High-resolution HLA Genotyping Research Articles

Revolutionising High Resolution HLA Genotyping for Transplant Assessment: Validation, Implementation and Challenges of Oxford Nanopore Technologies' Q20+ Sequencing.

The advent of third-generation sequencing (TGS) represents a significant shift in the field of genetic sequencing, enabling single-molecule sequencing to overcome limitations of short-read NGS platforms. Several studies have assessed the utilisation of TGS in HLA genotyping, though many of these studies have described the high error rate as an obstacle to achieving a robust and highly accurate HLA typing assay. In 2021, Oxford Nanopore Technologies (ONT) released the high-accuracy sequencing Kit 14 and the MinION flow cell model R10.4.1, which were reported to achieve sequencing accuracies up to 99%. The aim of this study was to validate this novel high-accuracy sequencing kit for HLA genotyping coupled with a full-gene HLA PCR assay. Comparison with historical data obtained using legacy flow cell models such as R9.4, R10.3 and R10.4 was also done to assess progressive improvement in sequencing performance with each sequential release. The workflow was validated based on data throughput, sequence quality and accuracy, and HLA genotyping resolution. An initial validation was performed using an internal reference panel of 42 samples representing common HLA allele groups, followed by an analysis of data obtained from 111 sequencing batch runs since the implementation, to assess assay performance and define quality control metrics to assess inter-run variability and monitor quality. Furthermore, challenges arising from MinION flow cell stability and use, and assessment of barcode contamination are discussed. The findings of this study highlight advantages of ONT sequencing kit 14/R10.4.1 for HLA genotyping and the implementation considerations for the routine diagnostic HLA laboratory.

High resolution HLA genotyping with third generation sequencing technology-A multicentre study.

Molecular HLA typing techniques are currently undergoing a rapid evolution. While real-time PCR is established as the standard method in tissue typing laboratories regarding allocation of solid organs, next generation sequencing (NGS) for high-resolution HLA typing is becoming indispensable but is not yet suitable for deceased donors. By contrast, high-resolution typing is essential for stem cell transplantation and is increasingly required for questions relating to various disease associations. In this multicentre clinical study, the TGS technique using nanopore sequencing is investigated applying NanoTYPE™ kit and NanoTYPER™ software (Omixon Biocomputing Ltd., Budapest, Hungary) regarding the concordance of the results with NGS and its practicability in diagnostic laboratories. The results of 381 samples show a concordance of 99.58% for 11 HLA loci, HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1 and -DPB1. The quality control (QC) data shows a very high quality of the sequencing performed in each laboratory, 34,926 (97.15%) QC values were returned as 'passed', 862 (2.4%) as 'inspect' and 162 (0.45%) as 'failed'. We show that an 'inspect' or 'failed' QC warning does not automatically lead to incorrect HLA typing. The advantages of nanopore sequencing are speed, flexibility, reusability of the flow cells and easy implementation in the laboratory. There are challenges, such as exon coverage and the handling of large amounts of data. Finally, nanopore sequencing presents potential for applications in basic research within the field of epigenetics and genomics and holds significance for clinical concerns.

HLA Genotype Imputation Results in Largely Accurate Epitope Mismatch Risk Categorization Across Racial Groups.

Biomarkers that predict posttransplant alloimmunity could lead to improved long-term graft survival. Evaluation of the number of mismatched epitopes between donor and recipient HLA proteins, termed molecular mismatch analysis, has emerged as an approach to classify transplant recipients as having high, intermediate, or low risk of graft rejection. When high-resolution genotypes are unavailable, molecular mismatch analysis requires algorithmic assignment, or imputation, of a high-resolution genotyping. Although imputation introduces inaccuracies in molecular mismatch analyses, it is unclear whether these inaccuracies would impact the clinical risk assessment for graft rejection. Using renal transplant patients and donors from our center, we constructed cohorts of surrogate donor-recipient pairs with high-resolution and low-resolution HLA genotyping that were racially concordant or discordant. We systemically assessed the impact of imputation on molecular mismatch analysis for cohorts of 180-200 donor-recipient pairs for each of 4 major racial groups. We also evaluated the effect of imputation for a racially diverse validation cohort of 35 real-world renal transplant pairs. In the surrogate donor-recipient cohorts, imputation preserved the molecular mismatch risk category for 90.5%-99.6% of racially concordant donor-recipient pairs and 92.5%-100% of racially discordant pairs. In the validation cohort, which comprised 72% racially discordant pairs, we found that imputation preserved the molecular mismatch risk category for 97.1% of pairs. Overall, these data demonstrate that imputation preserves the molecular mismatch risk assessment in the vast majority of cases and provides evidence supporting imputation in the performance of molecular mismatch analysis for clinical assessment.

