HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07)

OBJECTIVE

To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression.

RESULTS

First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression.

CONCLUSIONS

These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

KIR genotype and haplotype repertoire in Kuwaiti healthy donors, hematopoietic cell transplant recipients and healthy family members

The gene complex located on chromosome 19q13.4 encodes the Killer-cell Immunoglobulin-like Receptors (KIRs), which exhibit remarkable polymorphism in both gene content and sequences. Further, the repertoire of KIR genes varies within and between populations, creating a diverse pool of KIR genotypes. This study was carried out to characterize KIR genotypes and haplotypes among 379 Arab Kuwaiti individuals including 60 subjects from 20 trio families, 49 hematopoietic cell transplantation (HCT) recipients and 270 healthy Kuwaiti volunteer HCT donors. KIR Genotyping was performed by a combination of reverse sequence specific oligonucleotide probes (rSSO) and/or Real Time PCR. The frequencies of KIR genes in 270 healthy Kuwaiti volunteer donors were compared to previously reported frequencies in other populations. In addition, we compared the differences in KIR repertoire of patients and healthy donors to investigate the reproducibility of previously reported significant differences between patients with hematological malignancies and healthy donors. The observed frequencies in our cohort volunteer HCT donors was comparable to those reported in neighboring Arab populations. The activating genes KIR2DS1, KIR2DS5 and KIR3DS1 and the inhibitory gene KIR2DL5 were significantly more frequent in patients compared to healthy donors, however, none of the previously reported differences were reproducible in our Kuwaiti cohort. This report is the first description of KIR gene carrier frequency and haplotype characterization in a fairly large cohort of the Kuwaiti population, which may have implications in KIR based HCT donor selection strategies.

Trivalent mosaic or consensus HIV immunogens prime humoral and broader cellular immune responses in adults

BACKGROUNDMosaic and consensus HIV-1 immunogens provide two distinct approaches to elicit greater breadth of coverage against globally circulating HIV-1 and have shown improved immunologic breadth in nonhuman primate models.METHODSThis double-blind randomized trial enrolled 105 healthy HIV-uninfected adults who received 3 doses of either a trivalent global mosaic, a group M consensus (CON-S), or a natural clade B (Nat-B) gp160 env DNA vaccine followed by 2 doses of a heterologous modified vaccinia Ankara-vectored HIV-1 vaccine or placebo. We performed prespecified blinded immunogenicity analyses at day 70 and day 238 after the first immunization. T cell responses to vaccine antigens and 5 heterologous Env variants were fully mapped.RESULTSEnv-specific CD4+ T cell responses were induced in 71% of the mosaic vaccine recipients versus 48% of the CON-S recipients and 48% of the natural Env recipients. The mean number of T cell epitopes recognized was 2.5 (95% CI, 1.2-4.2) for mosaic recipients, 1.6 (95% CI, 0.82-2.6) for CON-S recipients, and 1.1 (95% CI, 0.62-1.71) for Nat-B recipients. Mean breadth was significantly greater in the mosaic group than in the Nat-B group using overall (P = 0.014), prime-matched (P = 0.002), heterologous (P = 0.046), and boost-matched (P = 0.009) measures. Overall T cell breadth was largely due to Env-specific CD4+ T cell responses.CONCLUSIONPriming with a mosaic antigen significantly increased the number of epitopes recognized by Env-specific T cells and enabled more, albeit still limited, cross-recognition of heterologous variants. Mosaic and consensus immunogens are promising approaches to address global diversity of HIV-1.TRIAL REGISTRATIONClinicalTrials.gov NCT02296541.FUNDINGUS NIH grants UM1 AI068614, UM1 AI068635, UM1 AI068618, UM1 AI069412, UL1 RR025758, P30 AI064518, UM1 AI100645, and UM1 AI144371, and Bill & Melinda Gates Foundation grant OPP52282.

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations

Importance

Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies.

Objective

To develop a haplotype-based artificial intelligence (HAI) model for identifying novel variants, including mixture variants (MVs) of known variants and new variants with novel mutations.

Design, Setting, and Participants

This cross-sectional study used serially observed viral genomic sequences globally (prior to March 14, 2022) to train and validate the HAI model and used it to identify variants arising from a prospective set of viruses from March 15 to May 18, 2022.

Main Outcomes and Measures

Viral sequences, collection dates, and locations were subjected to statistical learning analysis to estimate variant-specific core mutations and haplotype frequencies, which were then used to construct an HAI model to identify novel variants.

Results

Through training on more than 5 million viral sequences, an HAI model was built, and its identification performance was validated on an independent validation set of more than 5 million viruses. Its identification performance was assessed on a prospective set of 344 901 viruses. In addition to achieving an accuracy of 92.8% (95% CI within 0.1%), the HAI model identified 4 Omicron MVs (Omicron-Alpha, Omicron-Delta, Omicron-Epsilon, and Omicron-Zeta), 2 Delta MVs (Delta-Kappa and Delta-Zeta), and 1 Alpha-Epsilon MV, among which Omicron-Epsilon MVs were most frequent (609/657 MVs [92.7%]). Furthermore, the HAI model found that 1699 Omicron viruses had unidentifiable variants given that these variants acquired novel mutations. Lastly, 524 variant-unassigned and variant-unidentifiable viruses carried 16 novel mutations, 8 of which were increasing in prevalence percentages as of May 2022.

Conclusions and Relevance

In this cross-sectional study, an HAI model found SARS-COV-2 viruses with MV or novel mutations in the global population, which may require closer examination and monitoring. These results suggest that HAI may complement phylogenic variant assignment, providing additional insights into emerging novel variants in the population.

