The HLA genomic loci map: expression, interaction, diversity and disease

Description and first insights on a large genomic biobank of lung transplantation

The main limitation to long-term lung transplant (LT) survival is chronic lung allograft dysfunction (CLAD), which leads to irreversible lung damage and significant mortality. Individual factors can impact CLAD, but no large genetic investigation has been conducted to date. We established the multicentric Genetic COhort in Lung Transplantation (GenCOLT) biobank from a rich and homogeneous sub-part of COLT cohort. GenCOLT collected DNA, high-quality GWAS (genome-wide association study) genotyping and robust HLA data for donors and recipients to supplement COLT clinical data. GenCOLT closely mirrors the global COLT cohort without significant variations in variables like demographics, initial disease and survival rates (P > 0.05). The GenCOLT donors were 45 years-old on average, 44% women, and primarily died of stroke (54%). The recipients were 48 years-old at transplantation on average, 45% women, and the main underlying disease was chronic obstructive pulmonary disease (45%). The mean follow-up time was 67 months and survival at 5 years was 57.3% for the CLAD subgroup and 97.4% for the non-CLAD subgroup. After stringent quality controls, GenCOLT gathered more than 7.3 million SNP and HLA genotypes for 387 LT pairs, including 91% pairs composed of donor and recipient of European ancestry. Overall, GenCOLT is an accurate snapshot of LT clinical practice in France and Belgium between 2009 and 2018. It currently represents one of the largest genetic biobanks dedicated to LT with data available simultaneously for donors and recipients. This unique cohort will empower to run comprehensive GWAS investigations of CLAD and other LT outcomes.

Integrative analysis reveals novel insights into juvenile idiopathic arthritis pathogenesis and shared molecular pathways with associated traits

Background

Juvenile idiopathic arthritis (JIA) is an autoimmune joint disease that frequently co-occurs with other complex phenotypes, including cancers and other autoimmune diseases. Despite the identification of numerous risk variants through genome-wide association studies (GWAS), the affected genes, their connection to JIA pathogenesis, and their role in the development of associated traits remain unclear. This study aims to address these gaps by elucidating the gene-regulatory mechanisms underlying JIA pathogenesis and exploring its potential role in the emergence of associated traits.

Methods

A two-sample Mendelian Randomization (MR) analysis was conducted to identify blood-expressed genes causally linked to JIA. A curated protein interaction network was subsequently used to identify sets of single-nucleotide polymorphisms (i.e., spatial eQTL SNPs) that regulate the expression of JIA causal genes and their protein interaction partners. These SNPs were cross-referenced against the GWAS catalog to identify statistically enriched traits associated with JIA.

Results

The two-sample MR analysis identified 52 genes whose expression changes in the blood are putatively causal for JIA. These genes (e.g., HLA, LTA, LTB, IL6ST) participate in a range of immune-related pathways (e.g., antigen presentation, cytokine signalling) and demonstrate cell type-specific regulatory patterns across different immune cell types (e.g., PPP1R11 in CD4+ T cells). The spatial eQTLs that regulate JIA causal genes and their interaction partners were statistically enriched for GWAS SNPs linked with 95 other traits, including both known and novel JIA-associated traits. This integrative analysis identified genes whose dysregulation may explain the links between JIA and associated traits, such as autoimmune/inflammatory diseases (genes at 6p22.1 locus), Hodgkin lymphoma (genes at 6p21.3 [FKBPL, PBX2, AGER]), and chronic lymphocytic leukemia (BAK1).

Conclusion

Our approach provides a significant advance in understanding the genetic architecture of JIA and associated traits. The results suggest that the burden of associated traits may differ among JIA patients, influenced by their combined genetic risk across different clusters of traits. Future experimental validation of the identified connections could pave the way for refined patient stratification, the discovery of new biomarkers, and shared therapeutic targets.

Computational Methods for Predicting Key Interactions in T Cell-Mediated Adaptive Immunity

The adaptive immune system recognizes pathogen- and cancer-specific features and is endowed with memory, enabling it to respond quickly and efficiently to repeated encounters with the same antigens. T cells play a central role in the adaptive immune system by directly targeting intracellular pathogens and helping to activate B cells to secrete antibodies. Several fundamental protein interactions-including those between major histocompatibility complex (MHC) proteins and antigen-derived peptides as well as between T cell receptors and peptide-MHC complexes-underlie the ability of T cells to recognize antigens with great precision. Computational approaches to predict these interactions are increasingly being used for medically relevant applications, including vaccine design and prediction of patient response to cancer immunotherapies. We provide computational researchers with an accessible introduction to the adaptive immune system, review computational approaches to predict the key protein interactions underlying T cell-mediated adaptive immunity, and highlight remaining challenges.