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.

Low C4A copy numbers and higher HERV gene insertion contributes to increased risk of SLE, with absence of association with disease phenotype and disease activity.

Low copy numbers (CNs) of C4 genes are associated with systemic autoimmune disorders and affects autoantibody diversity and disease subgroups. The primary objective of this study was to characterize diversity of complement (C4) and C4-Human Endogenous Retrovirus (HERV) gene copy numbers in SLE. We also sought to assess the association of C4 and C4-HERV CNs with serum complement levels, autoantibodies, disease phenotypes and activity. Finally, we checked the association of C4 and HERV CNs with specific HLA alleles. Genomic DNA from 70 SLE and 90 healthy controls of south Indian Tamil origin were included. Demographic, clinical and serological data was collected in a predetermined proforma. CNs of C4A and C4B genes and the frequency of insertion of 6.4kb HERV within C4 gene (C4AL, C4BL) was determined using droplet digital polymerase chain reaction (ddPCR). A four digit high resolution HLA genotyping was done using next generation sequencing. In our cohort, the total C4 gene copies ranged from 2 to 6. Compared to controls, presence of two or less copies of C4A gene was associated with SLE risk (p = 0.005; OR = 2.79; 95% CI = 1.29-6.22). Higher frequency of HERV insertion in C4A than in C4B increases such risk (p = 0.000; OR = 12.67; 95% CI = 2.80-115.3). AL-AL-AL-BS genotype was significantly higher in controls than SLE (9%vs1%, p = 0.04; OR = 0.15, 95% CI = 0.00-0.16). Distribution of HLA alleles was not different in SLE compared to controls as well as in SLE subjects with ≤ 2 copies and > 2 copies of C4A, but HLA allele distribution was diverse in subjects with C4B ≤ 2 copies and > 2 copies. Finally, there was no correlation between the C4 and the C4-HERV diversity and complement levels, autoantibodies, disease phenotypes and activity. In conclusion, our data show that, low C4A copy number and higher insertion of HERV-K in C4A increases the risk for SLE. C4 and C4-HERV CNs did not correlate with serum complements, autoantibodies, disease phenotypes and activity in SLE. Further validation in a larger homogenous SLE cohort is needed.

High-resolution KIR and HLA genotyping in three Chinese ethnic minorities reveals distinct origins.

Polymorphism of killer-cell immunoglobulin-like receptors (KIRs) and their HLA class I ligands impacts the effector activity of cytotoxic NK cell and T cell subsets. Therefore, understanding the extent and implications of KIR and HLA class I genetic polymorphism across various populations is important for immunological and medical research. In this study, we conducted a high-resolution investigation of KIR and HLA class I diversity in three distinct Chinese ethnic minority populations. We studied the She, Yugur, and Tajik, and compared them with the Zhejiang Han population (Zhe), which represents the majority Southern Han ethnicity. Our findings revealed that the Tajik population exhibited the most diverse KIR copy number, allele, and haplotype diversity among the four populations. This diversity aligns with their proposed ancestral origin, closely resembling that of Iranian populations, with a relatively higher presence of KIR-B genes, alleles, and haplotypes compared with the other Chinese populations. The Yugur population displayed KIR distributions similar to those of the Tibetans and Southeast Asians, whereas the She population resembled the Zhe and other East Asians, as confirmed by genetic distance analysis of KIR. Additionally, we identified 12.9% of individuals across the three minority populations as having KIR haplotypes characterized by specific gene block insertions or deletions. Genetic analysis based on HLA alleles yielded consistent results, even though there were extensive variations in HLA alleles. The observed variations in KIR interactions, such as higher numbers of 2DL1-C2 interactions in Tajik and Yugur populations and of 2DL3-C1 interactions in the She population, are likely shaped by demographic and evolutionary mechanisms specific to their local environments. Overall, our findings offer valuable insights into the distribution of KIR and HLA diversity among three distinct Chinese ethnic minority populations, which can inform future clinical and population studies.

