Utilizing principal component analysis in the identification of clinically relevant changes in patient HLA single antigen bead solid phase testing patterns.

BACKGROUND: HLA antibody testing is essential for successful solid-organ allocation, patient monitoring post-transplant, and risk assessment for both solid-organ and hematopoietic transplant patients. Luminex solid-phase testing is the most common method for identifying HLA antibody specificities, making it one of the most complex immunoassays as each panel contains over 90 specificities for both HLA class I and HLA class II with most of the analysis being performed manually in the vendor-provided software. Principal component analysis (PCA), used in machine learning, is a feature extraction method often utilized to assess data with many variables. METHODS & FINDINGS: In our study, solid organ transplant patients who exhibited HLA donor-specific antibodies (DSAs) were used to characterize the utility of PCA-derived analysis when compared to a control group of post-transplant and pre-transplant patients. ROC analysis was utilized to determine a potential threshold for the PCA-derived analysis that would indicate a significant change in a patient's single antigen bead pattern. To evaluate if the algorithm could identify differences in patterns on HLA class I and HLA class II single antigen bead results using the optimized threshold, HLA antibody test results were analyzed using PCA-derived analysis and compared to the clinical results for each patient sample. The PCA-derived algorithm had a sensitivity of 100% (95% CI, 73.54%-100%), a specificity of 75% (95% CI, 56.30%-92.54%), with a PPV of 65% (95% CI, 52.50%-83.90%) and an NPV of 100%, in identifying new reactivity that differed from the patients historic HLA antibody pattern. Additionally, PCA-derived analysis was utilized to assess the potential over-reactivity of single antigen beads for both HLA class I and HLA class II antibody panels. This assessment of antibody results identified several beads in both the HLA class I and HLA class II antibody panel which exhibit over reactivity from 2018 to the present time. CONCLUSIONS: PCA-derived analysis would be ideal to help automatically identify patient samples that have an HLA antibody pattern of reactivity consistent with their history and those which exhibit changes in their antibody patterns which could include donor-specific antibodies, de novo HLA antibodies, and assay interference. A similar method could also be applied to evaluate the over-reactivity of beads in the HLA solid phase assays which would be beneficial for lot comparisons and instructive for transplant centers to better understand which beads are more prone to exhibiting over-reactivity and impact patient care.

Allele-specific quantification of human leukocyte antigen transcript isoforms by nanopore sequencing.

Introduction: While tens of thousands of HLA alleles have been identified by DNA sequencing, the contribution of alternative splicing to HLA diversity is not well characterized. In this study, we sought to determine if long-read sequencing could be used to accurately quantify allele-specific HLA transcripts in primary human lymphocytes. Methods: cDNA libraries were prepared from peripheral blood lymphocytes from 12 donors and sequenced by nanopore long-read sequencing. HLA reads were aligned to donor-specific reference sequences based on the known type of each donor. Allele-specific exon utilization was calculated as the proportion of reads aligning to each allele containing known exons, and transcript isoforms were quantified based on patterns of exon utilization within individual reads. Results: Splice variants were rare among class I HLA genes (median exon retention rate 99%-100%), except for several HLA-C alleles with exon 5 spliced out of up to 15% of reads. Splice variants were also rare among class II HLA genes (median exon retention rate 98%-100%), except for HLA-DQB1. Consistent with previous work, exon 5 of HLA-DQB1 was spliced out in alleles with a mutated splice acceptor site at rs28688207. Surprisingly, a 28% loss of exon 5 was also observed in HLA-DQB1 alleles with an intact splice acceptor site at rs28688207. Discussion: We describe a simple bioinformatic workflow to quantify allele-specific expression of HLA transcript isoforms. Further studies are warranted to characterize the repertoire of HLA transcripts expressed in different cell types and tissues across diverse populations.

Unique Molecular Identifier-Based High-Resolution HLA Typing and Transcript Quantitation Using Long-Read Sequencing.

