Identification of the new allele HLA-C*04:01:01:186 in a Greek individual using next generation sequencing.

The newly discovered HLA-C*04:01:01:186 allele differs from HLA-C*04:01:01:01 by a single nucleotide substitution in intron 3.

Identification of the new allele HLA-A*24:632 in a Greek individual using next generation sequencing.

The HLA-Α*24:632 allele differs from HLA-A*24:02:01:01 by a single nucleotide substitution in exon 2.

High-resolution HLA genotyping improves PIRCHE-II assessment of molecular mismatching in kidney transplantation.

HLA matching in solid organ transplant is performed with the aim of assessing immunologic compatibility in order to avoid hyperacute rejection and assess the risk of future rejection events. Molecular mismatch algorithms are intended to improve granularity in histocompatibility assessment and risk stratification. PIRCHE-II uses HLA genotyping to predict indirectly presented mismatched donor HLA peptides, though most clinical validation studies rely on imputing high resolution (HR) genotypes from low resolution (LR) typing data. We hypothesized that use of bona fide HR typing could overcome limitations in imputation, improving accuracy and predictive ability for donor-specific antibody development and acute rejection. We performed a retrospective analysis of adult and pediatric kidney transplant donor/recipient pairs (N = 419) with HR typing and compared the use of imputed LR genotyping verses HR genotyping for PIRCHE-II analysis and outcomes. Imputation success was highly dependent on the reference population used, as using historic Caucasian reference populations resulted in 10 % of pairs with unsuccessful imputation while multiethnic reference populations improved successful imputation with only 1 % unable to be imputed. Comparing PIRCHE-II analysis with HR and LR genotyping produced notably different results, with 20 % of patients discrepantly classified to immunologic risk groups. These data emphasize the importance of using multiethnic reference panels when performing imputation and indicate HR HLA genotyping has clinically meaningful benefit for PIRCHE-II analysis compared to imputed LR typing.

Updates in SJS/TEN: collaboration, innovation, and community.

Stevens-Johnson Syndrome/Toxic Epidermal Necrolysis (SJS/TEN) is a predominantly drug-induced disease, with a mortality rate of 15-20%, that engages the expertise of multiple disciplines: dermatology, allergy, immunology, clinical pharmacology, burn surgery, ophthalmology, urogynecology, and psychiatry. SJS/TEN has an incidence of 1-5/million persons per year in the United States, with even higher rates globally. One of the challenges of SJS/TEN has been developing the research infrastructure and coordination to answer questions capable of transforming clinical care and leading to improved patient outcomes. SJS/TEN 2021, the third research meeting of its kind, was held as a virtual meeting on August 28-29, 2021. The meeting brought together 428 international scientists, in addition to a community of 140 SJS/TEN survivors and family members. The goal of the meeting was to brainstorm strategies to support the continued growth of an international SJS/TEN research network, bridging science and the community. The community workshop section of the meeting focused on eight primary themes: mental health, eye care, SJS/TEN in children, non-drug induced SJS/TEN, long-term health complications, new advances in mechanisms and basic science, managing long-term scarring, considerations for skin of color, and COVID-19 vaccines. The meeting featured several important updates and identified areas of unmet research and clinical need that will be highlighted in this white paper.

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data.

