphism, resulting in differential antigen presentation, affects the association between HLA and leishmaniasis disease development. Finally, we established a valuable open-access resource of putative epitopes. A set of 14 HLA-unrestricted strong-binding epitopes, conserved across species, was prioritized for further epitope discovery in the search for novel subunit-based vaccines.

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.

Reduced PCR-generated errors from a hybrid capture-based NGS assay for HLA typing

Next generation sequencing (NGS) assays are state of the art for HLA genotyping. To sequence on an Illumina sequencer, the DNA of interest must be enriched, fragmented, and bookended with known oligonucleotide sequences, a process known as library construction. Many HLA genotyping assays enrich the target loci by long-range PCR (LR-PCR), prior to fragmentation. This PCR step has been reported to introduce errors in the DNA to be sequenced, including inaccurate replication of repeated sequences, and the in vitro recombination of alleles encoded on separate chromosomes. An alternative library construction method involves fragmentation of genomic DNA, followed by hybrid-capture (HC) enrichment of target HLA loci. This HC-based method involves PCR, but with far fewer cycles. Consequently, the HC method had significantly fewer PCR-induced errors, including more faithful replication of repeated sequences, and the near elimination of recombinant sequences. These improvements likely produce more accurate NGS sequencing data of HLA loci.

scHLAcount: allele-specific HLA expression from single-cell gene expression data

Summary

Bulk RNA sequencing studies have demonstrated that human leukocyte antigen (HLA) genes may be expressed in a cell type-specific and allele-specific fashion. Single-cell gene expression assays have the potential to further resolve these expression patterns, but currently available methods do not perform allele-specific quantification at the molecule level. Here, we present scHLAcount, a post-processing workflow for single-cell RNA-seq data that computes allele-specific molecule counts of the HLA genes based on a personalized reference constructed from the sample’s HLA genotypes.

Availability and implementation

scHLAcount is available under the MIT license at https://github.com/10XGenomics/scHLAcount.

Supplementary information

Supplementary data are available at Bioinformatics online.

Study on the polymorphisms of HLA-ABCDQB1DRB1 alleles and haplotypes in Hubei Han population of China

The present study aimed to analyse the frequencies of human leukocyte antigen HLA-ABCDQB1 and HLA-DRB1 alleles and haplotypes in a subset of 3,732 Han population from Hubei of China. All samples were typed in the HLA-ABCDQB1 and HLA-DRB1 loci using the sequence-based typing method; subsequently, the HLA polymorphisms were analysed. A total of 47 HLA-A, 89 HLA-B, 43 HLA-C, 49 HLA-DRB1 and 24 HLA-DQB1 alleles were identified in the Hubei Han population. The top three most frequent alleles in the HLA-ABCDQB1 and HLA-DRB1 were A*11:01 (0.2617), A*24:02 (0.1590), A*02:07 (0.1281); B*46:01 (0.1502), B*40:01 (0.1409) and B*58:01 (0.0616); C*01:02 (0.2023), C*07:02 (0.1691) and C*03:04 (0.1175); and DQB1*03:01 (0.2000), DQB1*03:03 (0.1900), DQB1*06:01 (0.1187); DRB1*09:01 (0.1790), DRB1*15:01 (0.1062) and DRB1*12:02 (0.0841), respectively. Meanwhile, the three most frequent two-loci haplotypes were A*02:07-C*01:02 (0.0929), B*46:01-C*01:02 (0.1366) and DQB1*03:03-DRB1*09:01 (0.1766). The three most frequent three-loci haplotypes were A*02:07-B*46:01-C*01:02 (0.0883), B*46:01-DQB1*03:03-DRB1*09:01 (0.0808) and C*01:02-DQB1*03:03-DRB1*09:01 (0.0837). The three most frequent four-loci haplotypes were A*02:07-B*46:01-C*01:02-DQB1*03:03 (0.0494), B*46:01-DRB1*09:01-C*01:02-DQB1*03:03 (0.0729) and A*02:07-B*46:01-DQB1*03:03-DRB1*09:01 (0.0501). The most frequent five-loci haplotype was A*02:07-B*46:01-C*01:02-DQB1*03:03-DRB1*09:01 (0.0487). Heat maps and multiple correspondence analysis based on the frequencies of HLA specificity indicated that the Hubei Han population might be described into Southern Chinese populations. Our results lay a certain foundation for future population studies, disease association studies and donor recruitment strategies.