HLA typing provides essential results for stem cell and solid organ transplants, as well as providing diagnostic benefits for various rheumatology, gastroenterology, neurology, and infectious diseases. It is becoming increasingly clear that understanding the expression of patient HLA transcripts can provide additional benefits for many of these same patient groups. Our study cohort was evaluated using a long-read RNA sequencing methodology to provide rapid HLA genotyping results and normalized HLA transcript expression. Our assay used NGSEngine to determine the HLA genotyping result and normalized mRNA transcript expression using Athlon2. The assay demonstrated an excellent concordance rate of 99.7%. Similar to previous studies, for the class I loci, patients demonstrated significantly lower expression of HLA-C than HLA-A and -B (Mann-Whitney U, p value = 0.0065 and p value = 0.0154, respectively). In general, the expression of class II transcripts was lower than that of class I transcripts. This study demonstrates a rapid high-resolution HLA typing assay using RNA-Seq that can provide accurate HLA genotyping and HLA allele-specific transcript expression in 7-8 h, a timeline short enough to perform the assay for deceased donors.

Bilineal evolution of a U2AF1-mutated clone associated with acquisition of distinct secondary mutations.

Rare hematologic malignancies display evidence of both myeloid and lymphoid differentiation. Here, we describe such a novel bilineal event discovered in an adult woman with B-lymphoblastic leukemia (BLL). At the time of BLL diagnosis, the patient had a normal karyotype and a bulk sequencing panel identified pathogenic variants in BCOR, EZH2, RUNX1, and U2AF1, a genotype more typical of myeloid neoplasia. Additionally, the patient was noted to have 3-year history of cytopenias, and morphologic dyspoiesis was noted on post-treatment samples, raising the possibility of an antecedent hematologic disorder. To investigate the clonal architecture of her disease, we performed targeted sequencing on fractionated samples enriched for either B-lymphoblasts or circulating granulocytes. These studies revealed a truncal founder mutation in the spliceosome gene U2AF1 in both fractions, while distinct secondary mutations were present only in B-lymphoblasts (BCOR, NRAS) or myeloid cells (ASXL1, EZH2, RUNX1). These results indicate that both processes evolved from a common U2AF1-mutated precursor, which then acquired additional mutations during a process of divergent evolution and bilineal differentiation. Our findings highlight an atypical mechanism of BLL leukemogenesis and demonstrate the potential utility of fractionated sequencing in the characterization of acute leukemia.

Next-generation sequencing and clinical histocompatibility testing.

Histocompatibility testing is essential for donor identification and risk assessment in solid organ and hematopoietic stem cell transplant. Additionally, it is useful for identifying donor specific alleles for monitoring donor specific antibodies in post-transplant patients. Next-generation sequence (NGS) based human leukocyte antigen (HLA) typing has improved many aspects of histocompatibility testing in hematopoietic stem cell and solid organ transplant. HLA disease association testing and research has also benefited from the advent of NGS technologies. In this review we discuss the current impact and future applications of NGS typing on clinical histocompatibility testing for transplant and non-transplant purposes.

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.

Influence of Germline Genetics on Tacrolimus Pharmacokinetics and Pharmacodynamics in Allogeneic Hematopoietic Stem Cell Transplant Patients.

Tacrolimus exhibits high inter-patient pharmacokinetics (PK) variability, as well as a narrow therapeutic index, and therefore requires therapeutic drug monitoring. Germline mutations in cytochrome P450 isoforms 4 and 5 genes (CYP3A4/5) and the ATP-binding cassette B1 gene (ABCB1) may contribute to interindividual tacrolimus PK variability, which may impact clinical outcomes among allogeneic hematopoietic stem cell transplantation (HSCT) patients. In this study, 252 adult patients who received tacrolimus for acute graft versus host disease (aGVHD) prophylaxis after allogeneic HSCT were genotyped to evaluate if germline genetic variants associated with tacrolimus PK and pharmacodynamic (PD) variability. Significant associations were detected between germline variants in CYP3A4/5 and ABCB1 and PK endpoints (e.g., median steady-state tacrolimus concentrations and time to goal tacrolimus concentration). However, significant associations were not observed between CYP3A4/5 or ABCB1 germline variants and PD endpoints (e.g., aGVHD and treatment-emergent nephrotoxicity). Decreased age and CYP3A5*1/*1 genotype were independently associated with subtherapeutic tacrolimus trough concentrations while CYP3A5*1*3 or CYP3A5*3/*3 genotypes, myeloablative allogeneic HSCT conditioning regimen (MAC) and increased weight were independently associated with supratherapeutic tacrolimus trough concentrations. Future lines of prospective research inquiry are warranted to use both germline genetic and clinical data to develop precision dosing tools that will optimize both tacrolimus dosing and clinical outcomes among adult HSCT patients.