HLA molecular mismatches and induced donor-specific tolerance in combined living donor kidney and hematopoietic stem cell transplantation.

We investigated the potential role of HLA molecular mismatches (MM) in achieving stable chimerism, allowing for donor-specific tolerance in patients undergoing combined living donor kidney and hematopoietic stem cell transplantation (HSCT). All patients with available DNA samples (N=32) who participated in a phase 2 clinical trial (NCT00498160) where they received an HLA mismatched co-transplantation of living donor kidney and facilitating cell-enriched HSCT were included in this study. High-resolution HLA genotyping data were used to calculate HLA amino acid mismatches (AAMM), Eplet MM, three-dimensional electrostatic mismatch scores (EMS-3D), PIRCHE scores, HLA-DPB1 T-cell epitope group MM, HLA-B leader sequence MM, and KIR ligands MM between the donor and recipient in both directions. HLA MM were analyzed to test for correlation with the development of chimerism, graft vs. host disease (GvHD), de novo DSA, and graft rejection. Follow-up time of this cohort was 6-13.5 years. Of the 32 patients, 26 developed high-level donor or mixed stable chimerism, followed by complete withdrawal of immunosuppression (IS) in 25 patients. The remaining six of the 32 patients had transient chimerism or no engraftment and were maintained on IS (On-IS). In host versus graft direction, a trend toward higher median number of HLA-DRB1 MM scores was seen in patients On-IS compared to patients with high-level donor/mixed chimerism, using any of the HLA MM modalities; however, initial statistical significance was observed only for the EMS-3D score (0.45 [IQR, 0.30-0.61] vs. 0.24 [IQR, 0.18-0.36], respectively; p=0.036), which was lost when applying the Bonferroni correction. No statistically significant differences between the two groups were observed for AAMM, EMS-3D, Eplet MM, and PIRCHE-II scores calculated in graft versus host direction. No associations were found between development of chimerism and GvHD and non-permissive HLA-DPB1 T-cell epitope group MM, HLA-B leader sequence, and KIR ligands MM. Our results suggest an association between HLA-DRB1 molecular mismatches and achieving stable chimerism, particularly when electrostatic quality of the mismatch is considered. The non-permissive HLA-DPB1 T-cell epitope group, HLA-B leader sequence, and KIR ligands MM do not predict chimerism and GvHD in this combined kidney/HSCT transplant patient cohort. Further work is needed to validate our findings. https://clinicaltrials.gov/study/NCT00498160, identifier NCT00498160.

High-resolution HLA genotyping identifies risk alleles in both class I and II for primary autoimmune neutropenia in early childhood in a Danish cohort.