Rare, convergent antibodies targeting the stem helix broadly neutralize diverse betacoronaviruses

Humanity has faced three recent outbreaks of novel betacoronaviruses, emphasizing the need to develop approaches that broadly target coronaviruses. Here, we identify 55 monoclonal antibodies from COVID-19 convalescent donors that bind diverse betacoronavirus spike proteins. Most antibodies targeted an S2 epitope that included the K814 residue and were non-neutralizing. However, 11 antibodies targeting the stem helix neutralized betacoronaviruses from different lineages. Eight antibodies in this group, including the six broadest and most potent neutralizers, were encoded by IGHV1-46 and IGKV3-20. Crystal structures of three antibodies of this class at 1.5-1.75-Å resolution revealed a conserved mode of binding. COV89-22 neutralized SARS-CoV-2 variants of concern including Omicron BA.4/5 and limited disease in Syrian hamsters. Collectively, these findings identify a class of IGHV1-46/IGKV3-20 antibodies that broadly neutralize betacoronaviruses by targeting the stem helix but indicate these antibodies constitute a small fraction of the broadly reactive antibody response to betacoronaviruses after SARS-CoV-2 infection.

Alternative splicing and genetic variation of mhc-e: implications for rhesus cytomegalovirus-based vaccines

Rhesus cytomegalovirus (RhCMV)-based vaccination against Simian Immunodeficiency virus (SIV) elicits MHC-E-restricted CD8+ T cells that stringently control SIV infection in ~55% of vaccinated rhesus macaques (RM). However, it is unclear how accurately the RM model reflects HLA-E immunobiology in humans. Using long-read sequencing, we identified 16 Mamu-E isoforms and all Mamu-E splicing junctions were detected among HLA-E isoforms in humans. We also obtained the complete Mamu-E genomic sequences covering the full coding regions of 59 RM from a RhCMV/SIV vaccine study. The Mamu-E gene was duplicated in 32 (54%) of 59 RM. Among four groups of Mamu-E alleles: three ~5% divergent full-length allele groups (G1, G2, G2_LTR) and a fourth monomorphic group (G3) with a deletion encompassing the canonical Mamu-E exon 6, the presence of G2_LTR alleles was significantly (p = 0.02) associated with the lack of RhCMV/SIV vaccine protection. These genomic resources will facilitate additional MHC-E targeted translational research.

Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.37*10-4, 1.0*10-15, 4.76*10-7 and 1.56*10-4, respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p values < 1.0*10-15). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact remdesivir binding.

Genotyping of canine MHC gene DLA-88 by next-generation sequencing reveals high frequencies of new allele discovery and gene duplication

Dogs have served as one of the most reliable preclinical models for a variety of diseases and treatments, including stem/progenitor cell transplantation. At the genetic epicenter of dog transplantation models, polymorphic major histocompatibility complex (MHC) genes are most impactful on transplantation success. Among the canine class I and class II genes, DLA-88 has been best studied in transplantation matching and outcomes, with 129 DLA-88 alleles identified. In this study we developed and tested a next generation (NGS) sequencing protocol for rapid identification of DLA-88 genotypes in dogs and compared the workflow and data generated with an established DLA-88 Sanger sequencing protocol that has been in common prior use for clinical studies. By testing the NGS protocol on a random population of 382 dogs, it was possible to demonstrate superior efficacy based on laboratory execution and overall cost. In addition, NGS proved far more effective at discovering new alleles and detecting multiple alleles associated with gene duplication. A total of 51 new DLA-88 alleles are reported here. This rate of new allele discovery indicates that a large pool of yet un-discovered DLA-88 alleles exists in the domestic dog population. In addition, more than 46% of dogs carried three or more copies of DLA-88, further emphasizing the need for more sensitive and cost-effective DLA typing methodology for the dog clinical model.

Application of Statistical Learning to Identify Omicron Mutations in SARS-CoV-2 Viral Genome Sequence Data From Populations in Africa and the United States

IMPORTANCE

With timely collection of SARS-CoV-2 viral genome sequences, it is important to apply efficient data analytics to detect emerging variants at the earliest time.

OBJECTIVE

To evaluate the application of a statistical learning strategy (SLS) to improve early detection of novel SARS-CoV-2 variants using viral sequence data from global surveillance.

DESIGN, SETTING, AND PARTICIPANTS

This case series applied an SLS to viral genomic sequence data collected from 63 686 individuals in Africa and 531 827 individuals in the United States with SARS-CoV-2. Data were collected from January 1, 2020, to December 28, 2021.

MAIN OUTCOMES AND MEASURES

The outcome was an indicator of Omicron variant derived from viral sequences. Centering on a temporally collected outcome, the SLS used the generalized additive model to estimate locally averaged Omicron caseload percentages (OCPs) over time to characterize Omicron expansion and to estimate when OCP exceeded 10%, 25%, 50%, and 75% of the caseload. Additionally, an unsupervised learning technique was applied to visualize Omicron expansions, and temporal and spatial distributions of Omicron cases were investigated.

RESULTS

In total, there were 2698 cases of Omicron in Africa and 12 141 in the United States. The SLS found that Omicron was detectable in South Africa as early as December 31, 2020. With 10% OCP as a threshold, it may have been possible to declare Omicron a variant of concern as early as November 4, 2021, in South Africa. In the United States, the application of SLS suggested that the first case was detectable on November 21, 2021.

CONCLUSIONS AND RELEVANCE

The application of SLS demonstrates how the Omicron variant may have emerged and expanded in Africa and the United States. Earlier detection could help the global effort in disease prevention and control. To optimize early detection, efficient data analytics, such as SLS, could assist in the rapid identification of new variants as soon as they emerge, with or without lineages designated, using viral sequence data from global surveillance.

Broadly neutralizing antibodies target the coronavirus fusion peptide

The potential for future coronavirus outbreaks highlights the need to broadly target this group of pathogens. We used an epitope-agnostic approach to identify six monoclonal antibodies that bind to spike proteins from all seven human-infecting coronaviruses. All six antibodies target the conserved fusion peptide region adjacent to the S2' cleavage site. COV44-62 and COV44-79 broadly neutralize alpha- and betacoronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariants BA.2 and BA.4/5, albeit with lower potency than receptor binding domain-specific antibodies. In crystal structures of COV44-62 and COV44-79 antigen-binding fragments with the SARS-CoV-2 fusion peptide, the fusion peptide epitope adopts a helical structure and includes the arginine residue at the S2' cleavage site. COV44-79 limited disease caused by SARS-CoV-2 in a Syrian hamster model. These findings highlight the fusion peptide as a candidate epitope for next-generation coronavirus vaccine development.