Using Nanopore Whole-Transcriptome Sequencing for Human Leukocyte Antigen Genotyping and Correlating Donor Human Leukocyte Antigen Expression with Flow Cytometric Crossmatch Results.

Transplant centers are increasingly using virtual crossmatching to evaluate recipient and donor compatibility. However, the current state of virtual crossmatching fails to incorporate donor human leukocyte antigen (HLA) expression in the assessment, despite numerous studies that have demonstrated the impact of donor HLA expression on physical crossmatch outcomes. Whole-transcriptome sequencing (RNA-Seq) for HLA enables simultaneous determination of HLA genotyping and relative HLA expression. Ultimately the RNA-Seq needs to be faster to be incorporated into the virtual crossmatching process. However, to demonstrate feasibility, the utility of the MinION sequencer (Oxford Nanopore Technologies, Oxford, UK) was evaluated in combination with RNA-Seq to generate HLA genotypes and to determine HLA class I expression. Although HLA class I expression varied among individuals, the pattern of HLA expression remained relatively consistent (HLA-B > HLA-A = HLA-C). HLA-A and -C had similar expression profiles. The impact of donor HLA expression was evaluated using serum samples containing a single donor-specific antibody (DSA). By making DSA consistent, donor HLA expression variability could be assessed. With consistent DSA mean fluorescence intensity, there was a direct relationship between the donor HLA expression to which the DSA is against and flow cytometric crossmatch median channel shifts.

Development of data-driven models for the flow cytometric crossmatch.

HLA laboratories use virtual crossmatching (VXM) to predict recipient and donor compatibility using HLA antibody data and donor HLA type. Increasingly, transplant centers are utilizing VXM as the final compatibility determination prior to transplant. However, the VXM interpretation is based on HLA experience of individual transplant centers. This study developed data-driven algorithms that predicted flow cytometric crossmatch (FCXM) outcomes using HLA antibody mean fluorescent intensity (MFI) data and donor HLA typing without the need for human interpretation.Two algorithms were evaluated; an MFI Optimal-Threshold model and a Least-Squares-Fitting model. The Optimal-Threshold model correctly determined between 81.5% and 85.5% of T or B-cell responses. A class I antibody MFI threshold of 4670 was optimal for predicting T-cell response while an antibody MFI threshold of 6180 was optimal for predicting B-cell responses. HLA class I antibodies had a 1.47-fold greater influence on FCXM outcomes than class II antibodies. HLA-B antibodies influenced T and B-cell responses more than HLA-A or -C (-B > -A > -C). The Least-Squares-Fitting model increased accuracy to 94.1% and 88.8% for T and B-cell responses, respectively. The algorithms described here provide enhanced FCXM prediction and novel insights into the influence of specific HLA antibodies on the crossmatch outcome.

HLA alleles and haplotypes observed in 263 US families.

The 17th International HLA and Immunogenetics Workshop (IHIW) conducted a project entitled "The Study of Haplotypes in Families by NGS HLA". We investigated the HLA haplotypes of 1017 subjects in 263 nuclear families sourced from five US clinical immunogenetics laboratories, primarily as part of the evaluation of related donor candidates for hematopoietic stem cell and solid organ transplantation. The parents in these families belonged to five broad groups - African (72 parents), Asian (115), European (210), Hispanic (118) and "Other" (11). High-resolution HLA genotypes were generated for each subject using next-generation sequencing (NGS) HLA typing systems. We identified the HLA haplotypes in each family using HaplObserve, software that builds haplotypes in families by reviewing HLA allele segregation from parents to children. We calculated haplotype frequencies within each broad group, by treating the parents in each family as unrelated individuals. We also calculated standard measures of global linkage disequilibrium (LD) and conditional asymmetric LD for each ethnic group, and used untruncated and two-field allele names to investigate LD patterns. Finally we demonstrated the utility of consensus DNA sequences in identifying novel variants, confirming them using HLA allele segregation at the DNA sequence level.

Suitability of dried DNA for long-range PCR amplification and HLA typing by next-generation sequencing.

