HLA Haplotype Validator for quality assessments of HLA typing

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Challenges for the standardized reporting of NGS HLA genotyping: Surveying gaps between clinical and research laboratories

Next generation sequencing (NGS) is being applied for HLA typing in research and clinical settings. NGS HLA typing has made it feasible to sequence exons, introns and untranslated regions simultaneously, with significantly reduced labor and reagent cost per sample, rapid turnaround time, and improved HLA genotype accuracy. NGS technologies bring challenges for cost-effective computation, data processing and exchange of NGS-based HLA data. To address these challenges, guidelines and specifications such as Genotype List (GL) String, Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING), and Histoimmunogenetics Markup Language (HML) were proposed to streamline and standardize reporting of HLA genotypes. As part of the 17th International HLA and Immunogenetics Workshop (IHIW), we implemented standards and systems for HLA genotype reporting that included GL String, MIRING and HML, and found that misunderstanding or misinterpretations of these standards led to inconsistencies in the reporting of NGS HLA genotyping results. This may be due in part to a historical lack of centralized data reporting standards in the histocompatibility and immunogenetics community. We have worked with software and database developers, clinicians and scientists to address these issues in a collaborative fashion as part of the Data Standard Hackathons (DaSH) for NGS. Here we report several categories of challenges to the consistent exchange of NGS HLA genotyping data we have observed. We hope to address these challenges in future DaSH for NGS efforts.

The changing landscape of HLA typing: Understanding how and when HLA typing data can be used with confidence from bench to bedside

Human leukocyte antigen (HLA) genes are extraordinary for their extreme diversity and widespread impact on human health and disease. More than 30,000 HLA alleles have been officially named and more alleles continue to be discovered at a rapid pace. HLA typing systems which have been developed to detect HLA diversity have advanced rapidly and are revolutionizing our understanding of HLA's clinical importance. However, continuous improvements in knowledge and technology have created challenges for clinicians and scientists. This review explains how differences in HLA typing systems can impact the HLA types that are assigned. The consequences of differences in laboratory testing methods and reference databases are described. The challenges of using HLA types that are not equivalent are illustrated. A fundamental understanding of the continual expansion of our understanding of HLA diversity and limitations in some of the typing data is essential for using typing data appropriately in clinical and research settings.

The combinatorial diversity of KIR and HLA class I allotypes in Peninsular Malaysia

Killer cell immunoglobulin-like receptors (KIRs) interact with polymorphic human leucocyte antigen (HLA) class I molecules, modulating natural killer (NK) cell functions and affecting both the susceptibility and outcome of immune-mediated diseases. The KIR locus is highly diverse in gene content, copy number and allelic polymorphism within individuals and across geographical populations. To analyse currently under-represented Asian and Pacific populations, we investigated the combinatorial diversity of KIR and HLA class I in 92 unrelated Malay and 75 Malaysian Chinese individuals from the Malay Peninsula. We identified substantial allelic and structural diversity of the KIR locus in both populations and characterized novel variations at each analysis level. The Malay population is more diverse than Malay Chinese, likely representing a unique history including admixture with immigrating populations spanning several thousand years. Characterizing the Malay population are KIR haplotypes with large structural variants present in 10% individuals, and KIR and HLA alleles previously identified in Austronesian populations. Despite the differences in ancestries, the proportion of HLA allotypes that serve as KIR ligands is similar in each population. The exception is a significantly reduced frequency of interactions of KIR2DL1 with C2+ HLA-C in the Malaysian Chinese group, caused by the low frequency of C2+ HLA. One likely implication is a greater protection from preeclampsia, a pregnancy disorder associated with KIR2DL1, which shows higher incidence in the Malay than in the Malaysian Chinese. This first complete, high-resolution, characterization of combinatorial diversity of KIR and HLA in Malaysians will form a valuable reference for future clinical and population studies.

High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.

HLA Haplotypes In 250 Families: The Baylor Laboratory Results And A Perspective On A Core NGS Testing Model For The 17th International HLA And Immunogenetics Workshop

Since their inception, the International HLA & Immunogenetics Workshops (IHIW) served as a collaborative platform for exchange of specimens, reference materials, experiences and best practices. In this report we present a subset of the results of human leukocyte antigen (HLA) haplotypes in families tested by next generation sequencing (NGS) under the 17th IHIW. We characterized 961 haplotypes in 921 subjects belonging to 250 families from 8 countries (Argentina, Austria, Egypt, Jamaica, Germany, Greece, Kuwait, and Switzerland). These samples were tested in a single core laboratory in a high throughput fashion using 6 different reagents/software platforms. Families tested included patients evaluated clinically as transplant recipients (kidney and hematopoietic cell transplant) and their respective family members. We identified 486 HLA alleles at the following loci HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, -DPB1 (77, 115, 68, 69, 10, 6, 4, 44, 31, 20 and 42 alleles, respectively). We also identified nine novel alleles with polymorphisms in coding regions. This approach of testing samples from multiple laboratories across the world in different stages of technology implementation in a single core laboratory may be useful for future international workshops. Although data presented may not be reflective of allele and haplotype frequencies in the countries to which the families belong, they represent an extensive collection of 3rd and 4th field resolution level 11-locus haplotype associations of 486 alleles identified in families from 8 countries.