High-resolution HLA class II sequencing of Swedish multiple sclerosis patients

Multiple sclerosis (MS) is a chronic neurological disease believed to be caused by autoimmune pathogenesis. The aetiology is likely explained by a complex interplay between inherited and environmental factors. Genetic investigations into MS have been conducted for over 50 years, yielding >100 associations to date. Globally, the strongest linkage is with the human leukocyte antigen (HLA) HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 haplotype. Here, high-resolution sequencing of HLA was used to determine the alleles of DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 as well as their extended haplotypes and genotypes in 100 Swedish MS patients. Results were compared to 636 population controls. The heterogeneity in HLA associations with MS was demonstrated; among 100 patients, 69 extended HLA-DR-DQ genotypes were found. Three extended HLA-DR-DQ genotypes were found to be correlated to MS; HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01 haplotype together with (A) HLA-DRB4*01:01:01//DRB4*01:01:01:01-DRB1*07:01:01-DQA1*02:01//02:01:01-DQB1*02:02:01, (B) HLA-DRBX*null-DRB1*08:01:01-DQA1*04:01:01-DQB1*04:02:01, and (C) HLA-DRB3*01:01:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01. At the allelic level, HLA-DRB3*01:01:02 was considered protective against MS. However, when combined with HLA-DRB3*01:01:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01, this extended haplotype was considered a predisposing risk factor. This highlights the limitations as included with investigations of single alleles relative to those of extended haplotypes/genotypes. In conclusion, with 69 genotypes presented among 100 patients, high-resolution sequencing was conducted to underscore the wide polymorphisms present among MS patients. Additional studies in larger cohorts will be of importance to define MS among the patient group not associated with HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01.

Human Leukocyte Antigen HLA-C, HLA-G, HLA-F and HLA-E placental profiles are altered in Early Severe Preeclampsia and Preterm Birth with Chorioamnionitis

BACKGROUND

The extravillous trophoblast expresses each of the non-classical MHC class I antigens - HLA-E, F, and G and a single classical class I antigen HLA-C. We recently demonstrated dynamic expression patterns of HLA-C, G and F during early EVT invasion and placentation.

OBJECTIVE

In this study we investigate the hypothesis that the immune inflammatory mediated complications of pregnancy such as early preeclampsia and preterm labor, may show altered expression profiles of non-classical HLA.

STUDY DESIGN

Real time q-PCR, western blot and immunohistochemistry were performed on placental villous tissues and basal plate sections from term non-laboring deliveries, preterm deliveries and severe early onset preeclampsia both with and without small for gestational age neonates.

RESULTS

HLA-G is strongly and exclusively expressed by the EVT within the placental basal plate and its levels increase in pregnancies complicated by severe early onset PE with SGA neonates as compared to healthy term controls. HLA-C shows a similar profile in the EVT of PE pregnancies, but significantly decreases in the villous placenta. HLA-F protein levels are decreased in both EVT and villous placenta of severe early onset PE pregnancies both with and without SGA babies as compared to Term and PTB deliveries. HLA-E decreases in blood vessels in placentas from PE pregnancies as compared to Term and PTB deliveries. HLA-F and HLA-C are increased in the placenta of PTBs with chorioamnionitis as compared to idiopathic PTB.

CONCLUSION

Dysregulation of placental HLA expression at the maternal fetal interface may contribute to the compromised maternal tolerance in PTB with chorioamnionitis and excessive maternal systemic inflammation associated with severe early onset PE.

Association of HLA-DQ Heterodimer Residues -18β and β57 With Progression From Islet Autoimmunity to Diabetes in the Diabetes Prevention Trial-Type 1

OBJECTIVE

The purpose was to test the hypothesis that the HLA-DQαβ heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and β-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset.

RESULTS

The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18β in the signal peptide and β57 in the β-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up.

CONCLUSIONS

HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18β within the signal peptide may be related to levels of protein synthesis and β57 to stability of the peptide-DQab trimolecular complex.

Broadly neutralizing antibodies target the coronavirus fusion peptide

The potential for future coronavirus outbreaks highlights the need to develop strategies and tools to broadly target this group of pathogens. Here, using an epitope-agnostic approach, we identified six monoclonal antibodies that bound to spike proteins from all seven human-infecting coronaviruses. Epitope mapping revealed that all six antibodies target the conserved fusion peptide region adjacent to the S2' cleavage site. Two antibodies, COV44-62 and COV44-79, broadly neutralize a range of alpha and beta coronaviruses, including SARS-CoV-2 Omicron subvariants BA.1 and BA.2, albeit with lower potency than RBD-specific antibodies. In crystal structures of Fabs COV44-62 and COV44-79 with the SARS-CoV-2 fusion peptide, the fusion peptide epitope adopts a helical structure and includes the arginine at the S2' cleavage site. Importantly, COV44-79 limited disease caused by SARS-CoV-2 in a Syrian hamster model. These findings identify the fusion peptide as the target of the broadest neutralizing antibodies in an epitope-agnostic screen, highlighting this site as a candidate for next-generation coronavirus vaccine development.

One-Sentence Summary

Rare monoclonal antibodies from COVID-19 convalescent individuals broadly neutralize coronaviruses by targeting the fusion peptide.