BACKGROUND: The Human Leukocyte Antigen (HLA) genes are a group of highly polymorphic genes that are located in the Major Histocompatibility Complex (MHC) region on chromosome 6. The HLA genotype affects the presentability of tumour antigens to the immune system. While knowledge of these genotypes is of utmost importance to study differences in immune responses between cancer patients, gold standard, PCR-derived genotypes are rarely available in large Next Generation Sequencing (NGS) datasets. Therefore, a variety of methods for in silico NGS-based HLA genotyping have been developed, bypassing the need to determine these genotypes with separate experiments. However, there is currently no consensus on the best performing tool. RESULTS: We evaluated 13 MHC class I and/or class II HLA callers that are currently available for free academic use and run on either Whole Exome Sequencing (WES) or RNA sequencing data. Computational resource requirements were highly variable between these tools. Three orthogonal approaches were used to evaluate the accuracy on several large publicly available datasets: a direct benchmark using PCR-derived gold standard HLA calls, a correlation analysis with population-based allele frequencies and an analysis of the concordance between the different tools. The highest MHC-I calling accuracies were found for Optitype (98.0%) and arcasHLA (99.4%) on WES and RNA sequencing data respectively, while for MHC-II HLA-HD was the most accurate tool for both data types (96.2% and 99.4% on WES and RNA data respectively). CONCLUSION: The optimal strategy for HLA genotyping from NGS data depends on the availability of either WES or RNA data, the size of the dataset and the available computational resources. If sufficient resources are available, we recommend Optitype and HLA-HD for MHC-I and MHC-II genotype calling respectively.

Benchmarking of 5 algorithms for high-resolution genotyping of human leukocyte antigen class I genes from blood and tissue samples.

Background: Specific alterations in human leukocyte antigen class I (HLA-I) loci are associated with clinical outcomes for immune checkpoint inhibitors, which increase the clinical relevance of accurate high-resolution HLA genotyping in immuno-oncology applications. Numerous algorithms have been developed for high- to full-resolution HLA genotyping by next-generation sequencing (NGS) data; however, Sanger sequencing-based typing (SBT) remains the gold standard. With the increasing use of NGS for clinical oncology, it is important to identify the computational tool with comparable performance as the gold standard. This study aimed to benchmark 5 algorithms against SBT for the high-resolution typing of classical HLA-I genes for targeted NGS data from blood and tissue samples. Methods: Paired white blood cell (WBC), plasma, and tissue deoxyribonucleic acid (DNA) samples derived from 22 cancer patients with known HLA genotypes were sequenced using a panel of all the following exons of classical HLA-I genes: HLA-A, HLA-B, and HLA-C. NGS-based genotypes were generated by the 5 different algorithms, including HLA-HD, HLAscan, OptiType, Polysolver, and xHLA. Accuracy was defined as the concordance between the SBT and NGS-based algorithms. Accuracy was computed as the fraction of all the alleles with concordant genotype using the SBT and any of the algorithm over the total number of alleles. Results: In relation to the WBC, plasma, and tissue samples, all 5 algorithms were highly accurate at low-resolution HLA-I genotyping, but had more varied accuracy at high-resolution HLA-I genotyping, particularly in HLA-A. The in-silico analyses revealed that high-resolution genotyping by all 5 algorithms achieved approximately 90% accuracy at sequencing depths of 6,000× - 100× for the WBC samples, at 6,000× - 700× for the plasma samples, and at 1,000× - 100× for the tissue samples. Among the 5 algorithms, HLA-HD was consistently accurate at high-resolution HLA-I genotyping, and had an accuracy of 93.9% for the WBC samples, 87.9% for the plasma samples, and 94.2% for tissue samples even at a 50× sequencing depth. Conclusions: We found that HLA-HD was an accurate algorithm for the high-resolution genotyping of classical HLA-I genes sequenced by our targeted panel, particularly at a sequencing depth ≥300× for blood and tissue samples.

Fixed drug eruption in a patient of HLA-B*58:01 negative after allopurinol administration: A case report.

WHAT IS KNOWN AND OBJECTIVE: Allopurinol is widely used for hyperuricemia and gouty arthritis, but is associated with cutaneous adverse drug reactions (CADRs). HLA-B*58:01 is a highly specific and effective genetic marker for the detection of allopurinol-induced CADRs, especially for Asian descents. CASE SUMMARY: A 60-year-old Chinese Han male patient took allopurinol for lowering uric acid after the negative result from HLA-B*58:01 testing. Then, he experienced episodes of well-demarcated pruritic erythematous patches on the whole body that developed into blisters and pustular eruption. Fixed drug eruption (FDE) was diagnosed by skin biopsy and improved with withdrawal and hormone treatments. WHAT IS NEW AND CONCLUSION: It should be kept in mind that cutaneous drug eruption might occur after allopurinol administration in Asians of HLA-B*58:01 negative. Awareness among medical practitioners about FDE can lead to correct diagnosis, treatment and decreased damage as well as lower therapeutic costs.