HLA studies in patients with autoimmune neutropenia (AIN) have shown very consistent results for the association with HLA class II alleles at low resolution. This study aimed to examine the association of both HLA class I and class II at high resolution to clarify the contribution of risk alleles to the disease. A total of 107 AIN patients were genotyped for six loci of HLA class I (HLA-A, -B and -C) and class II (HLA-DRB1, -DQB1, and -DPB1) genes by a high-resolution (3-field, 6-digit) analysis and compared with HLA typing of 1000 healthy controls. Compared with the controls, the allele frequencies were significantly higher in AIN patients for A*02:17:01G, C*01:02:01G, DRB1*10:01:01G, DRB1*14:01:01G, DRB1*16:01:01G, DQB1*05:02:01G, and DQB1*05:03:01G but lower significant for C*03:04:01G, DRB1*04:01:01G, DRB1*13:02:01G, DQB1*03:02:01G, and DQB1*06:04:01G. Frequently associated two-locus haplotypes were found to be DRB1*10:01:01G-DQB1*05:01:01G and DRB1*16:01:01G-DQB1*05:02:01G, while the S2 (Q- or D-KRAA) shared epitope (SE) was associated with lower risk. A unique association with HLA alleles was observed between patients with specific anti-HNA-1a antibodies and broad-reacting anti-FcγRIIIb. Anti-HNA-1a antibody-positive patients were associated with C*01:02:01G, DRB1*01:01:01G, DRB1*16:01:01G, DQB1*05:01:01G, DQB1*05:02:01G, DQB1*06:04:01G, and DPB1*10:01:01G; the two-locus haplotypes DRB1*01:01:01G-DQB1*05:01:01G and DRB1*16:01:01G-DQB1*05:02:01G; and the S3P (Q- or R-RRAA) SE. Anti-FcγRIIIb antibody-positive patients were associated with the alleles A*02:17:01G, DRB1*10:01:01G, and DQB1*05:02:01G; the haplotypes DRB1*10:01:01G-DQB1*05:01:01G and DRB1*11:01:02G-DQB1*05:02:01G; and the S3D (DRRAA) SE. The different associations regarding FcγRIIIb antibody specificities could indicate disease heterogeneity.

The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection.

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.

The Importance of Confirming False Homozygosity in Pretransplant HLA Typing Results of Patients with Hematologic Malignancies.

Loss of heterozygosity (LOH) on chromosome 6p, where the HLA genes are located, can result in incorrect homozygosity findings during HLA genotyping in patients with hematologic malignancies. The degree of HLA compatibility between donor and recipient is crucial in hematopoietic stem cell transplantation. Therefore, we present a case of false homozygosity in HLA genotyping due to LOH on chromosome 6p in a patient diagnosed with acute myeloid leukemia (AML). HLA molecular typing was conducted on both peripheral blood and buccal swab samples. The analysis included sequence-based typing (SBT) and next-generation sequencing-based typing. Additionally, chromosomal microarray analysis (CMA) was performed. A 68-year-old male presented with anemia and thrombocytopenia. Subsequent bone marrow examination confirmed AML. High-resolution HLA genotyping of Peripheral blood during blast crisis revealed homozygosity at the -A, -B, and -C loci. Conventional karyotyping showed a normal karyotype, 46,XY[20]. Retesting of HLA genotyping one week later confirmed the homozygous results. Subsequently, HLA typing was repeated using buccal swab specimens, confirming heterozygosity at all 4 HLA loci. CMA on peripheral blood samples during blast crisis revealed a large terminal region of copy-neutral LOH spanning approximately 43.5 Mb in the chromosome region 6p25.3p21.1. LOH at the HLA gene locus can significantly impact donor selection, potentially leading to the selection of mistakenly identified homozygous donors. Clinicians and laboratory personnel should be aware of these issues to prevent erroneous HLA typing results in patients with hematologic malignancies. It is advisable to confirm the HLA typing of recipients with hematologic malignancies whenever homozygosity is detected at any locus. This can be achieved through careful interpretation of low peaks in SBT, and by using buccal swab samples or peripheral blood collected after achieving remission.

Branching Trajectories and Diversification of Clonal Escape in Aplastic Anemia Revealed By Single-Cell Genomics