T cell response to intact SARS-CoV-2 includes coronavirus cross-reactive and variant-specific components

SARS-CoV-2 provokes a robust T cell response. Peptide-based studies exclude antigen processing and presentation biology, which may influence T cell detection studies. To focus on responses to whole virus and complex antigens, we used intact SARS-CoV-2 and full-length proteins with DCs to activate CD8 and CD4 T cells from convalescent people. T cell receptor (TCR) sequencing showed partial repertoire preservation after expansion. Resultant CD8 T cells recognize SARS-CoV-2-infected respiratory tract cells, and CD4 T cells detect inactivated whole viral antigen. Specificity scans with proteome-covering protein/peptide arrays show that CD8 T cells are oligospecific per subject and that CD4 T cell breadth is higher. Some CD4 T cell lines enriched using SARS-CoV-2 cross-recognize whole seasonal coronavirus (sCoV) antigens, with protein, peptide, and HLA restriction validation. Conversely, recognition of some epitopes is eliminated for SARS-CoV-2 variants, including spike (S) epitopes in the Alpha, Beta, Gamma, and Delta variant lineages.

T cell response to intact SARS-CoV-2 includes coronavirus cross-reactive and variant-specific components

SARS-CoV-2 provokes a brisk T cell response. Peptide-based studies exclude antigen processing and presentation biology and may influence T cell detection studies. To focus on responses to whole virus and complex antigens, we used intact SARS-CoV-2 and full-length proteins with DC to activate CD8 and CD4 T cells from convalescent persons. T cell receptor (TCR) sequencing showed partial repertoire preservation after expansion. Resultant CD8 T cells recognize SARS-CoV-2-infected respiratory cells, and CD4 T cells detect inactivated whole viral antigen. Specificity scans with proteome-covering protein/peptide arrays show that CD8 T cells are oligospecific per subject and that CD4 T cell breadth is higher. Some CD4 T cell lines enriched using SARS-CoV-2 cross-recognize whole seasonal coronavirus (sCoV) antigens, with protein, peptide, and HLA restriction validation. Conversely, recognition of some epitopes is eliminated for SARS-CoV-2 variants, including spike (S) epitopes in the alpha, beta, gamma, and delta variant lineages.

Mutations in viral nucleocapsid protein and endoRNase are discovered to associate with COVID19 hospitalization risk

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients ("cases") and 295 outpatients ("controls") from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytical power, we accessed 7137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values < 0.01). Using temporal synchrony, we identified a four SNV-haplotype (t19839-g28881-g28882-g28883) that was significantly associated with case/control status (Fisher's exact p = 2.84 × 10-11). This haplotype appeared in April 2020, peaked in June, and persisted into January 2021. The association was replicated (OR = 5.46, p-value = 4.71 × 10-12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering "cytokine storms" and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020-March 2021) Using a Statistical Learning Strategy

The emergence and establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest (VOIs) and variants of concern (VOCs) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from coronavirus disease 2019 (COVID-19) cases in the United States (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from 19 January 2020 to 15 March 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics and to identify VRVs with significant and substantial dynamics (false discovery rate q-value < 0.01; maximum VRV proportion >10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modeling was performed to gain insight into the potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which had not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identified 17 VRVs ~91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of four VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported a potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

A Model of Minor Histocompatibility Antigens in Allogeneic Hematopoietic Cell Transplantation

Minor histocompatibility antigens (mHAg) composed of peptides presented by HLA molecules can cause immune responses involved in graft-versus-host disease (GVHD) and graft-versus-leukemia effects after allogeneic hematopoietic cell transplantation (HCT). The current study was designed to identify individual graft-versus-host genomic mismatches associated with altered risks of acute or chronic GVHD or relapse after HCT between HLA-genotypically identical siblings. Our results demonstrate that in allogeneic HCT between a pair of HLA-identical siblings, a mHAg manifests as a set of peptides originating from annotated proteins and non-annotated open reading frames, which i) are encoded by a group of highly associated recipient genomic mismatches, ii) bind to HLA allotypes in the recipient, and iii) evoke a donor immune response. Attribution of the immune response and consequent clinical outcomes to individual peptide components within this set will likely differ from patient to patient according to their HLA types.

The KAG motif of HLA-DRB1 (β71, β74, β86) predicts seroconversion and development of type 1 diabetes

BACKGROUND

HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated.

METHODS

We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions.

FINDINGS

Three amino acid residues of HLA-DRB1 (β71, β74, β86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10-64). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10-4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10-14) after adjusting potential confounders.

INTERPRETATIONS

DNA sequence variation in HLA-DRB1 at positions β71, β74, and β86 are non-conservative (β74 A→E, β71 E vs K vs R and β86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65.

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 - 2021/03) Using a Statistical Learning Strategy

The emergence and establishment of SARS-CoV-2 variants of interest (VOI) and variants of concern (VOC) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from US COVID-19 cases (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from January 19, 2020 to March 15, 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics, to identify VRVs with significant and substantial dynamics (false discovery rate q-value <0.01; maximum VRV proportion > 10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modelling was performed to gain insight into potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which have not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identifies 17 VRVs ∼91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of 4 VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

High-resolution genotyping of HLA class I loci in children with type 1 diabetes and celiac disease

OBJECTIVES

HLA-DQ2 and DQ8 contribute to the strongest risk haplotypes for type 1 diabetes (T1D) and celiac disease (CD). The variation in genetic risk association is likely linked to different HLA class II loci susceptibility, but association studies of HLA class I alleles are scarce. The aim was to investigate HLA class I A, B, and C alleles polymorphisms in children with only T1D, CD, and a subgroup with both T1D and CD (T1D w/CD).

MATERIALS AND METHODS

HLA class I A, B, and C genes were genotyped using next-generation targeted sequencing. A conditional analysis was performed on 68 children with T1D, 219 children with CD and seven children with T1D w/CD enrolled from a birth cohort study at high genetic risk children from the South of Sweden.

RESULTS

Among 1764 HLA class I allele variants, A*29:02:01 in T1D w/CD was associated with both T1D (OR = 21.42 [1.05, 1322.4], p = 0.0231) and CD (OR = 35 [2.36, 529.12], p = 0.0051) along with C*05:01:01 with both T1D (OR = 5.54 [1.06, 24.8], p = 0.02) and CD (OR = 6.84 [1.46, 26.01], p = 0.0077). No independent effects of HLA-B allele associations were observed in T1D w/CD.