Association of High-Affinity Autoantibodies With Type 1 Diabetes High-Risk HLA Haplotypes.

OBJECTIVE: Electrochemiluminescence (ECL) assays are high-affinity autoantibody (Ab) tests that are more specific than Abs detected by traditional radiobinding assays (RBA) for risk screening and prediction of progression to type 1 diabetes. We sought to characterize the association of high-risk human leukocyte antigen (HLA) haplotypes and genotypes with ECL positivity and levels in relatives of individuals with type 1 diabetes. METHODS: We analyzed 602 participants from the TrialNet Pathway to Prevention Study who were positive for at least 1 RBA diabetes-related Ab [glutamic acid decarboxylase autoantibodies (GADA) or insulin autoantibodies (IAA)] and for whom ECL and HLA data were available. ECL and RBA Ab levels were converted to SD units away from mean (z-scores) for analyses. RESULTS: Mean age at initial visit was 19.4 ± 13.7 years; 344 (57.1%) were female and 104 (17.3%) carried the high-risk HLA-DR3/4*0302 genotype. At initial visit 424/602 (70.4%) participants were positive for either ECL-GADA or ECL-IAA, and 178/602 (29.6%) were ECL negative. ECL and RBA-GADA positivity were associated with both HLA-DR3 and DR4 haplotypes (all Ps < 0.05), while ECL and RBA-GADA z-score titers were higher in participants with HLA-DR3 haplotypes only (both Ps < 0.001). ECL-IAA (but not RBA-IAA) positivity was associated with the HLA-DR4 haplotype (P < 0.05). CONCLUSIONS: ECL-GADA positivity is associated with the HLA-DR3 and HLA-DR4 haplotypes and levels are associated with the HLA-DR3 haplotype. ECL-IAA positivity is associated with HLA-DR4 haplotype. These studies further contribute to the understanding of genetic risk and islet autoimmunity endotypes in type 1 diabetes.

Donor HLA genotyping of ex vivo expanded urine cells from kidney transplant recipients.

Antibody-mediated rejection (AMR) induced by donor-specific anti-HLA antibodies (DSA) remains a major cause of long-term graft loss after kidney transplantation. Currently, the presence of DSA cannot always be determined at a specific allele level, because existing donor HLA typing is low resolution and often incomplete, lacking HLA-DP, and occasionally HLA-C and HLA-DQ information and historical donor DNA samples are not available for HLA retyping. Here we present a novel, non-invasive technique for obtaining donor DNA from selectively expanded donor cells from urine of renal transplant recipients. Urine-derived cells were successfully expanded ex vivo from 31 of 32 enrolled renal transplant recipients, and with DNA obtained from these cells, donor HLA typing was unambiguously determined for HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1 and -DPB1 loci by next-generation sequencing. Our results showed 100% concordance of HLA typing data between donor peripheral blood and recipient urine-derived cells. In comparison, HLA typing showed that DNA derived from urine sediments mainly contained recipient-derived DNA. We also present the successful application of our novel technique in a clinical case of AMR in a renal transplant recipient. Urine-derived donor cells can be isolated from kidney transplant recipients and serve as a suitable source of donor material for reliable high-resolution HLA genotyping. Thus, this approach can aid the assessment of DSA specificity to support the diagnosis of AMR as well as the evaluation of treatment efficacy in kidney transplant recipients when complete donor HLA information and donor DNA are unavailable.

High-resolution HLA genotyping identifies alleles associated with severe COVID-19: A preliminary study from India.

