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.

BACKGROUND: The HLA-DRB1 gene in the major histocompatibility complex (MHC) region in chromosome 6p21 is the strongest genetic factor identified as influencing multiple sclerosis (MS) susceptibility. DNA methylation changes associated with MS have been consistently detected at the MHC region. However, understanding the full scope of epigenetic regulations of the MHC remains incomplete, due in part to the limited coverage of this region by standard whole genome bisulfite sequencing or array-based methods. METHODS: We developed and validated an MHC capture protocol coupled with bisulfite sequencing and conducted a comprehensive analysis of the MHC methylation landscape in blood samples from 147 treatment naïve MS study participants and 129 healthy controls. RESULTS: We identified 132 differentially methylated region (DMRs) within MHC region associated with disease status. The DMRs overlapped with established MS risk loci. Integration of the MHC methylome with human leukocyte antigen (HLA) genetic data indicate that the methylation changes are significantly associated with HLA genotypes. Using DNA methylation quantitative trait loci (mQTL) mapping and the causal inference test (CIT), we identified 643 cis-mQTL-DMRs paired associations, including 71 DMRs possibly mediating causal relationships between 55 single nucleotide polymorphisms (SNPs) and MS risk. RESULTS: The results describe MS-associated methylation changes in MHC region and highlight the association between HLA genotypes and methylation changes. Results from the mQTL and CIT analyses provide evidence linking MHC region variations, methylation changes, and disease risk for MS.

The human leukocyte antigen (HLA) genes are extremely polymorphic and are useful molecular markers to make inferences about human population history. However, the accuracy of the estimation of genetic diversity at HLA loci very much depends on the technology used to characterize HLA alleles; high-resolution genotyping of long-range HLA gene products improves the assessment of HLA population diversity as well as other population parameters compared to lower resolution typing methods. In this study we examined allelic and haplotype HLA diversity in a large healthy European American population sourced from the UCSF-DNA bank. A high-resolution next-generation sequencing method was applied to define non-ambiguous 3- and 4-field alleles at the HLA-A, HLA-C, HLA-B, HLA-DRB1, HLA-DRB3/4/5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1 loci in samples provided by 2248 unrelated individuals. A number of population parameters were examined including balancing selection and various measurements of linkage disequilibrium were calculated. There were no detectable deviations from Hardy-Weinberg proportions at HLA-A, HLA-DRB1, HLA-DQA1 and HLA-DQB1. For the remaining loci moderate and significant deviations were detected at HLA-C, HLA-B, HLA-DRB3/4/5, HLA-DPA1 and HLA-DPB1 loci mostly from population substructures. Unique 4-field associations were observed among alleles at 2 loci and haplotypes extending large intervals that were not apparent in results obtained using testing methodologies with limited sequence coverage and phasing. The high diversity at HLA-DPA1 results from detection of intron variants of otherwise well conserved protein sequences. It may be speculated that divergence in exon sequences may be negatively selected. Our data provides a valuable reference source for future population studies that may allow for precise fine mapping of coding and non-coding sequences determining disease susceptibility and allo-immunogenicity.

The KIR (killer-cell immunoglobulin-like receptor) region is characterized by structural variation and high sequence similarity among genes, imposing technical difficulties for analysis. We undertook the most comprehensive study to date of KIR genetic diversity in a large population sample, applying next-generation sequencing in 2,130 United States European-descendant individuals. Data were analyzed using our custom bioinformatics pipeline specifically designed to address technical obstacles in determining KIR genotypes. Precise gene copy number determination allowed us to identify a set of uncommon gene-content KIR haplotypes accounting for 5.2% of structural variation. In this cohort, KIR2DL4 is the framework gene that most varies in copy number (6.5% of all individuals). We identified phased high-resolution alleles in large multi-locus insertions and also likely founder haplotypes from which they were deleted. Additionally, we observed 250 alleles at 5-digit resolution, of which 90 have frequencies ≥1%. We found sequence patterns that were consistent with the presence of novel alleles in 398 (18.7%) individuals and contextualized multiple orphan dbSNPs within the KIR complex. We also identified a novel KIR2DL1 variant, Pro151Arg, and demonstrated by molecular dynamics that this substitution is predicted to affect interaction with HLA-C. No previous studies have fully explored the full range of structural and sequence variation of KIR as we present here. We demonstrate that pairing high-throughput sequencing with state-of-art computational tools in a large cohort permits exploration of all aspects of KIR variation including determination of population-level haplotype diversity, improving understanding of the KIR system, and providing an important reference for future studies.