Validation and functional follow-up of cervical cancer risk variants at the HLA locus

Cervical cancer is the fourth most common cancer in females. Genome-wide association studies (GWASs) have proposed cervical cancer susceptibility variants at the HLA locus on chromosome 6p21. To corroborate these findings and investigate their functional impact in cervical tissues and cell lines, we genotyped nine variants from cervical cancer GWASs (rs17190106, rs535777, rs1056429, rs2763979, rs143954678, rs113937848, rs3117027, rs3130214, and rs9477610) in a German hospital-based series of 1122 invasive cervical cancers, 1408 dysplasias, and 1196 healthy controls. rs17190106, rs1056429 and rs143954678/rs113937848 associated with cervical malignancies overall, while rs17190106 and rs535777 associated specifically with invasive cancer (OR = 0.69, 95% CI = 0.55-0.86, p = 0.001) or adenocarcinomas (OR = 1.63, 95%CI = 1.17-2.27, p = 0.004), respectively. We tested these and one previously genotyped GWAS variant, rs9272117, for potential eQTL effects on 36 gene transcripts at the HLA locus in 280 cervical epithelial tissues. The strongest eQTL pairs were rs9272117 and HLA-DRB6 (p = 1.9x10E-5), rs1056429 and HLA-DRB5 (p = 2.5x10E-4), and rs535777 and HLA-DRB1 (p = 2.7x10E-4). We also identified transcripts that were specifically upregulated (DDX39B, HCP5, HLA-B, LTB, NFKBIL1) or downregulated (HLA-C, HLA-DPB2) in HPV+ or HPV16+ samples. In comparison, treating cervical epithelial cells with proinflammatory cytokine γ-IFN led to a dose-dependent induction of HCP5, HLA-B, HLA-C, HLA-DQB1, HLA-DRB1, HLA-DRB6, and repression of HSPA1L. Taken together, these results identify relevant genes from both the MHC class I and II regions that are inflammation-responsive in cervical epithelium and associate with HPV (HCP5, HLA-B, HLA-C) and/or with genomic cervical cancer risk variants (HLA-DRB1, HLA-DRB6). They may thus constitute important contributors to the immune escape of precancerous cells after HPV-infection.

Improving population scale statistical phasing with whole-genome sequencing data

Haplotype estimation, or phasing, has gained significant traction in large-scale projects due to its valuable contributions to population genetics, variant analysis, and the creation of reference panels for imputation and phasing of new samples. To scale with the growing number of samples, haplotype estimation methods designed for population scale rely on highly optimized statistical models to phase genotype data, and usually ignore read-level information. Statistical methods excel in resolving common variants, however, they still struggle at rare variants due to the lack of statistical information. In this study we introduce SAPPHIRE, a new method that leverages whole-genome sequencing data to enhance the precision of haplotype calls produced by statistical phasing. SAPPHIRE achieves this by refining haplotype estimates through the realignment of sequencing reads, particularly targeting low-confidence phase calls. Our findings demonstrate that SAPPHIRE significantly enhances the accuracy of haplotypes obtained from state of the art methods and also provides the subset of phase calls that are validated by sequencing reads. Finally, we show that our method scales to large data sets by its successful application to the extensive 3.6 Petabytes of sequencing data of the last UK Biobank 200,031 sample release.

Computational design and investigation of the monomeric spike SARS-CoV-2-ferritin nanocage vaccine stability and interactions

Since the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) outbreak, several solutions have been proposed to manage the disease. The most viable option for controlling this virus is to produce effective vaccines. Most of the current SARS-CoV-2 vaccines have focused on the infusion spike protein. Spike exists as a trimer and plays a vital role in infecting host cells by binding to the Angiotensin-Converting Enzyme 2 (ACE2) receptor through its Receptor Binding Domain (RBD). Ferritin protein, a naturally occurring iron-storage protein, has gained attention for vaccine production due to its self-assembling property, non-toxic nature, and biocompatibility. Ferritin nanocages have recently been employed in the development of a SARS-CoV-2 vaccination eliciting not only long-term protective memory cells but also a sustained antibody response. In this study, a combination of in silico investigations including molecular docking, molecular dynamics simulations, and immune simulations were carried out to computationally model the monomeric spike protein on the ferritin nanocage as well as to evaluate its stability and interactions for the first time. The structural dynamics of the modeled complex demonstrated noticeable stability. In particular, the Receptor Binding Domain (RBD) and ferritin within the monomeric spike-ferritin complex illustrated significant stability. The lack of alterations in the secondary structure further supported the overall steadiness of the complex. The decline in the distance between ferritin and spike suggests a strong interaction over time. The cross-correlation matrices revealed that the monomeric spike and ferritin move towards each other supporting the stable interaction between spike and ferritin. Further, the orientation of monomeric spike protein within the ferritin unit facilitated the exposure of critical epitopes, specifically upward active Receptor Binding Domain (RBD), enabling effective interactions with the ACE2 receptor. The immune simulations of the model indicated high-level stimulations of both cellular and humoral immunity in the human body. It was also found that the employed model is effective regardless of the mutated spikes in different variants. These findings shed light on the current status of the SARS-CoV-2-ferritin nanoparticle vaccines and could be used as a framework for other similar vaccine designs.