In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

Easy-HLA: a validated web application suite to reveal the full details of HLA typing

Motivation

The HLA system plays a pivotal role in both clinical applications and immunology research. Typing HLA genes in patient and donor is indeed required in hematopoietic stem cell and solid-organ transplantation, and the histocompatibility complex region exhibits countless genetic associations with immune-related pathologies. Since the discovery of HLA antigens, the HLA system nomenclature and typing methods have constantly evolved, which leads to difficulties in using data generated with older methodologies.

Results

Here, we present Easy-HLA, a web-based software suite designed to facilitate analysis and gain knowledge from HLA typing, regardless of nomenclature or typing method. Easy-HLA implements a computational and statistical method of HLA haplotypes inference based on published reference populations containing over 600 000 haplotypes to upgrade missing or partial HLA information: ‘HLA-Upgrade’ tool infers high-resolution HLA typing and ‘HLA-2-Haplo’ imputes haplotype pairs and provides additional functional annotations (e.g. amino acids and KIR ligands). We validated both tools using two independent cohorts (total n = 2500). For HLA-Upgrade, we reached a prediction accuracy of 92% from low- to high-resolution of European genotypes. We observed a 96% call rate and 76% accuracy with HLA-2-Haplo European haplotype pairs prediction. In conclusion, Easy-HLA tools facilitate large-scale immunogenetic analysis and promotes the multi-faceted HLA expertise beyond allelic associations by providing new functional immunogenomics parameters.

Availability and implementation

Easy-HLA is a web application freely available (free account) at: https://hla.univ-nantes.fr.

Supplementary information

Supplementary data are available at Bioinformatics online.

SOAPTyping: an open-source and cross-platform tool for sequence-based typing for HLA class I and II alleles

Background

The human leukocyte antigen (HLA) gene family plays a key role in the immune response and thus is crucial in many biomedical and clinical settings. Utilizing Sanger sequencing, the golden standard technology for HLA typing enables accurate identification of HLA alleles in high-resolution. However, only the commercial software, such as uTYPE, SBT-Assign, and SBTEngine, and very few open-source tools could be applied to perform HLA typing based on Sanger sequencing.

Results

We developed a user-friendly, cross-platform and open-source desktop application, known as SOAPTyping, for Sanger-based typing in HLA class I and II alleles. SOAPTyping can produce accurate results with a comprehensible protocol and featured functions. Moreover, SOAPTyping supports a more advanced group-specific sequencing primers (GSSP) module to solve the ambiguous typing results. We used SOAPTyping to analyze 36 samples with known HLA typing from the University of California Los Angeles (UCLA) International HLA DNA Exchange platform and 100 anonymous clinical samples, and the HLA typing results from SOAPTyping are identical to the golden results and 5.5 times faster than commercial software uTYPE, which shows the usability of SOAPTyping.

Conclusions

We introduce the SOAPTyping as the first open-source and cross-platform HLA typing software with the capability of producing high-resolution HLA typing predictions from Sanger sequence data.

IPD-IMGT/HLA Database

The IPD-IMGT/HLA Database, http://www.ebi.ac.uk/ipd/imgt/hla/, currently contains over 25 000 allele sequence for 45 genes, which are located within the Major Histocompatibility Complex (MHC) of the human genome. This region is the most polymorphic region of the human genome, and the levels of polymorphism seen exceed most other genes. Some of the genes have several thousand variants and are now termed hyperpolymorphic, rather than just simply polymorphic. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this information, providing the scientific and medical community access to the many variant sequences of this gene system, that are critical for the successful outcome of transplantation. The number of currently known variants, and dramatic increase in the number of new variants being identified has necessitated a dedicated resource with custom tools for curation and publication. The challenge for the database is to continue to provide a highly curated database of sequence variants, while supporting the increased number of submissions and complexity of sequences. In order to do this, traditional methods of accessing and presenting data will be challenged, and new methods will need to be utilized to keep pace with new discoveries.