Acquired aplastic anemia (AA) is a bone marrow failure resulting from an autoimmune T-cell attack against hematopoietic stem and progenitor cells (HSPCs). Several escape mechanisms within the HSPC compartment have been reported: i) adaptive alterations causing loss of high-risk HLA allele of AA development [deletion or uniparental disomy (UPD) of chromosome 6p including HLA cluster region, and loss-of-function (LOF) mutations in HLA gene], ii) clonal expansion of paroxysmal nocturnal hemoglobinuria (PNH) clone resulting from PIGA mutation, and iii) presence of clonal hematopoiesis of indeterminate potential (CHIP) mutations (i.e., BCOR/ BCORL1, DNMT3A, ASXL1). Multiple types of alterations often co-occur, however due to the inherent limitations of conventional methods, it is not known if i) these alterations are in the same or independent clones, ii) what is the mutational hierarchy, and iii) what is the cell of origin. We addressed these questions using single-cell and bulk genomic sequencing. We developed custom single-cell panels covering HLA class I and II genes, along with 14 genes commonly mutated in AA and myelodysplastic syndromes. To identify copy number variations and UPD, we included 197 single nucleotide variants (SNVs) frequent across all ethnic backgrounds on chromosomes 6, 7, 8, 20, and 21. The TotalSeq™-D panel (BioLegend), was included to target 42 surface antigens and the samples were prepared on the Tapestri platform (Missionbio). High-resolution HLA genotyping was done using AlloSeq Tx 17 hybrid capture NGS assay (CareDx), and for confirmatory bulk sequencing we applied a custom duplex UMI NGS panel (TWIST Bioscience). We examined ten patients with severe AA (pediatric: n=6, age range 2-15 years; adult: n=4, 26-67), seven patients with refractory cytopenia of childhood (RCC, age range 2-16 years), who presented a hypocellular marrow and absence of a genetic predisposition syndrome, and one healthy control. All 17 patients had at least one of the HLA-A or HLA-B risk alleles linked to AA development. A total of 136,505 cells (median 4,467/run) were successfully genotyped across the samples. Single-cell trajectory analysis revealed that all identified clones arose independent of each other (Figure 1). UPD6p clones were found in five patients with three having multiple UPD6p clones carrying different breakpoints, pointing to clonal diversification. Additionally, three cases had LOF mutations in HLA-A or HLA-B (two having coexisting UPD6p). In a patient with two UPD6p and two HLA-A mutant clones, we verified that HLA-A risk allele (A*02:01) was lost in each instance. Multi-omic analysis revealed that these clones had both granulocytic and non-granulocytic (incl. lymphocytic) surface phenotypes, suggesting their early origin within hematopoietic ontogeny. Seven patients had nine independent clones with PIGA mutations (0.3-11.3% of the cells), consistent with its tendency to generate clonal mosaicism. Clones with mutations in BCOR/BCORL1, ASXL1, DNMT3A, and TET2 were identified in six, seven, four, and two patients, respectively. We next analyzed how many patients carry multiple clones and found that 65% (11/17) have concomitant clones, with the majority (9/11) belonging to different types of clonal escape (Figure 1). Finally, we found that 4/6 patients with adaptive HLA loss (representing true clonal escape from T-cell autoimmunity) also carried CHIP clones, indicating that adaptive hematopoiesis does not protect from the acquisition of CHIP mutations. In conclusion, we show that patients with AA across age spectrum and some patients with RCC share similar clonal backgrounds, with multiple functionally redundant alterations arising independently from coexisting CHIP clones. For the first time at a single-cell level, we were able to resolve the multifaceted clonal mosaic generated by the immunological forces at play in AA, and precisely unravel their immunoediting consequences.

Validation and application of new NGS-based HLA genotyping to clinical diagnostic practice.

Next-generation sequencing (NGS) has revolutionized clinical genotyping, providing high-resolution HLA genotyping with a low ambiguity rate. This study aimed to develop new NGS-based HLA genotyping (HLAaccuTest, NGeneBio, Seoul, KOREA) on the Illumina MiSeq platform and validate the clinical performance. The analytical performance of HLAaccuTest was validated for 11 loci comprising HLA-A, -B, -C, -DRB1/3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 using 157 reference samples. Among the 345 clinical samples, 180 were tested for performance evaluation and protocol optimization, and 165 were used in clinical trials in the validation phase for five loci, including HLA-A, -B, -C, -DRB1, and -DQB1. In addition, the improvement in the resolution of ambiguous alleles was also evaluated and compared with other NGS-based HLA genotyping for 18 reference samples, including five overlapping samples in analytical performance validation. All reference materials produced 100% concordant results for 11 HLA loci, 96.9% (2092 of 2160 HLA alleles) of the clinical samples were matched with the SBT results in the pre-validation phase. After the optimization phase, the clinical trials in the validation phase showed 99.7% (1645/1650 alleles) concordance with the complete resolution for 34 ambiguity results. The retesting of five discordant cases resolved all issues and yielded 100% concordant results with the SBT method. Additionally, for ambiguity using 18 reference materials with ambiguous alleles, about 30% of ambiguous alleles were more resolved than Trusight HLA v2. HLAaccuTest was successfully validated using a large volume of clinical samples and is fully applicable to the clinical laboratory.