CONCLUSION

Although the distribution of HLA class I alleles differs between children with T1D and CD, the A*29:02:01 and C*05:01:01 alleles showed shared risk association of both diseases.

A Detailed View of KIR Haplotype Structures and Gene Families as Provided by a New Motif-Based Multiple Sequence Alignment

Human chromosome 19q13.4 contains genes encoding killer-cell immunoglobulin-like receptors (KIR). Reported haplotype lengths range from 67 to 269 kb and contain 4 to 18 genes. The region has certain properties such as single nucleotide variation, structural variation, homology, and repetitive elements that make it hard to align accurately beyond single gene alleles. To the best of our knowledge, a multiple sequence alignment of KIR haplotypes has never been published or presented. Such an alignment would be useful to precisely define KIR haplotypes and loci, provide context for assigning alleles (especially fusion alleles) to genes, infer evolutionary history, impute alleles, interpret and predict co-expression, and generate markers. In order to extend the framework of KIR haplotype sequences in the human genome reference, 27 new sequences were generated including 24 haplotypes from 12 individuals of African American ancestry that were selected for genotypic diversity and novelty to the reference, to bring the total to 68 full length genomic KIR haplotype sequences. We leveraged these data and tools from our long-read KIR haplotype assembly algorithm to define and align KIR haplotypes at <5 kb resolution on average. We then used a standard alignment algorithm to refine that alignment down to single base resolution. This processing demonstrated that the high-level alignment recapitulates human-curated annotation of the human haplotypes as well as a chimpanzee haplotype. Further, assignments and alignments of gene alleles were consistent with their human curation in haplotype and allele databases. These results define KIR haplotypes as 14 loci containing 9 genes. The multiple sequence alignments have been applied in two software packages as probes to capture and annotate KIR haplotypes and as markers to genotype KIR from WGS.

High-resolution genotyping indicates that children with type 1 diabetes and celiac disease share three HLA class II loci in DRB3, DRB4 and DRB5 genes

Type 1 diabetes (T1D) and celiac disease (CD) share common genetic loci, mainly within the human leukocyte antigen (HLA) class II complex. Extended genotyping of HLA class II alleles and their potential risk for developing both diseases remains to be studied. The present study compared extended HLA-class II gene polymorphisms in children with T1D, CD, and a subgroup diagnosed with both diseases (T1D w/CD). Next-generation targeted sequencing (NGTS) of HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1, and DPB1 alleles from DNA collected from 68 T1D, 219 CD, and seven T1D w/CD patients were compared with 636 HLA-genotyped Swedish children from the general population selected as controls. In comparison to controls, the DRB4*01:03:01 allele occurred more frequently in T1D w/CD (odds ratio (OR) = 7.84; 95% confidence interval (95% CI) = (2.24, 34.5), P = 0.0002) and T1D (OR = 3.86; 95% CI, (2.69, 5.55), P = 1.07 × 10^-14 ), respectively. The DRB3*01:01:02 allele occurred more frequently in CD as compared to controls (OR = 7.87; 95% CI, (6.17, 10.03), P = 4.24 × 10^-71 ), but less frequently in T1D (OR = 2.59; 95% CI, (1.76, 3.81), P = 7.29 × 10^-07 ) and T1D w/CD (OR = 0.87; 95% CI, (0.09, 3.96), P ≤ 0.999). The frequency of the DRB4*01:03:01-DRB1*04:01:01-DQA1*03:01:01-DQB1*03:02:01 (DR4-DQ8) haplotype was higher in T1D w/CD (OR = 12.88; 95% CI (4.35, 38.14) P = 3.75 × 10^-9 ), and moderately higher in T1D (OR = 2.13; 95% CI (1.18, 3.83) P = 0.01) compared with controls, but comparable in CD (OR = 1.45; 95% CI (0.94, 2.21), P = 0.08) and controls. Children with T1D and CD are associated with DRB4*01:03:01, DRB3*01:01:02, and DRB3*02:02:01 of which DRB4*01:03:01 confers the strongest risk allele for developing T1D w/CD.

Next-Generation HLA Sequence Analysis Uncovers Seven HLA-DQ Amino Acid Residues and Six Motifs Resistant to Childhood Type 1 Diabetes

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, β9, β30, β57, and β70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10^-24, 3.54 × 10^-15, and 1.03 × 10^-21, respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at β57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10^-15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, β167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-β heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

Motifs of Three HLA-DQ Amino Acid Residues (α44, β57, β135) Capture Full Association With the Risk of Type 1 Diabetes in DQ2 and DQ8 Children

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10^-85) and β57A (OR 3.44, P = 3.80 * 10^-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, β57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and β135D to share the risk for T1D (OR 2.10, P = 1.96 * 10^-20). The motif "QAD" of α44, β57, and β135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10^-84), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10^-20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10^-8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10^-11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10^-3) but positively with IA-2A (OR 1.64; P = 2.40 * 10^-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, β57, β135) conferring T1D risk should sharpen functional and translational studies.

Fc Gamma Receptor Polymorphisms Modulated the Vaccine Effect on HIV-1 Risk in the HVTN 505 HIV Vaccine Trial