INTRODUCTION: Human leukocyte antigen (HLA) variability has been demonstrated to be associated with susceptibility/severity of COVID-19. High-resolution HLA genotyping to identify alleles associated with severe COVID-19 in an Indian cohort was performed. METHODS: Quantitative reverse-transcription polymerase chain reaction-confirmed SARS-CoV-2-positive patients with mild/moderate/severe disease (n = 54) and asymptomatic (n = 42) were recruited and genotyped for 11-HLA loci on MiSeq using NGSgo®-MX11-3 and analyzed (NGSengine; GenDx). RESULTS: A significant difference in alleles between the groups was identified for HLA-C*04:01:01:01, HLA-DRB5*01:01:01:02, HLA-DQA1*03:01:01:01, HLA-DPB1*04:01:01:41, and HLA-DPA1*01:03:01:02. Alleles namely, HLA-C*04:01:01:01 (OR: 5.71; 95% CI: 1.2-27.14; p = .02), HLA-DRB5*01:01:01:02 (OR: 2.94; 95% CI: 1.1-7.84; p = .03), DQA1*03:01:01:01 (OR: 22.47; 95% CI: 1.28-393.5; p = .03), HLA-DPB1*04:01:01:41 (OR: 9.44; 95% CI: 0.5-175.81; p = .13), and HLA-DPA1*01:03:01:02 (OR: 8.27; 95% CI: 2.26-30.21; p = .001) were associated with severe COVID-19. CONCLUSION: Genotyping for these alleles will enable identification of individuals at risk of severe disease and stratification for preferential vaccination.

Targeted RNA-Based Oxford Nanopore Sequencing for Typing 12 Classical HLA Genes.

Identification of human leukocyte antigen (HLA) alleles from next-generation sequencing (NGS) data is challenging because of the high polymorphism and mosaic nature of HLA genes. Owing to the complex nature of HLA genes and consequent challenges in allele assignment, Oxford Nanopore Technologies' (ONT) single-molecule sequencing technology has been of great interest due to its fitness for sequencing long reads. In addition to the read length, ONT's advantages are its portability and possibility for a rapid real-time sequencing, which enables a simultaneous data analysis. Here, we describe a targeted RNA-based method for HLA typing using ONT sequencing and SeqNext-HLA SeqPilot software (JSI Medical Systems GmbH). Twelve classical HLA genes were enriched from cDNA of 50 individuals, barcoded, pooled, and sequenced in 10 MinION R9.4 SpotON flow cell runs producing over 30,000 reads per sample. Using barcoded 2D reads, SeqPilot assigned HLA alleles to two-field typing resolution or higher with the average read depth of 1750x. Sequence analysis resulted in 99-100% accuracy at low-resolution level (one-field) and in 74-100% accuracy at high-resolution level (two-field) with the expected alleles. There are still some limitations with ONT RNA sequencing, such as noisy reads, homopolymer errors, and the lack of robust algorithms, which interfere with confident allele assignment. These issues need to be inspected carefully in the future to improve the allele call rates. Nevertheless, here we show that sequencing of multiplexed cDNA amplicon libraries on ONT MinION can produce accurate high-resolution typing results of 12 classical HLA loci. For HLA research, ONT RNA sequencing is a promising method due to its capability to sequence full-length HLA transcripts. In addition to HLA genotyping, the technique could also be applied for simultaneous expression analysis.

Systematic comparative study of computational methods for HLA typing from next-generation sequencing.

The human leukocyte antigen (HLA) system plays an important role in hematopoietic stem cell transplantation (HSCT) and organ transplantations, immune disorders as well as oncological immunotherapy. However, HLA typing remains a challenging task due to the high level of polymorphism and homology among HLA genes. Based on the high-throughput next-generation sequencing data, new HLA typing algorithms and software tools were developed. But there is still a deficit of systematic comparative studies to assist in the selection of the optimal analytical approaches under different conditions. Here, we present a detailed comparison of eight software tools for HLA typing on different real datasets (whole-genome sequencing, whole-exome sequencing and transcriptomic sequencing data) and in-silico samples with different sequencing lengths, depths, and error rates. We figure out the algorithms with the best efficiency in different scenarios, and demonstrate the effect of different raw reads on analytical performances. Our results provide a comprehensive picture of specifications and performances of the eight existing HLA genotyping algorithms, which could assist researchers in selecting the most appropriate tool for specific raw datasets.