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

BackgroundSpecific 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.MethodsPaired 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.ResultsIn 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.ConclusionsWe 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.

Interplay Between Class II HLA Genotypes and the Microbiome and Immune Phenotypes in Individuals With PTEN Hamartoma Tumor Syndrome.

Illumina sequencing of bacterial and fungal microbes was carried out on patient-donated fecal samples in a cohort of 67 patients with pathogenic germline PTEN mutations, including 41 individuals with autoimmunity and/or phenotypes consistent with immune dysregulation (cases) and 26 individuals without (controls). From these data, we measured differences in alpha and beta diversity between cases and controls and identified differentially abundant bacterial and fungal taxa using phyloseq and MicrobiomeSeq packages in R. We analyzed correlations between these taxa and specific HLA genotypes, along with correlations between HLA diversity and microbial diversity, by conducting high-resolution HLA genotyping at four class II loci (DRB1, DRB345, DQA1, and DQB1). We found that alpha diversity distributions for both bacterial and fungal genera were statistically different between cases and controls. We identified differentially abundant bacterial and fungal taxa between cases and controls. Network analysis of differentially abundant bacterial taxa revealed some co-varying bacterial genera. We additionally found significant correlations between certain HLA genotypes and certain taxa and significant correlations between HLA diversity and alpha diversity. PTEN-associated immune phenotypes might be influenced by the gut microbiome, and class II HLA molecules, in part, crosstalk with the gut microbiome. These preliminary observations should lay the groundwork for future studies to ultimately derive clinical measures, which could use gut microbiome and HLA molecule biomarkers to predict, and perhaps prevent, immunity and inflammation in patients predisposed to cancer because of germline PTEN mutations.

Eplet mismatch imputation studies should include immunologic risk assessment

To the Editor: HLA eplet mismatch analysis represents the evolution from antigen-level match assessments and cell-based donor-specific antibody (DSA) identification to an integrated approach combining sophisticated molecular histocompatibility genotyping with solid phase antibody detection techniques. Analyzing eplet mismatches between donor–recipient pairs at each HLA locus and using eplet motifs in the interpretation of posttransplant antibody reactivity has garnered increasing attention in recent years. Seminal studies to date reveal a direct correlation between posttransplant outcomes and the degree of HLA-DR and/or HLA-DQ eplet mismatches, particularly when grouped into high or low eplet mismatch ranges.1Wiebe C Nickerson PW. Human leukocyte antigen molecular mismatch to risk stratify kidney transplant recipients.Current Opinion Organ Transplant. 2020; 25: 8-14Crossref PubMed Scopus (18) Google Scholar While this area of solid organ transplantation continues to develop, there is an anticipation that eplet mismatch analysis will eventually play a role in organ allocation. Two recent studies in AJT by Senev et al2Senev A Emonds MP Van Sandt V et al.Clinical importance of extended second field high-resolution HLA genotyping for kidney transplantation.Am J Transplant. 2020; 20: 3367-3378Abstract Full Text Full Text PDF PubMed Scopus (37) Google Scholar and Engen et al3Engen RM Jedraszko AM Conciatori MA Tambur AR. Substituting imputation of HLA antigens for high-resolution HLA typing: Evaluation of a multiethnic population and implications for clinical decision making in transplantation.Am J Transplant. 2021; 21 (https://doi.org/10.1111/ajt.16070): 344-352Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar performed stringent analyses of the accuracy of imputing high-resolution typing based on the low-resolution HLA genotyping to identify eplet mismatches in donor–recipient pairs. Using slightly different methods, these groups found that imputation did not agree with high-resolution HLA genotyping in 8.7–18.8% of pairs for HLA-ABC eplets and 37–46.1% of pairs for HLA-DR and DQB1 eplets. The authors concluded that the overall imprecision of imputation was a major limitation to eplet mismatch analysis. However, we believe that the utility and potential application of imputation for determining HLA eplet mismatch burden was not fully addressed in the two studies. While we agree that imputation is not a perfect tool to define high-resolution HLA typing results, we maintain that imputation can nonetheless be a useful approach when high-resolution typing is unavailable. Multiple retrospective studies have correlated clinical outcomes, such as DSA formation and graft rejection, with numerical ranges of eplet mismatches that stratify donor–recipient pairs into high or low immunologic risk groups. As such, risk stratification does not necessarily depend on the correct identification of each individual eplet. For example, if imputation versus high-resolution genotyping increased the mismatch burden by four HLA-DR eplets, but did not change the immunologic risk stratification because the number of eplet mismatches remains below the low-risk cutoff of 10,4Wiebe C Kosmoliaptsis V Pochinco D et al.HLA-DR/DQ molecular mismatch: a prognostic biomarker for primary alloimmunity.Am J Transplant. 2019; 19: 1708-1719Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar then imputation would be useful. Supporting this presumption, Senev et al show in Figure 6 that in 88% of cases the imputed HLA-DR and -DQ eplet mismatch burden is within two eplets of agreement with high-resolution genotyping (Figure 6). Similarly, Engen et al report in Table 8 that in 85.4% of cases, the imputed total Class-I and Class-II eplet mismatch burden is within two eplets of high-resolution genotyping. While a direct analysis was not performed, those data strongly suggest that imputation would result in the correct eplet-based immunologic risk stratification in nearly all cases. In the future, as total eplet mismatch burden is superseded by analysis of the mismatch of specific immunogenic eplets, the need for high-resolution genotyping will grow.5McCaughan JA Battle RK Singh SKS et al.Identification of risk epitope mismatches associated with de novo donor-specific HLA antibody development in cardiothoracic transplantation.Am J Transplant. 2018; 18: 2924-2933Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar However, in the current era of eplet mismatch analysis, we believe that imputation is a reasonable approach for retrospective studies when high-resolution genotyping is not available. The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.