Storage and stable shipment of genomic DNA are of great concern to laboratories that may need to perform testing off archived samples. There are some dry-state storage methods that are available that have the potential to provide a way to store samples at room temperature for long periods of time as well as offer a means to ship DNA to other facilities without the same safety concerns that come with shipping liquid samples. The recovered DNA should be of sufficient integrity such that downstream applications can be performed without concern of the sample quality. This work describes sample properties between two methods of DNA storage, dried (room temperature) and traditional (-80 °C). DNA was evaluated for purity, fragment length, and the ability to generate HLA typing using next-generation sequencing.

Characteristics, properties, and potential applications of circulating cell-free dna in clinical diagnostics: a focus on transplantation.

The initial discovery of cell-free DNA (cfDNA) in 1948 by Mandel and Metais has led to numerous investigations evaluating the role of cfDNA in various disease states. cfDNA has been characterized in various patient populations with similar results. cfDNA are typically 150 bp of double-stranded DNA that are thought to be released from nucleosomes during apoptosis and necrosis. They are found in circulation as monomers, dimers, and trimers. Different specimen types yield significantly different amounts cfDNA. While serum yields the highest amount of cfDNA, it contains the most genomic DNA contamination compared to Streck and plasma specimen types. The utility of cfDNA as a biomarker was advanced by the completion of the Human Genome Project and enabled interrogation of tumor markers in cancer patients. While tumor genetics may have been the initial application of cfDNA, the most successful application of cfDNA as a clinical biomarker is noninvasive prenatal testing (NIPT). CfDNA has become the gold-standard for NIPT testing, allowing for high sensitivity while maintaining specificity for aneuploidy. Because prenatal testing is essentially mixed genome analysis, application of cfDNA analysis to solid organ transplantation is a clear diagnostic target. There have been several studies examining the role of cfDNA in solid organ transplantation. These studies identified cfDNA as a surrogate marker for rejection with a high level of concordance with biopsies. While the data thus far are promising, there is still a need for more prospective studies to determine the clinical utility of cfDNA in solid organ transplant rejection.

The Past, Present, and Future of HLA Typing in Transplantation.

The HLA region is the most polymorphic genes in the human genome and is associated with an increasing number of disease states. Historically, HLA typing methodology has been governed by phenotypic determination. This practice has evolved into the use of molecular methods such as real-time PCR, sequence-specific oligonucleotides, and sequencing-based methods. Numerous studies have identified HLA matching as a key determinate to improve patient outcomes from transplantation. Solid-organ transplants focus on HLA-DRB1 in renal organ allocation while hematopoietic cell transplants focus on HLA-A, -B, -C, -DRB1 matching. The role of HLA typing in the future will be driven by HLA expression, understanding of HLA haplotypes, and rapid HLA typing.

HLAProfiler utilizes k-mer profiles to improve HLA calling accuracy for rare and common alleles in RNA-seq data.

BACKGROUND: The human leukocyte antigen (HLA) system is a genomic region involved in regulating the human immune system by encoding cell membrane major histocompatibility complex (MHC) proteins that are responsible for self-recognition. Understanding the variation in this region provides important insights into autoimmune disorders, disease susceptibility, oncological immunotherapy, regenerative medicine, transplant rejection, and toxicogenomics. Traditional approaches to HLA typing are low throughput, target only a few genes, are labor intensive and costly, or require specialized protocols. RNA sequencing promises a relatively inexpensive, high-throughput solution for HLA calling across all genes, with the bonus of complete transcriptome information and widespread availability of historical data. Existing tools have been limited in their ability to accurately and comprehensively call HLA genes from RNA-seq data. RESULTS: We created HLAProfiler ( https://github.com/ExpressionAnalysis/HLAProfiler ), a k-mer profile-based method for HLA calling in RNA-seq data which can identify rare and common HLA alleles with > 99% accuracy at two-field precision in both biological and simulated data. For 68% of novel alleles not present in the reference database, HLAProfiler can correctly identify the two-field precision or exact coding sequence, a significant advance over existing algorithms. CONCLUSIONS: HLAProfiler allows for accurate HLA calls in RNA-seq data, reliably expanding the utility of these data in HLA-related research and enabling advances across a broad range of disciplines. Additionally, by using the observed data to identify potential novel alleles and update partial alleles, HLAProfiler will facilitate further improvements to the existing database of reference HLA alleles. HLAProfiler is available at https://expressionanalysis.github.io/HLAProfiler/ .