High-Resolution HLA Typing of HLA-A, -B, -C, -DRB1, and -DQB1 in Kinh Vietnamese by Using Next-Generation Sequencing

Human leukocyte antigen (HLA) genotyping displays the particular characteristics of HLA alleles and haplotype frequencies in each population. Although it is considered the current gold standard for HLA typing, high-resolution sequence-based HLA typing is currently unavailable in Kinh Vietnamese populations. In this study, high-resolution sequence-based HLA typing (3-field) was performed using an amplicon-based next-generation sequencing platform to identify the HLA-A, -B, -C, -DRB1, and -DQB1 alleles of 101 unrelated healthy Kinh Vietnamese individuals from southern Vietnam. A total of 28 HLA-A, 41 HLA-B, 21 HLA-C, 26 HLA-DRB1, and 25 HLA-DQB1 alleles were identified. The most frequently occurring HLA alleles were A^∗11:01:01, B^∗15:02:01, C^∗07:02:01, DRB1^∗12:02:01, and DQB1^∗03:01:01. Haplotype calculation showed that A^∗29:01:01∼B^∗07:05:01, DRB1^∗12:02:01∼DQB1^∗3:01:01, A^∗29:01:01∼C^∗15:05:02∼B^∗07:05:01, A^∗33:03:01∼B^∗58:01:01∼DRB1^∗03:01:01, and A^∗29:01:01∼C^∗15:05:02∼B^∗07:05:01∼DRB1^∗10:01:01∼DQB1^∗05:01:01 were the most common haplotypes in the southern Kinh Vietnamese population. Allele distribution and haplotype analyses demonstrated that the Vietnamese population shares HLA features with South-East Asians but retains unique characteristics. Data from this study will be potentially applicable in medicine and anthropology.

Performance of a multiplexed amplicon-based next-generation sequencing assay for HLA typing

BACKGROUND

Next-generation sequencing (NGS) has enabled efficient high-resolution typing of human leukocyte antigen (HLA) genes with minimal ambiguity. Most commercially available assays amplify individual or subgroup of HLA genes by long-range PCR followed by library preparation and sequencing. The AllType assay simplifies the workflow by amplifying 11 transplant-relevant HLA genes in one PCR reaction. Here, we report the performance of this unique workflow evaluated using 218 genetically diverse samples.

METHODS

Five whole genes (HLA-A/B/C/DQA1/DPA1) and six near-whole genes (HLA-DRB1/DRB345/DQB1/DPB1; excluding exon 1 and part of intron 1) were amplified in a multiplexed, long-range PCR. Manual library preparation was performed per manufacturer's protocol, followed by template preparation and chip loading on the Ion Chef, and sequencing on the Ion S5 sequencer. Pre-specified rules for quality control and repeat testing were followed; technologists were blinded to the reference results. The concordance between AllType and reference results was determined at 2-field resolution. We also describe the ranges of input DNA and library concentrations, read number per sample and per locus, and key health metrics in relation to typing results.

RESULTS

The concordance rates were 98.6%, 99.8% and 99.9% at the sample (n = 218), genotype (n = 1688), and allele (n = 3376) levels, respectively. Three genotypes were discordant, all of which shared the same G group typing results with the reference. Most ambiguous genotypes (116 out of 144, 80.6%) were due to the lack of exon 1 and intron 1 coverage for HLA-DRB1/DRB345/DQB1/DPB1 genes. A broad range of input DNA concentrations and library concentrations were tolerated. Per sample read numbers were adequate for accurate genotyping. Per locus read numbers showed some inter-lot variations, and a trend toward improved inter-locus balance was observed with later lots of reagents.

CONCLUSION

The AllType assay on the Ion Chef/Ion S5 platform offers a robust and efficient workflow for clinical HLA typing at the 2-field resolution. The multiplex PCR strategy simplifies the laboratory procedure without compromising the typing accuracy.

Long-Read Nanopore Sequencing Validated for Human Leukocyte Antigen Class I Typing in Routine Diagnostics

Matching of human leukocyte antigen (HLA) gene polymorphisms by high-resolution DNA sequence analysis is the gold standard for determining compatibility between patient and donor for hematopoietic stem cell transplantation. Single-molecule sequencing (PacBio or MinION) is a newest (third) generation sequencing approach. MinION is a nanopore sequencing platform, which provides long targeted DNA sequences. The long reads provide unambiguous phasing, but the initial high error profile prevented its use in high-impact applications, such as HLA typing for HLA matching of donor and recipient in the transplantation setting. Ongoing developments on instrumentation and basecalling software have improved the per-base accuracy of 1D² nanopore reads tremendously. In the current study, two validation panels of samples covering 70 of the 71 known HLA class I allele groups were used to compare third field sequences obtained by MinION, with Sanger sequence-based typing showing a 100% concordance between both data sets. In addition, the first validation panel was used to set the acceptance criteria for the use of MinION in a routine setting. The acceptance criteria were subsequently confirmed with the second validation panel. In summary, the present study describes validation and implementation of nanopore sequencing HLA class I typing method and illustrates that nanopore sequencing technology has advanced to a point where it can be used in routine diagnostics with high accuracy.