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.

IntroductionHuman 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.MethodsQuantitative 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).ResultsA 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.ConclusionGenotyping for these alleles will enable identification of individuals at risk of severe disease and stratification for preferential vaccination.

Risk factors, histopathological features, and graft outcome of transplant glomerulopathy in the absence of donor-specific HLA antibodies

Transplant glomerulopathy is established as a hallmark of chronic antibody-mediated rejection in kidney transplant patients with donor-specific HLA antibodies (HLA-DSA). The clinical importance of transplant glomerulopathy in the absence of HLA-DSA is not well established. To help define this, 954 patients (encompassing 3744 biopsies) who underwent kidney transplantation 2004-2013 were studied with retrospective high-resolution HLA genotyping of both donors and recipients. The risk factors, histopathological appearance and prognosis of cases with transplant glomerulopathy in the absence of HLA-DSA were compared to those cases with HLA-DSA, and the impact of the PIRCHE-II score and eplet mismatches on development of transplant glomerulopathy evaluated. In this cohort, 10.3% developed transplant glomerulopathy, on average 3.2 years post-transplant. At the time of glomerulopathy, 23.5% had persistent pre-transplant or de novo HLA-DSA, while 76.5% were HLA-DSA negative. Only HLA-DSA was identified as a risk factor for glomerulopathy development as eplet mismatches and the PIRCHE-II score did not associate. HLA-DSA negative biopsies with glomerulopathy had less interstitial inflammation, less glomerulitis, and less C4d deposition in the peritubular capillaries compared to the HLA-DSA positive biopsies with glomerulopathy. While graft function was comparable between the two groups, HLA-DSA positive glomerulopathy was associated with a significantly higher risk of graft failure compared to HLA-DSA negative glomerulopathy (Hazard Ratio 3.84; 95% confidence interval 1.94-7.59). Landmark analysis three-years post-transplant showed that HLA-DSA negative patients with glomerulopathy still had a significant increased risk of graft failure compared to patients negative for glomerulopathy (2.62; 1.46-4.72). Thus, transplant glomerulopathy often occurs in the absence of HLA-DSA, independent of HLA molecular mismatches, and represents a different phenotype with less concomitant inflammation and better graft survival compared to that developed in the presence of HLA-DSA.