HIV Vaccine Trials Network (HVTN) 505 was a phase 2b efficacy trial of a DNA/recombinant adenovirus 5 (rAd5) HIV vaccine regimen. Although the trial was stopped early for lack of overall efficacy, later correlates of risk and sieve analyses generated the hypothesis that the DNA/rAd5 vaccine regimen protected some vaccinees from HIV infection yet enhanced HIV infection risk for others. Here, we assessed whether and how host Fc gamma receptor (FcγR) genetic variations influenced the DNA/rAd5 vaccine regimen's effect on HIV infection risk. We found that vaccine receipt significantly increased HIV acquisition compared with placebo receipt among participants carrying the FCGR2C-TATA haplotype (comprising minor alleles of four FCGR2C single-nucleotide polymorphism [SNP] sites) (hazard ratio [HR] = 9.79, P = 0.035) but not among participants without the haplotype (HR = 0.86, P = 0.67); the interaction of vaccine and haplotype effect was significant (P = 0.034). Similarly, vaccine receipt increased HIV acquisition compared with placebo receipt among participants carrying the FCGR3B-AGA haplotype (comprising minor alleles of the 3 FCGR3B SNPs) (HR = 2.78, P = 0.058) but not among participants without the haplotype (HR = 0.73, P = 0.44); again, the interaction of vaccine and haplotype was significant (P = 0.047). The FCGR3B-AGA haplotype also influenced whether a combined Env-specific CD8+ T-cell polyfunctionality score and IgG response correlated significantly with HIV risk; an FCGR2A SNP and two FCGR2B SNPs influenced whether anti-gp140 antibody-dependent cellular phagocytosis correlated significantly with HIV risk. These results provide further evidence that Fc gamma receptor genetic variations may modulate HIV vaccine effects and immune function after HIV vaccination.IMPORTANCE By analyzing data from the HVTN 505 efficacy trial of a DNA/recombinant adenovirus 5 (rAd5) vaccine regimen, we found that host genetics, specifically Fc gamma receptor genetic variations, influenced whether receiving the DNA/rAd5 regimen was beneficial, neutral, or detrimental to an individual with respect to HIV-1 acquisition risk. Moreover, Fc gamma receptor genetic variations influenced immune responses to the DNA/rAd5 vaccine regimen. Thus, Fc gamma receptor genetic variations should be considered in the analysis of future HIV vaccine trials and the development of HIV vaccines.

Antibody Fc effector functions and IgG3 associate with decreased HIV-1 risk

HVTN 505 is a preventative vaccine efficacy trial testing DNA followed by recombinant adenovirus serotype 5 (rAd5) in circumcised, Ad5-seronegative men and transgendered persons who have sex with men in the United States. Identified immune correlates of lower HIV-1 risk and a virus sieve analysis revealed that, despite lacking overall efficacy, vaccine-elicited responses exerted pressure on infecting HIV-1 viruses. To interrogate the mechanism of the antibody correlate of HIV-1 risk, we examined antigen-specific antibody recruitment of Fcγ receptors (FcγRs), antibody-dependent cellular phagocytosis (ADCP), and the role of anti-envelope (anti-Env) IgG3. In a prespecified immune correlates analysis, antibody-dependent monocyte phagocytosis and antibody binding to FcγRIIa correlated with decreased HIV-1 risk. Follow-up analyses revealed that anti-Env IgG3 breadth correlated with reduced HIV-1 risk, anti-Env IgA negatively modified infection risk by Fc effector functions, and that vaccine recipients with a specific FcγRIIa single-nucleotide polymorphism locus had a stronger correlation with decreased HIV-1 risk when ADCP, Env-FcγRIIa, and IgG3 binding were high. Additionally, FcγRIIa engagement correlated with decreased viral load setpoint in vaccine recipients who acquired HIV-1. These data support a role for vaccine-elicited anti-HIV-1 Env IgG3, antibody engagement of FcRs, and phagocytosis as potential mechanisms for HIV-1 prevention.

HLA high-resolution typing by next-generation sequencing in Pandemrix-induced narcolepsy

The incidence of narcolepsy type 1 (NT1) increased in Sweden following the 2009–2010 mass-vaccination with the influenza Pandemrix-vaccine. NT1 has been associated with Human leukocyte antigen (HLA) DQB1*06:02 but full high-resolution HLA-typing of all loci in vaccine-induced NT1 remains to be done. Therefore, here we performed HLA typing by sequencing HLA-DRB3, DRB4, DRB5, DRB1, DQA1, DQB1, DPA1 and DPB1 in 31 vaccine-associated NT1 patients and 66 of their first-degree relatives (FDR), and compared these data to 636 Swedish general population controls (GP). Previously reported disease-related alleles in the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01extended haplotype were increased in NT1 patients (34/62 haplotypes, 54.8%) compared to GP (194/1272 haplotypes, 15.3%, p = 6.17E^-16). Indeed, this extended haplotype was found in 30/31 patients (96.8%) and 178/636 GP (28.0%). In total, 15 alleles, four extended haplotypes, and six genotypes were found to be increased or decreased in frequency among NT1 patients compared to GP. Among subjects with the HLA-DRB5*01:01:01-DRB1*15:01:01-DQA1*01:02-DQB1*06:02 haplotype, a second DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype (p = 2.02E^-2), but not homozygosity for DRB1*15:01:01-DQB1*06:02:01 (p = 7.49E^-1) conferred association to NT1. Alleles with increased frequency in DQA1*01:02:01 (p = 1.07E^-2) and DQA1*03:02//*03:03:01 (p = 3.26E^-2), as well as with decreased frequency in DRB3*01:01:02 (p = 8.09E^-3), DRB1*03:01:01 (p = 1.40E^-2), and DQB1*02:01:01 (p = 1.40E^-2) were found among patients compared to their FDR. High-resolution HLA sequencing in Pandemrix-associated NT1 confirmed the strong association with the DQB1*06:02:01-containing haplotype but also revealed an increased association to the not previously reported extended HLA-DRB4*01:03:01-DRB1*04:01:01-DQA1*03:02//*03:03:01-DQB1*03:01:01 haplotype. High-resolution HLA typing should prove useful in dissecting the immunological mechanisms of vaccination-associated NT1.

Eleven Amino Acids of HLA-DRB1 and Fifteen Amino Acids of HLA-DRB3, 4, and 5 Include Potentially Causal Residues Responsible for the Risk of Childhood Type 1 Diabetes

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the β49-55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (β14, β25, β71, and β73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10^-18), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10^-11), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population.

Comparison of sequence-specific oligonucleotide probe vs next generation sequencing for HLA-A, B, C, DRB1, DRB3/B4/B5, DQA1, DQB1, DPA1, and DPB1 typing: Toward single-pass high-resolution HLA typing in support of solid organ and hematopoietic cell transplant programs

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence‐specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence‐specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high‐resolution data, Sanger sequencing‐based typing (SBT) has been the “gold standard.” However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high‐resolution typing may provide critical information for highly sensitized patients with donor‐specific anti‐HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three‐field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single‐pass NGS HLA typing method has direct application for solid organ transplantation.