Policy Challenges for Organ Allocation in an Era of "Precision Medicine"

There is increasing interest in the use of precision medicine tools and evidence-based outcome measures for donor-recipient matching to optimize transplant outcomes. Although the shift toward greater precision can provide health and resource benefits, it may be perceived as conflicting with both established equity-focused organ allocation norms and the legal and ethical obligations of health care providers and related institutions. With increasing evidence that various forms of human leukocyte antigen (HLA) mismatch and/or prognostic biomarkers can affect outcomes, the tension between maximizing utility and ensuring equity seems likely to intensify. In Canada, health care providers are generally required by law to put the interests of their patient, such as access to an organ, above the needs of the health care system and other patients. In addition, transplantation right of access lawsuits, which have been successful in the past, could affect the implementation of precision approaches. These legal tensions could be further heightened by media representations, which have historically favored strong rights of access. When implementing new precision technologies in organ allocation, there will be a recurrent need for policymakers to revisit the balance of equity and utility and to assess how to craft rules that reflect our society’s conception of a fair allocation system.

A laboratory practice that uses the polymerase chain reaction-sequence specific priming technique to rapidly screen for HLA-DR2 allotype from germline DNA in immunology course for undergraduate medical students

In this article, we describe an in-house polymerase chain reaction-sequence specific priming (PCR-SSP) assay designed for undergraduate medical students as part of the experimental pathogen biology and immunology (EPBI) course. It screens human leukocyte antigen (HLA)-DR2 allotype from genomic DNA samples using a rapid and single-tube PCR technique, yielding definitive typing result without conventional post-amplification step like probing or Sanger sequencing. This laboratory exercise offers the undergraduate medical students an opportunity to learn about current molecular biology techniques in HLA genotyping with limited effort and cost, in addition to a better understanding of concepts presented in the classroom lectures. Upon completing this experiment module, the students show statistically significant improvement in several key indexes, such as the knowledge about the mainstream HLA DNA typing techniques, awareness of the relevance of this knowledge for their future scientific research, immunogenetics-related basic laboratory skills they acquire, and interest and desire for mastering this assay (all p < .05). This easy to implement set of experiments is composed of a two-session lab module occupying eight teaching hours, and has been run successfully in our laboratory.

A blueprint for electronic utilization of ambiguous molecular HLA typing data in organ allocation systems and virtual crossmatch

Virtual crossmatch (VXM) compares a transplant candidate's unacceptable antigens to the HLA typing of the donor before an organ offer is accepted and, in selected cases, supplant a prospective physical crossmatch. However, deceased donor typing can be ambiguous, leading to uncertainty in compatibility prediction. We have developed a prototype web application that utilizes ambiguous HLA molecular typing data to predict which unacceptable antigens are present in the donor HLA genotype as donor-specific antibodies (DSA). The application compares a candidate's listed unacceptable antigens to computed probabilities of all possible two-field donor HLA alleles and UNOS antigens. The VIrtual CrossmaTch for mOleculaR HLA typing (VICTOR) tool can be accessed at http://www.transplanttoolbox.org/victor. We reanalyzed historical VXM cases where a transplant center's manual interpretation of molecular typing results influenced offer evaluation. We found that interpretation of ambiguous donor molecular typing data using imputation could one day influence VXM decisions if the DSA predictions were rigorously validated. Standardized interpretation of molecular typing data, if applied to the match run, could also change which offers are made. HLA typing ambiguity has been an underappreciated source of immunological risk in organ transplantation. The VICTOR tool can serve as a testbed for development of allocation policies with the aim of decreasing offers refused due to HLA incompatibility.