Individual HLAs affect survival after allogeneic stem cell transplantation in adult T-cell leukaemia/lymphoma

Allogeneic haematopoietic stem cell transplantation (allo-HSCT) is the only curative therapy for adult T-cell leukaemia/lymphoma (ATL). Specific HLAs are associated with outcomes of immunotherapy and allo-HSCT. We hypothesised that individual HLAs would affect the clinical outcomes of ATL patients after allo-HSCT. Using data from a Japanese registry, we retrospectively analysed 829 patients with ATL who received transplants from HLA-identical sibling donors or HLA-A, -B, -C or -DRB1 allele-matched unrelated donors between 1996 and 2015. We evaluated the overall mortality risk of HLA-A, -B and -DR antigens with frequencies exceeding 3%. Outcomes were compared between transplants with or without specific HLA antigens. Of the 25 HLAs, two candidates were identified but showed no statistically significant differences by multiple comparison. HLA-B62 was associated with a lower risk of mortality (hazard ratio [HR], 0.68; 95% confidence interval [CI]: 0.51-0.90; p = 0.008), whereas HLA-B60 was associated with a higher risk of mortality (HR, 1.64; 95% CI: 1.19-2.27; p = 0.003). In addition, HLA-B62 was associated with a lower risk of transplant-related mortality (TRM) (HR, 0.52; 95% CI: 0.32-0.85, p = 0.009), whereas HLA-B60 was associated with a higher risk of grades III-IV acute graft-versus-host disease (HR, 2.63; 95% CI: 1.62-4.27; p < 0.001). Neither HLA influenced relapse. The higher risk of acute GVHD in HLA-B60-positive patients and the lower risk of TRM in HLA-B62-positive patients were consistent with previously obtained results from patients with other haematological malignancies. Consideration of HLA in ATL patients may help to predict risk and outcomes after allo-HSCT.

Frequency distribution of HLA class I and II alleles in Greek population and their significance in orchestrating the National Donor Registry Program

Human leukocyte antigens (HLA) represent one of the most polymorphic systems in humans, responsible for the identification of foreign antigens and the presentation of immune responses. Therefore, HLA is considered to play a major role in human disorders, donor-recipient matching and transplantation outcomes. This study aimed to determine the HLA class I and II alleles and haplotypes in the Greek population. Moreover, a comparative analysis of HLA alleles and haplotype frequencies found in Greek and pooled European populations was also performed to acquire a better knowledge about the HLA alleles distribution. A total number of 1896 healthy individuals were typed for their HLA alleles in the National Tissue Typing Center of Greece. High-resolution HLA typing for the HLA-A, -B, -C and -DR, -DQ, -DP with the use of the next-generation sequencing analysis was performed, followed by data analysis for establishing the HLA allele and haplotype differences. The results of this study showed that the most frequent alleles for the HLA-A were the A*02:01:01 (27.1%), *24:02:01 (14.4%), *01:01:01 (9.3%), for the HLA-B were the B*51:01:01 (15.3%), *18:01:01 (9.7%), *35:01:01 (6.8%) and for the HLA-C were the C*04:01:01 (15.4%), *07:01:01 (13.1%), *12:03:01 (9.6%). For the HLA class II, the most frequent alleles for the HLA-DRB1 were the DRB1*11:04:01 (16.4%), *16:01:01 (11.3%), *11:01:01 (9.5%), for the HLA-DQB1 were the DQB1*03:01:01 (30.5%), *05:02:01 (15.1%), *05:01:01 (10.6%) and for the HLA-DPB1 were the DPB1*04:01:01 (34.8%), *02:01:01 (11.6%), *04:02:01 (7.3%). Additionally, the most frequent haplotypes were the A*02:01:01∼C*07:01:01-B*18:01:01∼DRB1*11:04:01 (2.3%), followed by the A*01:01:01∼C*07:01:01∼B*08:01:01∼DRB1*03:01:01 (2.2%), A*24:02:01∼C*04:01:01∼B*35:02:01∼DRB1*11:04:01 (1.4%) and A*02:01:01∼C*04:01:01∼B*35:01:01-DRB1*14:01:01 (1.2%). The results herein were comparable to those obtained from the pooled European populations. Moreover, these results can be used for the improvement of the donor-recipient matching procedure and to understand better the disease association in Greece.