A Novel Allele-Specific PCR Protocol for the Detection of the HLA-C*03:02 Allele, a Pharmacogenetic Marker, in Vietnamese Kinh People.

BACKGROUND: Allopurinol, a common anti-hyperuricemia drug, is well known as an inducer of severe cutaneous adverse drug reactions (SCARs). One of the most well-defined risk factors of allopurinol-induced SCARs is the presence of polymorphic alleles of human leukocyte antigen (HLA) genes, such as HLA-B*58:01 and HLA-C*03:02 alleles. There is no commercial test or published in-house protocol for the specific detection of the HLA-C*03:02 allele. In this article, we established for the first time a simple allele-specific (AS) PCR method to identify HLA-C*03:02 allele carriers, and at the same time, determine their zygosities. METHODS: A two-step AS-PCR protocol, using four primer sets, was designed to specifically amplify and differentiate the HLA-C*03:02 allele from 17 other HLA-C alleles found in Vietnamese people. The protocol was validated with PCR-sequencing-based typing (SBT) of 100 samples of unknown genotypes. RESULTS: The PCR protocol can detect the HLA-C*03:02 allele and determine the zygosity. The results of this protocol were highly consistent with those of the SBT (ĸ = 0.98, p < 0.001). Regarding the specific detection of the HLA-C*03:02 allele, the PCR protocol had a sensitivity of 100% (95% CI: 91.61-100%) and specificity of 98.3% (95% CI: 90.9-99.7%). The protocol was used to determine the distribution of the HLA-C*03:02 allele in 810 unrelated Vietnamese Kinh people, 14.2% of which were HLA-C*03:02 carriers, the allele frequency was 7.5%. CONCLUSION: A novel AS-PCR protocol with a sensitivity of 100% for the detection of the HLA-C*03:02 allele was established. The protocol can be used for personalized treatment with allopurinol in order to minimize the risk of SCARs in Vietnamese people as well as in other Asian populations with similar genetic characteristics.

Chronic idiopathic axonal polyneuropathy: Electrophysiological progression and human leukocyte antigen associations.

BACKGROUND: We aimed to describe the electrophysiological progression rate of chronic idiopathic axonal polyneuropathy (CIAP) and look into the potential role of human leukocyte antigen (HLA) genetic susceptibility in its development. METHODS: We recruited 57 patients with CIAP (mean age at diagnosis 67, mean follow-up 7 years). The assessments included clinical and electrophysiological data and HLA-DQ genotyping. RESULTS: The DQA1*05 allele was found more frequently in patients than in healthy controls (odds ratio, 1.96, P = .011). In patients with length-dependent CIAP, a linear effect of time on the electrophysiological findings was found in the superficial radial (3.2% mean annual decrement, P < .001), sural (4.7% mean annual decrement, P = .002) and tibial nerve (6.1% mean annual decrement, P = .007) amplitudes, independently from age or gender. CONCLUSIONS: Patients with length-dependent CIAP, show a linear progression over time. Interesting associations of HLA-DQA1*05 allele with length-dependent CIAP and non-DQ2/DQ8 with idiopathic sensory ganglionopathy were found. These merit further investigation in larger cohorts and may suggest a role of the immune system in the pathogenesis of CIAP.

Benchmarking HLA genotyping and clarifying HLA impact on survival in tumor immunotherapy.