Human Leukocyte Antigen alleles as an aid to STR in complex forensic DNA samples

Human biological samples with multiple contributors remain one of the most challenging aspects of DNA typing within a forensic science context. With the increasing sensitivity of commercially available kits allowing detection of low template DNA, complex mixtures are now a standard component of forensic DNA evidence. Over the years, various methods and techniques have been developed to try to resolve the issue of mixed profiles. However, forensic DNA analysis has relied on the same markers to generate DNA profiles for the past 30 years causing considerable challenges in the deconvolution of complex mixed samples. The future of resolving complicated DNA mixtures may rely on utilising markers that have been previously applied to gene typing of non-forensic relevance. With Massively Parallel Sequencing (MPS), techniques becoming more popular and accessible even epigenetic markers have become a source of interest for forensic scientists. The aim of this review is to consider the potential of alleles from the Human Leukocyte Antigen (HLA) complex as effective forensic markers. While Massively Parallel Sequencing of HLA is routinely used in clinical laboratories in fields such as transplantation, pharmacology or population studies, there have not been any studies testing its suitability for forensic casework samples.

Immunogenomics of Colorectal Tumors: Facts and Hypotheses on an Evolving Saga

Immunotherapy with immune checkpoint inhibitors is an approved treatment option for a subpopulation of patients with colorectal cancers that display microsatellite instability. However, not all individuals within this subgroup respond to immunotherapy, and molecular biomarkers for effective patient stratification are still lacking. In this opinion article, we provide an overview of the different biological parameters that contribute to rendering colorectal cancers with microsatellite instability potentially sensitive to immunotherapy. We critically discuss the reasons why such parameters have limited predictive value and the implications therein. We also consider that a more informed knowledge of response determinants in this tumor subtype could help understand the mechanisms of immunotherapy resistance in microsatellite stable tumors. We conclude that the dynamic nature of the interactions between cancer and immune cells complicates conventional biomarker development and argue that a new generation of adaptive metrics, borrowed from evolutionary genetics, may improve the effectiveness and reliability of clinical decision making.

Indonesians Human Leukocyte Antigen (HLA) Distributions and Correlations with Global Diseases

In Human, Major Histocompatibility Complex known as Human Leukocyte Antigen (HLA). The HLA grouped into three subclasses regions: the class I region, the class II region, and the class III region. There are thousands of polymorphic HLAs, many of them are proven to have correlations with diseases. Indonesia consists of diverse ethnicity people and populations. It carries a unique genetic diversity between one and another geographical positions. This paper aims to extract Indonesians HLA allele data, mapping the data, and correlating them with global diseases. From the study, it is found that global diseases, like Crohn's disease, rheumatoid arthritis, Graves' disease, gelatin allergy, T1D, HIV, systemic lupus erythematosus, juvenile chronic arthritis, and Mycobacterial disease (tuberculosis and leprosy) suspected associated with the Indonesian HLA profiles.

Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping

The advent of next generation sequencing (NGS) has altered the face of genotyping the human leukocyte antigen (HLA) system in clinical, stem cell donor registry, and research contexts. NGS has led to a dramatically increased sequencing throughput at high accuracy, while being more time and cost efficient than precursor technologies. This has led to a broader and deeper profiling of the key genes in the human immunogenetic make-up. The rapid evolution of sequencing technologies is evidenced by the development of varied short-read sequencing platforms with differing read lengths and sequencing capacities to long-read sequencing platforms capable of profiling full genes without fragmentation. Concomitantly, there has been development of a diverse set of computational analyses and software tools developed to deal with the various strengths and limitations of the sequencing data generated by the different sequencing platforms. This review surveys the different modalities involved in generating NGS HLA profiling sequence data. It systematically describes various computational approaches that have been developed to achieve HLA genotyping to different degrees of resolution. At each stage, this review enumerates the drawbacks and advantages of each of the platforms and analysis approaches, thus providing a comprehensive picture of the current state of HLA genotyping technologies.

Using next-generation sequencing for characterising HLA-DRB1 and DQB1 loci in a cohort of Colombian women

The Colombian population is characterised by a high genetic diversity, secondary to the ethnic mixture arising from colonisation. Unfortunately, few reports are available regarding HLA-DRB1 and DQB1 diversity in Colombia to date. HLA-DRB1 and DQB1 diversity was identified in this study using next-generating sequencing (NGS) on a cohort of Colombian women. Cervical samples taken from 276 women were used for typing DRB1 and DQB1 loci by Illumina MiSeq. Allele and haplotype frequencies were calculated using an expectation-maximisation algorithm. Hardy-Weinberg Equilibrium and linkage disequilibrium (LD) between loci were evaluated. Forty-seven DRB1 alleles and 14 DQB1 alleles were identified. DRB1*04:07:01G and DQB1*03:02:01G alleles occurred most frequently in the target population. Significant LD was found in 44 out of the 144 identified haplotypes, within which DRB1*04:07:01G-DQB1*03:02:01G occurred most frequently (6.56%). The alleles and haplotypes found with NGS agreed with that found in previous reports involving lower resolution for the Colombian population, and greater genetic variability was found, especially concerning DRB1. Comparing allele and haplotype frequency distribution in the target population to that of other populations denoted HLA system intra- and inter-population diversity.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