Effect of Fc Receptor Genetic Diversity on HIV-1 Disease Pathogenesis

Fc receptor (FcR) genes collectively have copy number and allelic polymorphisms that have been implicated in multiple inflammatory and autoimmune diseases. This variation might also be involved in etiology of infectious diseases. The protective role of Fc-mediated antibody-function in HIV-1 immunity has led to the investigation of specific polymorphisms in FcR genes on acquisition, disease progression, and vaccine efficacy in natural history cohorts. The purpose of this review is not only to explore these known HIV-1 host genetic associations, but also to re-evaluate them in the context of genome-wide data. In the current era of effective anti-retroviral therapy, the potential impact of such variation on post-treatment cohorts cannot go unheeded and is discussed here in the light of current findings. Specific polymorphisms associating with HIV-1 pathogenesis have previously been genotyped by assays that captured only the single-nucleotide polymorphism (SNP) of interest without relative information of neighboring variants. With recent technological advances, variation within these genes can now be characterized using next-generation sequencing, allowing precise annotation of the whole chromosomal region. We herein also discuss updates in the annotation of common FcR variants that have been previously associated with HIV-1 pathogenesis.

HLA-F on HLA-Null 721.221 Cells Activates Primary NK Cells Expressing the Activating Killer Ig-like Receptor KIR3DS1

NK cells elicit important responses against transformed and virally infected cells. Carriage of the gene encoding the activating killer Ig-like receptor KIR3DS1 is associated with slower time to AIDS and protection from HIV infection. Recently, open conformers of the nonclassical MHC class Ib Ag HLA-F were identified as KIR3DS1 ligands. In this study, we investigated whether the interaction of KIR3DS1 on primary NK cells with HLA-F on the HLA-null cell line 721.221 (221) stimulated KIR3DS1⁺ NK cells. We used a panel of Abs to detect KIR3DS1⁺CD56^dim NK cells that coexpressed the inhibitory NK cell receptors KIR2DL1/L2/L3, 3DL2, NKG2A, and ILT2; the activating NK cell receptors KIR2DS1/S2/S3/S5; and CCL4, IFN-γ, and CD107a functions. We showed that both untreated and acid-pulsed 221 cells induced a similar frequency of KIR3DS1⁺ cells to secrete CCL4/IFN-γ and express CD107a with a similar intensity. A higher percentage of KIR3DS1⁺ than KIR3DS1^- NK cells responded to 221 cells when either inclusive or exclusive (i.e., coexpressing none of the other inhibitory NK cell receptors and activating NK cell receptors detected by the Ab panel) gating strategies were employed to identify these NK cell populations. Blocking the interaction of HLA-F on 221 cells with KIR3DS1-Fc chimeric protein or anti-HLA-F Abs on exclusively gated KIR3DS1⁺ cells reduced the frequency of functional cells compared with that of unblocked conditions for stimulated KIR3DS1⁺ NK cells. Thus, ligation of KIR3DS1 activates primary NK cells for several antiviral functions.

Sieve analysis of breakthrough HIV-1 sequences in HVTN 505 identifies vaccine pressure targeting the CD4 binding site of Env-gp120

Although the HVTN 505 DNA/recombinant adenovirus type 5 vector HIV-1 vaccine trial showed no overall efficacy, analysis of breakthrough HIV-1 sequences in participants can help determine whether vaccine-induced immune responses impacted viruses that caused infection. We analyzed 480 HIV-1 genomes sampled from 27 vaccine and 20 placebo recipients and found that intra-host HIV-1 diversity was significantly lower in vaccine recipients (P ≤ 0.04, Q-values ≤ 0.09) in Gag, Pol, Vif and envelope glycoprotein gp120 (Env-gp120). Furthermore, Env-gp120 sequences from vaccine recipients were significantly more distant from the subtype B vaccine insert than sequences from placebo recipients (P = 0.01, Q-value = 0.12). These vaccine effects were associated with signatures mapping to CD4 binding site and CD4-induced monoclonal antibody footprints. These results suggest either (i) no vaccine efficacy to block acquisition of any viral genotype but vaccine-accelerated Env evolution post-acquisition; or (ii) vaccine efficacy against HIV-1s with Env sequences closest to the vaccine insert combined with increased acquisition due to other factors, potentially including the vaccine vector.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes

AIM

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies.

METHODS

Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D.

RESULTS

In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10^-92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime.

CONCLUSION

Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations.

Different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease

Celiac disease is associated with the HLA-DR3-DQA1*05:01-DQB1*02:01 and DR4-DQA1*03:01-DQB1*03:02 haplotypes. In addition, there are currently over 40 non-HLA loci associated with celiac disease. This study extends previous analyses on different HLA haplotypes in celiac disease using next generation targeted sequencing. Included were 143 patients with celiac disease and 135 non-celiac disease controls investigated at median 9.8 years (1.4-18.3 years). PCR-based amplification of HLA and sequencing with Illumina MiSeq technology were used for extended sequencing of the HLA class II haplotypes HLA-DRB1, DRB3, DRB4, DRB5, DQA1 and DQB1, respectively. Odds ratios were computed marginally for every allele and haplotype as the ratio of allelic frequency in patients and controls as ratio of exposure rates (RR), when comparing a null reference with equal exposure rates in cases and controls. Among the extended HLA haplotypes, the strongest risk haplotype for celiac disease was shown for DRB3*01:01:02 in linkage with DQA1*05:01-DQB1*02:01 (RR = 6.34; P-value < .0001). In a subpopulation analysis, DRB3*01:01:02-DQA1*05:01-DQB1*02:01 remained the most significant in patients with Scandinavian ethnicity (RR = 4.63; P < .0001) whereas DRB1*07:01:01-DRB4*01:03:01-DQA1*02:01-DQB1*02:02:01 presented the highest risk of celiac disease among non-Scandinavians (RR = 7.94; P = .011). The data also revealed 2 distinct celiac disease risk DR3-DQA1*05:01-DQB*02:01 haplotypes distinguished by either the DRB3*01:01:02 or DRB3*02:02:01 alleles, indicating that different DRB1*03:01-DQB1*02:01 haplotypes confer different risk for celiac disease. The associated risk of celiac disease for DR3-DRB3*01:01:02-DQA1*05:01-DQB1*02:01 is predominant among patients of Scandinavian ethnicity.