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.

Tools for building, analyzing and evaluating HLA haplotypes from families

The highly polymorphic classical human leukocyte antigen (HLA) genes display strong linkage disequilibrium (LD) that results in conserved multi-locus haplotypes. For unrelated individuals in defined populations, HLA haplotype frequencies can be estimated using the expectation-maximization (EM) method. Haplotypes can also be constructed using HLA allele segregation from nuclear families. It is straightforward to identify many HLA genotyping inconsistencies by visually reviewing HLA allele segregation in family members. It is also possible to identify potential crossover events when two or more children are available in a nuclear family. This process of visual inspection can be unwieldy, and we developed the "HaplObserve" program to standardize the process and automatically build haplotypes using family-based HLA allele segregation. HaplObserve facilitates systematically building haplotypes, and reporting potential crossover events. HLA Haplotype Validator (HLAHapV) is a program originally developed to impute chromosomal phase from genotype data using reference haplotype data. We updated and adapted HLAHapV to systematically compare observed and estimated haplotypes. We also used HLAHapV to identify haplotypes when uninformative HLA genotypes are present in families. Finally, we developed "pould", an R package that calculates haplotype frequencies, and estimates standard measures of global (locus-level) LD from both observed and estimated haplotypes.

Using Exome and Amplicon-Based Sequencing Data for High-Resolution HLA Typing with ATHLATES

ATHLATES (accurate typing of human leukocyte antigen through exome sequencing) was originally developed to analyze whole-exome sequencing (exome-seq) data from the Illumina platform and to predict the HLA genotype at 2-field or higher resolution. HLA locus-specific reads are first collected by stringent read mapping to the IMGT/HLA database. ATHLATES then performs read assembly, candidate allele identification, and genotype inference. Here, we describe the protocol of using ATHLATES for the above purpose and expand the application to analyze targeted sequencing data using amplicons of full HLA genes.

Computational Approaches to Facilitate Epitope-Based HLA Matching in Solid Organ Transplantation

Epitope-based HLA matching has been emerged over the last few years as an improved method for HLA matching in solid organ transplantation. The epitope-based matching concept has been incorporated in both the PIRCHE-II and the HLAMatchmaker algorithm to find the most suitable donor for a recipient. For these algorithms, high-resolution HLA genotype data of both donor and recipient is required. Since high-resolution HLA genotype data is often not available, we developed a computational method which allows epitope-based HLA matching from serological split level HLA typing relying on HLA haplotype frequencies. To validate this method, we simulated a donor-recipient population for which PIRCHE-II and eplet values were calculated when using both high-resolution HLA genotype data and serological split level HLA typing. The majority of the serological split level HLA-determined ln(PIRCHE-II)/ln(eplet) values did not or only slightly deviate from the reference group of high-resolution HLA-determined ln(PIRCHE-II)/ln(eplet) values. This deviation was slightly increased when HLA-C or HLA-DQ was omitted from the input and was substantially decreased when using two-field resolution HLA genotype data of the recipient and serological split level HLA typing of the donor. Thus, our data suggest that our computational approach is a powerful tool to estimate PIRCHE-II/eplet values when high-resolution HLA genotype data is not available.

A comparative reference study for the validation of HLA-matching algorithms in the search for allogeneic hematopoietic stem cell donors and cord blood units

The accuracy of human leukocyte antigen (HLA)‐matching algorithms is a prerequisite for the correct and efficient identification of optimal unrelated donors for patients requiring hematopoietic stem cell transplantation. The goal of this World Marrow Donor Association study was to validate established matching algorithms from different international donor registries by challenging them with simulated input data and subsequently comparing the output. This experiment addressed three specific aspects of HLA matching using different data sets for tasks of increasing complexity. The first two tasks targeted the traditional matching approach identifying discrepancies between patient and donor HLA genotypes by counting antigen and allele differences. Contemporary matching procedures predicting the probability for HLA identity using haplotype frequencies were addressed by the third task. In each task, the identified disparities between the results of the participating computer programs were analyzed, classified and quantified. This study led to a deep understanding of the algorithms participating and finally produced virtually identical results. The unresolved discrepancies total to less than 1%, 4% and 2% for the three tasks and are mostly because of individual decisions in the design of the programs. Based on these findings, reference results for the three input data sets were compiled that can be used to validate future matching algorithms and thus improve the quality of the global donor search process.