MEM-based pangenome indexing for k-mer queries

Pangenomes are growing in number and size, thanks to the prevalence of high-quality long-read assemblies. However, current methods for studying sequence composition and conservation within pangenomes have limitations. Methods based on graph pangenomes require a computationally expensive multiple-alignment step, which can leave out some variation. Indexes based on k-mers and de Bruijn graphs are limited to answering questions at a specific substring length k. We present Maximal Exact Match Ordered (MEMO), a pangenome indexing method based on maximal exact matches (MEMs) between sequences. A single MEMO index can handle arbitrary-length queries over pangenomic windows. MEMO enables both queries that test k-mer presence/absence (membership queries) and that count the number of genomes containing k-mers in a window (conservation queries). MEMO's index for a pangenome of 89 human autosomal haplotypes fits in 2.04 GB, 8.8× smaller than a comparable KMC3 index and 11.4× smaller than a PanKmer index. MEMO indexes can be made smaller by sacrificing some counting resolution, with our decile-resolution HPRC index reaching 0.67 GB. MEMO can conduct a conservation query for 31-mers over the human leukocyte antigen locus in 13.89 seconds, 2.5x faster than other approaches. MEMO's small index size, lack of k-mer length dependence, and efficient queries make it a flexible tool for studying and visualizing substring conservation in pangenomes.

HLA-DRB5 Overexpression Promotes Platelet Reduction in Immune Thrombocytopenia Mice Model by Facilitating MHC-II-Mediated Antigen Presentation

INTRODUCTION

Major histocompatibility complex II (MHC-II)-mediated antigen presentation contributes to the pathogenesis of immune thrombocytopenia (ITP). Human leukocyte antigen (HLA)-DRB5 is an MHC-II molecule and this study aims to investigate its role and mechanisms in ITP development.

METHODS

Guinea pig anti-mouse platelet (PLT) serum-induced ITP mice received tail vein injection of HLA-DRB5 overexpressing adenoviral vector/immune receptor expressed on myeloid cells-1 (IREM-1) monoclonal antibody (mAb). PLT count changes in mice blood were assessed by a hematology analyzer. MHC-II/CD80/CD86 expression in mice blood was measured by quantitative real-time-PCR and immunofluorescence assay. CD8+ T-cell proportion in mice blood was detected by flow cytometry.

RESULTS

HLA-DRB5 overexpression exacerbated PLT reduction since the 5th day of the establishment of ITP mice model and enhanced MHC-II/CD80/CD86 expression upregulation as well as CD8+ T-cell ratio elevation in the blood of ITP mice, while its effects were reversed by IREM-1 mAb.

CONCLUSION

HLA-DRB5 overexpression upregulates MHC-II-mediated antigen presentation to CD8+ T cells, thus lowering PLT count in the ITP mice model.

HLA-DR and HLA-DQ Polymorphism Correlation with Sexually Transmitted Infection Caused by Chlamydia trachomatis

Background and Objectives: Chlamydia trachomatis (C. trachomatis) represents one of the most prevalent bacterial sexually transmitted diseases. This study aims to explore the relationship between HLA alleles/genotypes/haplotypes and C. trachomatis infection to better understand high-risk individuals and potential complications. Materials and Methods: This prospective study recruited participants from Transylvania, Romania. Patients with positive NAAT tests for C. trachomatis from cervical/urethral secretion or urine were compared with controls regarding HLA-DR and -DQ alleles. DNA extraction for HLA typing was performed using venous blood samples. Results: Our analysis revealed that the presence of the DRB1*13 allele significantly heightened the likelihood of C. trachomatis infection (p = 0.017). Additionally, we observed that individuals carrying the DRB1*01/DRB1*13 and DQB1*03/DQB1*06 genotype had increased odds of C. trachomatis infection. Upon adjustment, the association between the DRB1*01/DRB1*13 genotype and C. trachomatis remained statistically significant. Conclusions: Our findings underscore the importance of specific HLA alleles and genotypes in influencing susceptibility to C. trachomatis infection. These results highlight the intricate relationship between host genetics and disease susceptibility, offering valuable insights for targeted prevention efforts and personalized healthcare strategies.