Multiple sclerosis (MS) susceptibility shows strong genetic associations with HLA alleles and haplotypes. We genotyped 11 HLA genes in 477 non-Hispanic European MS patients and their 954 unaffected parents using a validated next-generation sequencing (NGS) methodology. HLA haplotypes were assigned unequivocally by tracing HLA allele transmissions. We explored HLA haplotype/allele associations with MS using the genotypic transmission disequilibrium test (gTDT) and multiallelic TDT (mTDT). We also conducted a case-control (CC) study with all patients and 2029 healthy unrelated ethnically matched controls. We performed separate analyses of 54 extended multi-case families by reviewing transmission of haplotype blocks. The haplotype fragment including DRB5*01:01:01~DRB1*15:01:01:01 was significantly associated with predisposition (gTDT: p < 2.20e-16; mTDT: p =1.61e-07; CC: p < 2.22e-16) as reported previously. A second risk allele, DPB1*104:01 (gTDT: p = 3.69e-03; mTDT: p = 2.99e-03; CC: p = 1.00e-02), independent from the haplotype bearing DRB1*15:01 was newly identified. The allele DRB1*01:01:01 showed significant protection (gTDT: p = 8.68e-06; mTDT: p = 4.50e-03; CC: p = 1.96e-06). Two DQB1 alleles, DQB1*03:01 (gTDT: p = 2.86e-03; mTDT: p = 5.56e-02; CC: p = 4.08e-05) and DQB1*03:03 (gTDT: p = 1.17e-02; mTDT: p = 1.16e-02; CC: p = 1.21e-02), defined at two-field level also showed protective effects. The HLA class I block, A*02:01:01:01~C*03:04:01:01~B*40:01:02 (gTDT: p = 5.86e-03; mTDT: p = 3.65e-02; CC: p = 9.69e-03) and the alleles B*27:05 (gTDT: p = 6.28e-04; mTDT: p = 2.15e-03; CC: p = 1.47e-02) and B*38:01 (gTDT: p = 3.20e-03; mTDT: p = 6.14e-03; CC: p = 1.70e-02) showed moderately protective effects independently from each other and from the class II associated factors. By comparing statistical significance of 11 HLA loci and 19 haplotype segments with both untruncated and two-field allele names, we precisely mapped MS candidate alleles/haplotypes while eliminating false signals resulting from 'hitchhiking' alleles. We assessed genetic burden for the HLA allele/haplotype identified in this study. This family-based study including the highest-resolution of HLA alleles proved to be powerful and efficient for precise identification of HLA genotypes associated with both, susceptibility and protection to development of MS.

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.

OBJECTIVES: Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe, delayed hypersensitivity reaction (DHR). We observed DRESS to inhibitors of interleukin 1 (IL-1) or IL-6 in a small group of patients with Stills disease with atypical lung disease. We sought to characterise features of patients with Stills disease with DRESS compared with drug-tolerant Stills controls. We analysed human leucocyte antigen (HLA) alleles for association to inhibitor-related DHR, including in a small Kawasaki disease (KD) cohort. METHODS: In a case/control study, we collected a multicentre series of patients with Stills disease with features of inhibitor-related DRESS (n=66) and drug-tolerant Stills controls (n=65). We retrospectively analysed clinical data from all Stills subjects and typed 94/131 for HLA. European Stills-DRESS cases were ancestry matched to International Childhood Arthritis Genetics Consortium paediatric Stills cases (n=550) and compared for HLA allele frequencies. HLA association also was analysed using Stills-DRESS cases (n=64) compared with drug-tolerant Stills controls (n=30). KD subjects (n=19) were similarly studied. RESULTS: Stills-DRESS features included eosinophilia (89%), AST-ALT elevation (75%) and non-evanescent rash (95%; 88% involving face). Macrophage activation syndrome during treatment was frequent in Stills-DRESS (64%) versus drug-tolerant Stills (3%; p=1.2×10-14). We found striking enrichment for HLA-DRB1*15 haplotypes in Stills-DRESS cases versus INCHARGE Stills controls (p=7.5×10-13) and versus self-identified, ancestry-matched Stills controls (p=6.3×10-10). In the KD cohort, DRB1*15:01 was present only in those with suspected anakinra reactions. CONCLUSIONS: DRESS-type reactions occur among patients treated with IL-1/IL-6 inhibitors and strongly associate with common HLA-DRB1*15 haplotypes. Consideration of preprescription HLA typing and vigilance for serious reactions to these drugs are warranted.