An Object-Oriented Regression for Building Disease Predictive Models with Multiallelic HLA Genes

Recent genome-wide association studies confirm that human leukocyte antigen (HLA) genes have the strongest associations with several autoimmune diseases, including type 1 diabetes (T1D), providing an impetus to reduce this genetic association to practice through an HLA-based disease predictive model. However, conventional model-building methods tend to be suboptimal when predictors are highly polymorphic with many rare alleles combined with complex patterns of sequence homology within and between genes. To circumvent this challenge, we describe an alternative methodology; treating complex genotypes of HLA genes as "objects" or "exemplars," one focuses on systemic associations of disease phenotype with "objects" via similarity measurements. Conceptually, this approach assigns disease risks base on complex genotype profiles instead of specific disease-associated genotypes or alleles. Effectively, it transforms large, discrete, and sparse HLA genotypes into a matrix of similarity-based covariates. By the Kernel representative theorem and machine learning techniques, it uses a penalized likelihood method to select disease-associated exemplars in building predictive models. To illustrate this methodology, we apply it to a T1D study with eight HLA genes (HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA-DRB5, HLA-DQA1, HLA-DQB1, HLA-DPA1, and HLA-DPB1) to build a predictive model. The resulted predictive model has an area under curve of 0.92 in the training set, and 0.89 in the validating set, indicating that this methodology is useful to build predictive models with complex HLA genotypes.

Distribution of HLA-G extended haplotypes and one HLA-E polymorphism in a large-scale study of mother-child dyads with and without severe preeclampsia and eclampsia

The etiological pathways and pathogenesis of preeclampsia have rendered difficult to disentangle. Accumulating evidence points toward a maladapted maternal immune system, which may involve aberrant placental expression of immunomodulatory human leukocyte antigen (HLA) class Ib molecules during pregnancy. Several studies have shown aberrant or reduced expression of HLA-G in the placenta and in maternal blood in cases of preeclampsia compared with controls. Unlike classical HLA class Ia loci, the nonclassical HLA-G has limited polymorphic variants. Most nucleotide variations are clustered in the 5'-upstream regulatory region (5'URR) and 3'-untranslated regulatory region (3'UTR) of HLA-G and reflect a stringent expressional control. Based on genotyping and full gene sequencing of HLA-G in a large number of cases and controls (n > 900), the present study, which to our knowledge is the largest and most comprehensive performed, investigated the association between the HLA-G 14-bp ins/del (rs66554220) and HLA-E polymorphisms in mother and newborn dyads from pregnancies complicated by severe preeclampsia/eclampsia and from uncomplicated pregnancies. Furthermore, results from extended HLA-G haplotyping in the newborns are presented in order to assess whether a combined contribution of nucleotide variations spanning the 5'URR, coding region, and 3'UTR of HLA-G describes the genetic association with severe preeclampsia more closely. In contrast to earlier findings, the HLA-G 14-bp ins/del polymorphism was not associated with severe preeclampsia. Furthermore, the polymorphism (rs1264457) defining the two nonsynonymous HLA-E alleles, HLA-E*01:01:xx:xx and HLA-E*01:03:xx:xx, were not associated with severe preeclampsia. Finally, no specific HLA-G haplotypes were significantly associated with increased risk of developing severe preeclampsia/eclampsia.

HLA-F and MHC-I Open Conformers Bind Natural Killer Cell Ig-Like Receptor KIR3DS1

Based on previous findings supporting HLA-F as a ligand for KIR3DL2 and KIR2DS4, we investigated the potential for MHC-I open conformers (OCs) as ligands for KIR3DS1 and KIR3DL1 through interactions measured by surface plasmon resonance. These measurements showed physical binding of KIR3DS1 but not KIR3DL1 with HLA-F and other MHC-I OC while also confirming the allotype specific binding of KIR3DL1 with MHC-I peptide complex. Concordant results were obtained with biochemical pull-down from cell lines and biochemical heterodimerization experiments with recombinant proteins. In addition, surface binding of HLA-F and KIR3DS1 to native and activated NK and T cells was coincident with specific expression of the putative ligand or receptor. A functional response of KIR3DS1 was indicated by increased granule exocytosis in activated cells incubated with HLA-F bound to surfaces. The data extend a model for interaction between MHC-I open conformers and activating KIR receptors expressed during an inflammatory response, potentially contributing to communication between the innate and adaptive immune response.

HLA class II genes modulate vaccine-induced antibody responses to affect HIV-1 acquisition

In the RV144 vaccine trial, two antibody responses were found to correlate with HIV-1 acquisition. Because human leukocyte antigen (HLA) class II-restricted CD4(+) T cells are involved in antibody production, we tested whether HLA class II genotypes affected HIV-1-specific antibody levels and HIV-1 acquisition in 760 individuals. Indeed, antibody responses correlated with acquisition only in the presence of single host HLA alleles. Envelope (Env)-specific immunoglobulin A (IgA) antibodies were associated with increased risk of acquisition specifically in individuals with DQB1*06. IgG antibody responses to Env amino acid positions 120 to 204 were higher and were associated with decreased risk of acquisition and increased vaccine efficacy only in the presence of DPB1*13. Screening IgG responses to overlapping peptides spanning Env 120-204 and viral sequence analysis of infected individuals defined differences in vaccine response that were associated with the presence of DPB1*13 and could be responsible for the protection observed. Overall, the underlying genetic findings indicate that HLA class II modulated the quantity, quality, and efficacy of antibody responses in the RV144 trial.