Phenomic landscape and pharmacogenomic implications for HLA region in a Taiwan Han Chinese population

BACKGROUND

The human leukocyte antigen (HLA) genes, exhibiting significant genetic diversity, are associated with susceptibility to various clinical diseases and diverse in drug responses. High costs of HLA sequencing and the population-specific architecture of this genetic region necessitate the establishment of a population-specific HLA imputation reference panel. Moreover, there is a lack of understanding about the genetic and phenotypic landscape of HLA variations within the Taiwanese population.

METHODS

We created models for a Taiwanese-specific HLA imputation reference panel. These models were trained with the array genotype data and HLA sequencing data from 845 Taiwanese subjects. HLA imputation was applied for 59,448 Taiwanese subjects to characterize the HLA allele and haplotype frequencies. Additionally, a phenome-wide association study (PheWAS) was conducted to identify the phenotypes associated with HLA variations. The association of the biallelic HLA variants with the binary and quantitative traits were evaluated with additive logistic and linear regression models, respectively. Furthermore, an omnibus test with likelihood-ratio test was applied for each HLA amino acid position in the multiallelic HLA amino acid polymorphisms to compare the difference between a fitted model and a null model following a χ2 distribution of n-1 degree of freedom at a position with n residues. Finally, we estimated the prevalence of adverse drug reactions (ADR)-related HLA alleles in the Taiwanese population.

RESULTS

In this study, the reference panel models displayed remarkable accuracy, with averages of 99.3%, 98.9%, and 99.1% for 2-, 4-, 6-digit alleles of the eight classical HLA genes, respectively. For PheWAS, a total of 18,136 significant associations with HLA variants across 26 phenotypes are identified (p < 5×10-8), highlighting the pleiotropy feature of the HLA region. Among the independent signals, 15 are novel, including the association of HLA-B pos 138 variation with ankylosing spondylitis (AS), and rs9266290 and rs9266292 with allergy. Through an analysis spanning the entire HLA region, we identified clusters of phenotype correlations. Finally, the carriers of pharmacogenomic related HLA alleles, including HLA-C*01:02 (35.86%), HLA-B*58:01 (20.9%), and HLA-B*15:02 (8.38%), were characterized in the Taiwanese general population.

CONCLUSIONS

We successfully delivered the HLA imputation for 59,448 Taiwanese subjects and characterized the genetic and phenotypic landscapes of the HLA variations. In addition, we quantified the estimated prevalence of the ADR-related HLA alleles in the Taiwanese population. The developed HLA imputation reference panel could be used for estimation of population HLA allele frequencies, which can facilitate further studies in the role of HLA variants in a wider range of phenotypes in the population.

Narrative Review Explaining the Role of HLA-A, -B, and -C Molecules in COVID-19 Disease in and around Africa

The coronavirus disease 2019 (COVID-19) has left a devasting effect on various regions globally. Africa has exceptionally high rates of other infectious diseases, such as tuberculosis (TB), human immunodeficiency virus (HIV), and malaria, and was not impacted by COVID-19 to the extent of other continents Globally, COVID-19 has caused approximately 7 million deaths and 700 million infections thus far. COVID-19 disease severity and susceptibility vary among individuals and populations, which could be attributed to various factors, including the viral strain, host genetics, environment, lifespan, and co-existing conditions. Host genetics play a substantial part in COVID-19 disease severity among individuals. Human leukocyte antigen (HLA) was previously been shown to be very important across host immune responses against viruses. HLA has been a widely studied gene region for various disease associations that have been identified. HLA proteins present peptides to the cytotoxic lymphocytes, which causes an immune response to kill infected cells. The HLA molecule serves as the central region for infectious disease association; therefore, we expect HLA disease association with COVID-19. Therefore, in this narrative review, we look at the HLA gene region, particularly, HLA class I, to understand its role in COVID-19 disease.

Rapid desensitization through immunoadsorption during cardiopulmonary bypass. A novel method to facilitate human leukocyte antigen incompatible heart transplantation

BACKGROUND

Anti-human leukocyte antigen (HLA)-antibody production represents a major barrier to heart transplantation, limiting recipient compatibility with potential donors and increasing the risk of complications with poor waiting-list outcomes. Currently there is no consensus to when desensitization should take place, and through what mechanism, meaning that sensitized patients must wait for a compatible donor for many months, if not years. We aimed to determine if intraoperative immunoadsorption could provide a potential desensitization methodology.

METHODS

Anti-HLA antibody-containing whole blood was added to a Cardiopulmonary bypass (CPB) circuit set up to mimic a 20 kg patient undergoing heart transplantation. Plasma was separated and diverted to a standalone, secondary immunoadsorption system, with antibody-depleted plasma returned to the CPB circuit. Samples for anti-HLA antibody definition were taken at baseline, when combined with the CPB prime (on bypass), and then every 20 min for the duration of treatment (total 180 min).