Immune dysfunction plays a role in the development of Parkinson disease (PD). NK cells regulate immune functions and are modulated by killer cell immunoglobulin-like receptors (KIR). KIR are expressed on the surface of NK cells and interact with HLA class I ligands on the surface of all nucleated cells. We investigated KIR-allelic polymorphism to interrogate the role of NK cells in PD. We sequenced KIR genes from 1314 PD patients and 1978 controls using next-generation methods and identified KIR genotypes using custom bioinformatics. We examined associations of KIR with PD susceptibility and disease features, including age at disease onset and clinical symptoms. We identified two KIR3DL1 alleles encoding highly expressed inhibitory receptors associated with protection from PD clinical features in the presence of their cognate ligand: KIR3DL1*015/HLA-Bw4 from rigidity (p _c = 0.02, odds ratio [OR] = 0.39, 95% confidence interval [CI] 0.23-0.69) and KIR3DL1*002/HLA-Bw4i from gait difficulties (p _c = 0.05, OR = 0.62, 95% CI 0.44-0.88), as well as composite symptoms associated with more severe disease. We also developed a KIR3DL1/HLA interaction strength metric and found that weak KIR3DL1/HLA interactions were associated with rigidity (p_c = 0.05, OR = 9.73, 95% CI 2.13-172.5). Highly expressed KIR3DL1 variants protect against more debilitating symptoms of PD, strongly implying a role of NK cells in PD progression and manifestation.

The primary goal of the unrelated population HLA diversity (UPHD) component of the 17th International HLA and Immunogenetics Workshop was to characterize HLA alleles at maximum allelic-resolution in worldwide populations and re-evaluate patterns of HLA diversity across populations. The UPHD project included HLA genotype and sequence data, generated by various next-generation sequencing methods, from 4,240 individuals collated from 12 different countries. Population data included well-defined large datasets from the USA and smaller samples from Europe, Australia, and Western Asia. Allele and haplotype frequencies varied across populations from distant geographical regions. HLA genetic diversity estimated at 2- and 4-field allelic resolution revealed that diversity at the majority of loci, particularly for European-descent populations, was lower at the 2-field resolution. Several common alleles with identical protein sequences differing only by intronic substitutions were found in distinct haplotypes, revealing a more detailed characterization of linkage between variants within the HLA region. The examination of coding and non-coding nucleotide variation revealed many examples in which almost complete biunivocal relations between common alleles at different loci were observed resulting in higher linkage disequilibrium. Our reference data of HLA profiles characterized at maximum resolution from many populations is useful for anthropological studies, unrelated donor searches, transplantation, and disease association studies.

Parkinson's disease (PD) is a neurodegenerative disease in which genetic risk has been mapped to HLA, but precise allelic associations have been difficult to infer due to limitations in genotyping methodology. Mapping PD risk at highest possible resolution, we performed sequencing of 11 HLA genes in 1,597 PD cases and 1,606 controls. We found that susceptibility to PD can be explained by a specific combination of amino acids at positions 70-74 on the HLA-DRB1 molecule. Previously identified as the primary risk factor in rheumatoid arthritis and referred to as the "shared epitope" (SE), the residues Q/R-K/R-R-A-A at positions 70-74 in combination with valine at position 11 (11-V) is highly protective in PD, while risk is attributable to the identical epitope in the absence of 11-V. Notably, these effects are modified by history of cigarette smoking, with a strong protective effect mediated by a positive history of smoking in combination with the SE and 11-V (P = 10-4; odds ratio, 0.51; 95% confidence interval, 0.36-0.72) and risk attributable to never smoking in combination with the SE without 11-V (P = 0.01; odds ratio, 1.51; 95% confidence interval, 1.08-2.12). The association of specific combinations of amino acids that participate in critical peptide-binding pockets of the HLA class II molecule implicates antigen presentation in PD pathogenesis and provides further support for genetic control of neuroinflammation in disease. The interaction of HLA-DRB1 with smoking history in disease predisposition, along with predicted patterns of peptide binding to HLA, provide a molecular model that explains the unique epidemiology of smoking in PD.