Buccal swab genomic DNA fragmentation predicts likelihood of successful HLA genotyping by next-generation sequencing.

Many clinical human leukocyte antigen (HLA) laboratories are adopting next-generation sequencing (NGS) technology for HLA genotyping. There have been several reports of the cost-benefit and reduction in turn-around-time provided by NGS. Ninety-six percent of buccal swabs and peripheral blood samples had reportable HLA genotyping by NGS. The HLA loci most likely to fail genotyping from buccal swabs were DQB1, DPB1, and DPA1. Successful buccal swab samples had significantly less genomic DNA fragmentation compared to buccal swab samples that were unsuccessful. Increasing sequencing depth of coverage for heavily fragmented samples rescued HLA genotyping. This information provides laboratories with a quality assurance parameter that reduces the amount of repeat NGS needed to achieve high-resolution HLA genotyping. This information should further reduce laboratory and patient costs for HLA genotyping.

C1q Test for Identification of Sensitized Liver Recipients at Risk of Early Acute Antibody-Mediated Rejection.

BACKGROUND The majority of liver recipients transplanted with positive crossmatch have a post-transplant course free of acute antibody-mediated rejection (AMR). However, 10% of sensitized recipients develop early severe AMR. There is no clear strategy that would allow for predicting the postoperative course in sensitized liver recipients. One of the possible factors contributing to the dichotomous course in sensitized recipients may be the complement-binding characteristics of the donor-specific antibodies (DSA). MATERIAL AND METHODS We tested sera of sensitized recipients with DSA at the time of transplant, diagnosed with severe AMR or 'AMR-free' for C1q reactivity and strength of mean fluorescence intensity (MFI) in single-antigen beads (SAB) assay. RESULTS Both groups tested positive for DSA C1q binding and DSA-SAB. Recipients with early AMR had significantly stronger DSA MFI in the C1q assay (P<.0001). AMR was observed in patients with very high DSA C1q MFI (22681±8841 vs. the no-AMR group 7954±2061). In SAB assay, DSA MFI strength differences were equivocal (P=0.31). CONCLUSIONS The C1q test is a supportive adjunct in identifying patients at risk of postoperative acute AMR and selects an AMR-free course with 100% negative predictive value despite the presence of DSA.

Performance Characteristics and Validation of Next-Generation Sequencing for Human Leucocyte Antigen Typing.

High-resolution human leukocyte antigen (HLA) matching reduces graft-versus-host disease and improves overall patient survival after hematopoietic stem cell transplant. Sanger sequencing has been the gold standard for HLA typing since 1996. However, given the increasing number of new HLA alleles identified and the complexity of the HLA genes, clinical HLA typing by Sanger sequencing requires several rounds of additional testing to provide allele-level resolution. Although next-generation sequencing (NGS) is routinely used in molecular genetics, few clinical HLA laboratories use the technology. The performance characteristics of NGS HLA typing using TruSight HLA were determined using Sanger sequencing as the reference method. In total, 211 samples were analyzed with an overall accuracy of 99.8% (2954/2961) and 46 samples were analyzed for precision with 100% (368/368) reproducibility. Most discordant alleles were because of technical error rather than assay performance. More important, the ambiguity rate was 3.5% (103/2961). Seventy-four percentage of the ambiguities were within the DRB1 and DRB4 loci. HLA typing by NGS saves approximately $6000 per run when compared to Sanger sequencing. Thus, TruSight HLA assay enables high-throughput HLA typing with an accuracy, precision, ambiguity rate, and cost savings that should facilitate adoption of NGS technology in clinical HLA laboratories.

Clinical validation of NGS technology for HLA: An early adopter's perspective.

Clinical validation of NGS for HLA typing has been a topic of interest with many laboratories investigating the merits. NGS has proven effective at reducing ambiguities and costs while providing more detailed information on HLA genes not previously sequenced. The ability of NGS to multiplex many patients within a single run presents unique challenges and sequencing new regions of HLA genes requires application of our knowledge of genetics to accurately determine HLA typing. This review represents my laboratory's experience in validation of NGS for HLA typing. It describes the obstacles faced with validation of NGS and is broken down into pre-analytic, analytic, and post-analytic challenges. Each section includes solutions to address them.