Incidence and impact of allele-specific anti-HLA antibodies and high-resolution HLA genotyping on assessing immunologic compatibility

The ability to identify specific HLA molecules against which a patient has alloantibodies has revolutionized assessment of immunologic compatibility. Anti-HLA antibodies are typically evaluated as reactive against well-defined serologic antigen groups. Thus, donor HLA genotyping is aimed at defining HLA at the serologic split-antigen level to avoid incompatible antigen-antibody combinations. However, anti-HLA antibodies can have reactivities not accurately described by well-defined serologic antigens. While existence of these antibodies is acknowledged, their precise impact on clinical practice is not clear. We performed a single-center review of 2 years of pre-and post-transplant anti-HLA antibody testing data combined with high-resolution HLA genotyping data for living and deceased organ donors to evaluate the clinical impact of anti-HLA antibodies with reactivities outside of commonly defined serologic antigen groups. We find approximately 15% of patients awaiting transplantation have alloantibodies with differential reactivity for HLA proteins encoded by specific alleles within a serologic antigen group. Allele-specific antibodies are associated with positive cellular crossmatches not accurately predicted by standard donor HLA genotyping and can manifest as post-transplant donor-specific antibodies. Our data highlights the importance of evaluating anti-HLA antibodies at the allele-level and provides evidence supporting utility for high-resolution HLA genotyping in solid organ transplantation.

HLA genotyping in synovial sarcoma: Identifying HLA-A*02 and its association with clinical outcome.

e23560 Background: Patients (pts) with synovial sarcoma (SS) and an HLA-A*02 genotype whose tumors express NY-ESO-1 may be eligible for clinical trials of adoptive T cell therapy. We reasoned that a next generation tumor sequencing platform utilizing matched normal DNA (MSK-IMPACT) could accurately identify HLA genotype. Although HLA-A*02 is necessary for some adoptive T cell therapies, the prognosis of this genotype on clinical outcome has not been described in SS. Methods: Pts with metastatic SS who consented to screen for a clinical trial of engineered T cells had high-resolution HLA genotyping performed with a Clinical Laboratory Improvement Amendments (CLIA)-certified test. Where feasible, HLA genotype and loss-of-heterozygosity (LOH) of HLA alleles were determined from IMPACT samples. Overall survival (OS) was estimated in three overlapping cohorts and stratified by HLA-A*02 status: pts treated with anthracyclines or alkylators in the first line, pazopanib in the second line or beyond, and all pts from time of metastasis. Results: 66 pts with SS were screened, but not treated with T cells; 30% (n = 20) were HLA-A*02-positive on a CLIA-certified outside test. 23 pts had HLA genotyping both by IMPACT and an outside laboratory, 22 (96%) of whom had concordant results. 3 pts had LOH of at least 1 HLA allele, including one with LOH of HLA*02:01 in the primary tumor. Among pts treated chemotherapy (n = 36) or pazopanib (n = 37), OS did not significantly differ between HLA-A*02-positive or negative pts. Univariable analyses of OS from the time of metastasis in the whole cohort identified primary tumor size and time to metastasis as variables significantly associated with outcome (hazard ratio (HR) 1.2, 95% confidence interval (CI) 1.123 – 1.345 [P < 0.001] and HR 0.99, 95% CI 0.976 – 0.999 [P = 0.032], respectively). HLA-A*02-positive status and age did not reach the significance threshold (HR 1.95, 95% CI 0.995 – 3.813 [P = 0.052] and HR 1.021, 95% CI 0.999 – 1.044 [P = 0.061], respectively). Multivariable analysis found older age and larger tumor size were independently associated with significantly shorter OS (HR 1.03, 95% CI 1.002 – 1.049 [P = 0.037] and HR 1.2, 95% CI 1.127 – 1.37 [P < 0.001], respectively). Conclusions: Targeted exome panels like IMPACT that utilize matched tumor-normal DNA may accurately identify HLA genotype. Detection of LOH at HLA loci may identify a subgroup of pts who would be refractory to treatment with HLA-A*02-restricted engineered T cells. HLA-A*02 status was not associated with a statistically significant survival difference in pts with metastatic SS.