Human leukocyte antigen (HLA) genotyping gains intensive attention due to its critical role in cancer immunotherapy. It is still a challenging issue to generate reliable HLA genotyping results through in silico tools. In addition, the survival impact of HLA alleles in tumor prognosis and immunotherapy remains controversial. In this study, the benchmarking of HLA genotyping on TCGA is performed and a 'Gun-Bullet' model which helps to clarify the survival impact of HLA allele is presented. The performance of HLA class I genotyping is generally better than class II. POLYSOLVER, OptiType, and xHLA perform generally better at HLA class I calling with an accuracy of 0.954, 0.949, and 0.937, respectively. HLA-HD obtained the highest accuracy of 0.904 on HLA class II alleles calling. Each HLA genotyping tool displayed specific error patterns. The ensemble HLA calling from the top-3 tools is superior to any individual one. HLA alleles show distinct survival impact among cancers. Cytolytic activity (CYT) was proposed as the underlying mechanism to interpret the survival impact of HLA alleles in the 'Gun-Bullet' model for fighting cancer. A strong HLA allele plus a high tumor mutation burden (TMB) could stimulate intensive immune CYT, leading to extended survival. We established an up to now most reliable TCGA HLA benchmark dataset, composing of concordance alleles generated from eight prevalently used HLA genotyping tools. Our findings indicate that reliable HLA genotyping should be performed based on concordance alleles integrating multiple tools and incorporating TMB background with HLA genotype, which helps to improve the survival prediction compared to HLA genotyping alone.

Donor-dominant one-way matching of human leukocyte antigen-A/B/DR alleles predicts graft-versus-host disease following living donor liver transplantation.

AIM: Graft-versus-host disease (GVHD) following liver transplantation is rare but fatal. Therefore, it is important to identify possible risk factors before transplantation. Although it has been suggested that donor-dominant one-way human leukocyte antigen (HLA) matching of three loci (HLA-A/B/DR) is associated with the occurrence of GVHD, the precise significance of HLA matching including HLA-C/DQ/DP remains unclear. METHODS: We retrospectively analyzed the impact of donor-dominant one-way HLA matching at six HLA loci at the allele level on GVHD using clinical registry data from 1759 cases who underwent living donor liver transplantation between June 1990 and June 2019. We extracted cases with donor-dominant one-way HLA matching at the antigen level and reconfirmed them at the allele level using preserved DNA samples. RESULTS: Three of four cases (75%) who developed GVHD showed donor-dominant one-way HLA matching at three HLA-A/B/DR loci. These cases also showed donor-dominant one-way HLA matching at HLA-C/DQ/DP. Three of six cases (50%) with donor-dominant one-way HLA matching at three loci of HLA-A/B/DR developed GVHD. Notably, none of the cases with donor-dominant one-way HLA matching at one or two HLA-A/B/DR loci developed GVHD, irrespective of matching status at HLA-C/DQ/DP. The HLA matching status at the antigen level was revised in 22 of 56 cases, following reconfirmation at the allele level. CONCLUSIONS: Pairing of donors and recipients with donor-dominant one-way HLA matching at three HLA-A/B/DR loci should be avoided to prevent GVHD. No impact of HLA-C/DQ/DP on GVHD was identified. For liver transplantation, HLA genotypes should be determined at the allele level.

Gluten neuropathy: electrophysiological progression and HLA associations.

OBJECTIVE: Gluten neuropathy (GN) is the term used to describe peripheral neuropathy that occurs in patients with gluten sensitivity (GS) or coeliac disease (CD) in the absence of other risk factors. We aimed to describe the neurophysiological progression rate of GN across time and look into the potential role of genetic susceptibility in its development. METHODS: This is a cohort study of 45 patients with GN with a mean follow-up period of 8 ± 5 years. The assessments included clinical and neurophysiological data and HLA-DQ genotyping. RESULTS: The mean age at diagnosis was 60 ± 12 years. The majority of patients had a length-dependent neuropathy (75.6%), whereas the rest were diagnosed with sensory ganglionopathy (SG). DQA1*02-positive patients were more likely to suffer with SG compared to the DQA1*02 negative patients (60% versus 13.8%, p = 0.009). There was also a trend for statistical significance regarding the DQB1*06 allele and the DQA1*01/DQB1*06 haplotype were found more frequently in patients with GN than in healthy controls (p = 0.026 and p = 0.047, respectively). A linear effect of time on the neurophysiological findings was found in radial sensory nerve action potential (1.9% mean annual decrement, p = 0.036), sural sensory nerve action potential (3.3% mean annual decrement, p = 0.013) and tibial nerve motor compound action potential (6.5% mean annual decrement, p < 0.001) amplitudes, independently from age or gender. CONCLUSIONS: GN is a late manifestation of GS and CD. The majority of patients have the length-dependent neuropathy with a linear deterioration over time. HLA genotyping of GS and CD patients who suffer from neuropathic symptoms is recommended as it can help identifying patients at risk for developing SG.