RESULTS

A reduction in individual allele median fluorescence intensity (MFI) to below clinically relevant levels (<1000 MFI), and in the majority of cases below the lower positive detection limit (<500 MFI), even in alleles with a baseline MFI >4000 was demonstrated. Reduction occurred in all cases within 120 min, demonstrating efficacy in a time period usual for heart transplantation. Flowcytometric crossmatching of suitable pseudo-donor lymphocytes demonstrated a change from T cell and B cell positive channel shifts to negative, demonstrating a reduction in binding capacity.

CONCLUSIONS

Intraoperative immunoadsorption in an ex vivo setting demonstrates clinically relevant reductions in anti-HLA antibodies within the normal timeframe for heart transplantation. This method represents a potential desensitization technique that could enable sensitized children to accept a donor organ earlier, even in the presence of donor-specific anti-HLA antibodies.

Regulatory SVA retrotransposons and classical HLA genotyped-transcripts associated with Parkinson's disease

Introduction

Parkinson's disease (PD) is a neurodegenerative and polygenic disorder characterised by the progressive loss of neural dopamine and onset of movement disorders. We previously described eight SINE-VNTR-Alu (SVA) retrotransposon-insertion-polymorphisms (RIPs) located and expressed within the Human Leucocyte Antigen (HLA) genomic region of chromosome 6 that modulate the differential co-expression of 71 different genes including the HLA classical class I and class II genes in a Parkinson's Progression Markers Initiative (PPMI) cohort.

Aims and methods

In the present study, we (1) reanalysed the PPMI genomic and transcriptomic sequencing data obtained from whole blood of 1521 individuals (867 cases and 654 controls) to infer the genotypes of the transcripts expressed by eight classical HLA class I and class II genes as well as DRA and the DRB3/4/5 haplotypes, and (2) examined the statistical differences between three different PD subgroups (cases) and healthy controls (HC) for the HLA and SVA transcribed genotypes and inferred haplotypes.

Results

Significant differences for 57 expressed HLA alleles (21 HLA class I and 36 HLA class II alleles) up to the three-field resolution and four of eight expressed SVA were detected at p<0.05 by the Fisher's exact test within one or other of three different PD subgroups (750 individuals with PD, 57 prodromes, 60 individuals who had scans without evidence of dopamine deficits [SWEDD]), when compared against a group of 654 HCs within the PPMI cohort and when not corrected by the Bonferroni test for multiple comparisons. Fourteen of 20 significant alleles were unique to the PD-HC comparison, whereas 31 of the 57 alleles overlapped between two or more different subgroup comparisons. Only the expressed HLA-DRA*01:01:01 and -DQA1*03:01:01 protective alleles (PD v HC), the -DQA1*03:03:01 risk (HC v Prodrome) or protective allele (PD v Prodrome), the -DRA*01:01:02 and -DRB4*01:03:02 risk alleles (SWEDD v HC), and the NR_SVA_381 present genotype (PD v HC) at a 5% homozygous insertion frequency near HLA-DPA1, were significant (Pc<0.1) after Bonferroni corrections. The homologous NR_SVA_381 insertion significantly decreased the transcription levels of HLA-DPA1 and HLA-DPB1 in the PPMI cohort and its presence as a homozygous genotype is a risk factor (Pc=0.012) for PD. The most frequent NR_SVA_381 insertion haplotype in the PPMI cohort was NR_SVA_381/DPA1*02/DPB1*01 (3.7%). Although HLA C*07/B*07/DRB5*01/DRB1*15/DQB1*06 was the most frequent HLA 5-loci phased-haplotype (n, 76) in the PPMI cohort, the NR_SVA_381 insertion was present in only six of them (8%).

Conclusions

These data suggest that expressed SVA and HLA gene alleles in circulating white blood cells are coordinated differentially in the regulation of immune responses and the long-term onset and progression of PD, the mechanisms of which have yet to be elucidated.

Frequencies of HLA-B alleles in Indonesian Malay Ethnic

Background

The HLA-B alleles have been used as a marker to predict drug-induced adverse reactions and as a major contributor to hypersensitivity reactions. We examined the feasibility of HLA-B alleles as pharmacogenomic markers of drug-induced hypersensitivity in an Indonesian Malay Ethnic.

Methods

Fifty-eight Indonesian individuals of Malay ethnicity were enrolled in this study. HLA-B alleles were determined using reverse sequence-specific oligonucleotide probe coupled with xMAP technology.