HLA Class I Expression Changes in Different Types of Cultured Parathyroid Cells

OBJECTIVES

Tissue-specific immunogenicity can be characterized by the determination of human leukocyte antigens (HLA). Parathyroid hyperplasia tissue cells are presumed to have the ability to lose HLA class I expression profile during cultivation, whereas healthy parathyroid cells are presumed to already express HLA class I molecules at low levels. However, there are conflicting results about the expression of HLA class I antigens. In this study, our aim was to evaluate different patterns of HLA class I expression in different parathyroid tissue cells.

MATERIALS AND METHODS

Parathyroid tissue cells were isolated enzymatically and cultured in vitro. Expression of HLA class I (HLA-A, HLA-B, HLA-C) mRNA and protein levels were studied in 7 parathyroid adenomas and 9 parathyroid hyperplasia tissue samples by reverse transcriptase-polymerase chain reaction and Western blot analyses.

RESULTS

HLA-A protein expression remained stable in parathyroid adenoma and hyperplasia tissue, but HLA-A mRNA expression decreased in adenoma tissue. In parathyroid hyperplasia tissue, HLA-B protein expression remained stable, although mRNA expres-sion levels decreased during cultivation. HLA-C mRNA expression was steady in parathyroid adenoma yet significantly decreased in hyperplasia tissue samples. HLA-C protein expression levels were below 30 pg for both types of parathyroid tissue during cultivation.

CONCLUSIONS

HLA class I expression levels of para-thyroid hyperplasia and adenoma tissue were not found to be similar. Parathyroid hyperplasia tissue is the donor tissue for the treatment of permanent hypoparathyroidism. Therefore, expression patterns of HLA class I are directly relevant to the transplant process. In particular, the HLA region is highly polymorphic, and, as a consequence of this, heterogeneous correlations among HLA-A, HLA-B, and HLA-C expression patterns of parathyroid tissue should be evaluated in detail before transplant for future studies.

HLA-A, -B, -DRB1 Alleles as Genetic Predictive Factors for Dengue Disease: A Systematic Review and Meta-Analysis

Dengue virus infection (DEN) is one of the most prevalent arbovirus diseases in the tropical and subtropical areas. Some human leukocyte antigen (HLA) alleles have been reported to be a protective or risk factor to DEN. Due to the limited sample sizes and regional limitations, the results of individual studies were various. This meta-analysis aimed at investigating the relationship between HLA alleles and dengue disease. Relevant studies of the relationship between HLA and dengue disease were searched through PubMed, Embase, Web of science, and Cochrane databases. Subgroups according to ethnicity or sub-alleles and sensitivity analysis were used to explore the potential source of heterogeneity, which was performed to confirm the findings. The relationships between HLA and dengue disease were defined by odds ratios (ORs) with a 95% confidence interval (CI). Fourteen studies were finally confirmed. Results indicated that A*0203 (OR = 2.19, 95% CI = 1.30-3.69) and A*24 in the Asian group (OR = 1.44, 95% CI = 1.21-1.71) were positively associated with an increased risk of DEN when compared with normal controls. A*33 (OR = 0.49, 95% CI = 0.34-0.69) in Southeast Asia was negatively associated with DEN when compared with normal controls, suggesting a protective role against DEN. In addition, DRB1*11 (OR = 4.10, 95% CI = 1.23-13.69) was positively associated with severe dengue (SD) when compared with dengue fever, whereas DRB1*03 (OR = 0.48, 95% CI = 0.28-0.82) and DRB1*09 (OR = 0.73, 95% CI = 0.55-0.96) were negatively associated with SD when compared with normal controls. The meta-analysis confirmed that HLA-A*0203, A*24, A*33, DRB1*03, DRB1*09, and DRB1*11 have significantly affected dengue disease, and the associations are related to race and regions.