HLA allele and haplotype frequencies in the Panamanian population.

In this study, we report for the first time HLA allele and haplotype frequencies in the modern Panamanian population at a two-field (four digits) resolution level. Reported frequencies were calculated from genotype data for the HLA-A, -B, -C, -DPB1, -DQB1 and -DRB1 loci of 462 healthy unrelated Panamanian adults of Hispanic ethnicity. In addition to providing new insights on the allelic structure of the Panamanian population and its origin, these data are critical for better planning of healthcare strategies in the country and for future research exploring the association with certain chronic and infectious diseases.

Diffuse panbronchiolitis: A case report from a Chinese consanguineous marriage family and literature review.

Diffuse panbronchiolitis (DPB) is a chronic diffuse airway inflammatory disease, which is strongly associated with the class I human leukocyte antigen (HLA) alleles. Here, we report a pair of sisters who have been suffering from chronic cough, expectoration and wheezing for many years. They were previously misdiagnosed as chronic bronchitis and bronchial asthma, and were recently diagnosed as diffuse panbronchiolitis. The 36-year-old elder sister suffered from diffuse panbronchiolitis complicated with pulmonary tuberculosis. The 30-year-old younger sister suffered from diffuse panbronchiolitis complicated with bronchial asthma and bronchiectasis. We have performed HLA genotyping research on the two sisters, their parents and younger brother. The results showed that all family members were positive for HLA-A24 and HLA-B13. The younger sister and mother were positive for HLA-A2. The younger brother and father were positive for HLA-A11. We suspect that the two sisters' disease susceptibility may be caused by their parents' consanguineous marriage. In this study, we reported the clinical characteristics of the two sisters with diffuse panbronchiolitis and shared the associated HLA genotyping results of this family cluster, hoping to provide reference for the etiology, diagnosis and treatment of this disease.

Utilizing nanopore sequencing technology for the rapid and comprehensive characterization of eleven HLA loci; addressing the need for deceased donor expedited HLA typing.

The comprehensive characterization of human leukocyte antigen (HLA) genomic sequences remains a challenging problem. Despite the significant advantages of next-generation sequencing (NGS) in the field of Immunogenetics, there has yet to be a single solution for unambiguous, accurate, simple, cost-effective, and timely genotyping necessary for all clinical applications. This report demonstrates the benefits of nanopore sequencing introduced by Oxford Nanopore Technologies (ONT) for HLA genotyping. Samples (n = 120) previously characterized at high-resolution three-field (HR-3F) for 11 loci were assessed using ONT sequencing paired to a single-plex PCR protocol (Holotype) and to two multiplex protocols OmniType (Omixon) and NGSgo®-MX6-1 (GenDx). The results demonstrate the potential of nanopore sequencing for delivering accurate HR-3F typing with a simple, rapid, and cost-effective protocol. The protocol is applicable to time-sensitive applications, such as deceased donor typings, enabling better assessments of compatibility and epitope analysis. The technology also allows significantly shorter turnaround time for multiple samples at a lower cost. Overall, the nanopore technology appears to offer a significant advancement over current next-generation sequencing platforms as a single solution for all HLA genotyping needs.