Results

HLA-B*15:02 (15.52%), HLA-B*35:05 (9.48%), and HLA-B*07:05 (7.76%) were frequent alleles in the Indonesian Malay ethnic populations. We discovered at least eight pharmacogenomics markers of drug-induced hypersensitivity: HLA-B*15:02, HLA-B*15:21, HLA-B*13:01, HLA-B*35:05, HLA-B*38:02, HLA-B*51:01, HLA-B*57:01, and HLA-B*58:01. HLA-B*15:02 was in the same serotype group with HLA-B*15:21, which is a B-75 serotype associated with genetic predisposition for carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis. The Indonesian population, represented by Malay, Javanese, and Sundanese ethnicities, was similar to South East Asian, Han Chinese, and Taiwanese populations based on HLA-B*15:02 frequency as the most common allele found in Malay ethnics.

Conclusion

We provided valuable information on the frequency of drug hypersensitivity-associated HLA-B alleles in Indonesian Malay ethnic population, which can improve treatment safety.

Advancements in HLA Typing Techniques and Their Impact on Transplantation Medicine

HLA typing serves as a standard practice in hematopoietic stem cell transplantation to ensure compatibility between donors and recipients, preventing the occurrence of allograft rejection and graft-versus-host disease. Conventional laboratory methods that have been widely employed in the past few years, including sequence-specific primer PCR and sequencing-based typing (SBT), currently face the risk of becoming obsolete. This risk stems not only from the extensive diversity within HLA genes but also from the rapid advancement of next-generation sequencing and third-generation sequencing technologies. Third-generation sequencing systems like single-molecule real-time (SMRT) sequencing and Oxford Nanopore (ONT) sequencing have the capability to analyze long-read sequences that span entire intronic-exonic regions of HLA genes, effectively addressing challenges related to HLA ambiguity and the phasing of multiple short-read fragments. The growing dominance of these advanced sequencers in HLA typing is expected to solidify further through ongoing refinements, cost reduction, and error rate minimization. This review focuses on hematopoietic stem cell transplantation (HSCT) and explores prospective advancements and application of HLA DNA typing techniques. It explores how the adoption of third-generation sequencing technologies can revolutionize the field by offering improved accuracy, reduced ambiguity, and enhanced assessment of compatibility in HSCT. Embracing these cutting-edge technologies is essential to advancing the success rates and outcomes of hematopoietic stem cell transplantation. This review underscores the importance of staying at the forefront of HLA typing techniques to ensure the best possible outcomes for patients undergoing HSCT.

Contribution of HLA class I (A, B, C) and HLA class II (DRB1, DQA1, DQB1) alleles and haplotypes in exploring ethnic origin of central Tunisians

BACKGROUND

Estimation of HLA (Human leukocyte Antigen) alleles' frequencies in populations is essential to explore their ethnic origin. Anthropologic studies of central Tunisian population were rarely reported. Then, in this work, we aimed to explore the origin of central Tunisian population using HLA alleles and haplotypes frequencies.

METHODS

HLA class I (A, B, C) and HLA class II (DRB1, DQA1, DQB1) loci genotyping of 272 healthy unrelated organ donors was performed by Polymerase Chain Reaction-Sequence Specific Oligonucleotide (PCR-SSO). We compared central Tunisians with other populations (Arabs, Berbers, Mediterraneans, Europeans, Africans, etc.) using alleles and haplotypes frequencies, genetic distances, Neighbour-Joining dendrogram and correspondence analysis.

RESULTS

Among the 19 HLA A alleles, the 26 HLA B alleles, the 13 HLA C alleles, the 15 HLA DRB1 alleles, the 6 HLA DQA1 alleles and the 5 HLA DQB1 alleles identified in the studied population, HLA A*02 (22.8%), HLA B*50 (13.1%), HLA C*06 (21.8%), HLA DRB1*07 (17.8%), HLA DQA1*01 (32.1%) and HLA DQB1*03 (31.6%) were the most frequent alleles. The extended haplotypes HLA A*02-B*50-C*06-DRB1*07-DQA1*02-DQB1*02 (1.97%) was the most frequent HLA six-loci haplotype.

CONCLUSION

Central Tunisians were very close to other Tunisian populations, to Iberians and North Africans. They were rather distant from sub-Saharan populations and eastern Mediterraneans especially Arabs although the strong cultural and religious impact of Arabs in this population.

Fighting flu: novel CD8+ T-cell targets are required for future influenza vaccines

Seasonal influenza viruses continue to cause severe medical and financial complications annually. Although there are many licenced influenza vaccines, there are billions of cases of influenza infection every year, resulting in the death of over half a million individuals. Furthermore, these figures can rise in the event of a pandemic, as seen throughout history, like the 1918 Spanish influenza pandemic (50 million deaths) and the 1968 Hong Kong influenza pandemic (~4 million deaths). In this review, we have summarised many of the currently licenced influenza vaccines available across the world and current vaccines in clinical trials. We then briefly discuss the important role of CD8+ T cells during influenza infection and why future influenza vaccines should consider targeting CD8+ T cells. Finally, we assess the current landscape of known immunogenic CD8+ T-cell epitopes and highlight the knowledge gaps required to be filled for the design of rational future influenza vaccines that incorporate CD8+ T cells.

Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis

BACKGROUND

Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear.

METHODS

To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk.

RESULTS

We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks.

CONCLUSION

Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.

The Influence of HLA Polymorphisms on the Severity of COVID-19 in the Romanian Population

In this study, we aimed to investigate whether specific HLA alleles found in patients from Romania and the Republic of Moldova were associated with the severity of COVID-19 infection and its associated mortality. We analyzed the HLA alleles at the -A, -B, -C, -DRB1, and -DQB1 loci in a cohort of 130 individuals with severe and extremely severe forms of COVID-19, including 44 individuals who died. We compared these findings to a control group consisting of individuals who had either not been diagnosed with COVID-19 or had experienced mild forms of the disease. Using multivariate logistic regression models, we discovered that the B*27 and B*50 alleles were associated with an increased susceptibility to developing a severe form of COVID-19. The A*33 and C*15 alleles showed potential for offering protection against the disease. Furthermore, we identified two protective alleles (A*03 and DQB1*02) against the development of extremely severe forms of COVID-19. By utilizing score statistics, we established a statistically significant association between haplotypes and disease severity (p = 0.021). In summary, this study provides evidence that HLA genotype plays a role in influencing the clinical outcome of COVID-19 infection.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Genotype imputation methods for whole and complex genomic regions utilizing deep learning technology

The imputation of unmeasured genotypes is essential in human genetic research, particularly in enhancing the power of genome-wide association studies and conducting subsequent fine-mapping. Recently, several deep learning-based genotype imputation methods for genome-wide variants with the capability of learning complex linkage disequilibrium patterns have been developed. Additionally, deep learning-based imputation has been applied to a distinct genomic region known as the major histocompatibility complex, referred to as HLA imputation. Despite their various advantages, the current deep learning-based genotype imputation methods do have certain limitations and have not yet become standard. These limitations include the modest accuracy improvement over statistical and conventional machine learning-based methods. However, their benefits include other aspects, such as their "reference-free" nature, which ensures complete privacy protection, and their higher computational efficiency. Furthermore, the continuing evolution of deep learning technologies is expected to contribute to further improvements in prediction accuracy and usability in the future.

Multi-ancestry meta-analysis of host genetic susceptibility to tuberculosis identifies shared genetic architecture

The heritability of susceptibility to tuberculosis (TB) disease has been well recognized. Over 100 genes have been studied as candidates for TB susceptibility, and several variants were identified by genome-wide association studies (GWAS), but few replicate. We established the International Tuberculosis Host Genetics Consortium to perform a multi-ancestry meta-analysis of GWAS, including 14,153 cases and 19,536 controls of African, Asian, and European ancestry. Our analyses demonstrate a substantial degree of heritability (pooled polygenic h2 = 26.3%, 95% CI 23.7-29.0%) for susceptibility to TB that is shared across ancestries, highlighting an important host genetic influence on disease. We identified one global host genetic correlate for TB at genome-wide significance (p<5 × 10-8) in the human leukocyte antigen (HLA)-II region (rs28383206, p-value=5.2 × 10-9) but failed to replicate variants previously associated with TB susceptibility. These data demonstrate the complex shared genetic architecture of susceptibility to TB and the importance of large-scale GWAS analysis across multiple ancestries experiencing different levels of infection pressure.

Deep Learning-Based HLA Allele Imputation Applicable to GWAS

Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of imputation accuracy and computational costs. Here, I describe Deep*HLA, a recently published method that employs deep learning algorithms to accurately impute HLA alleles from regional single nucleotide variants. Deep*HLA was trained and benchmarked on two reference panels of different ancestries. Deep*HLA achieved high imputation accuracy with relatively mild reduced imputation accuracy for rare alleles. I provide a detailed protocol for running Deep*HLA, including instructions for data preprocessing, model training, and imputation. Deep*HLA is implemented in Python 3 and is freely available.

HLA Genetics for the Human Diseases

Highly polymorphic human leukocyte antigen (HLA) molecules (alleles) expressed by different classical HLA class I and class II genes have crucial roles in the regulation of innate and adaptive immune responses, transplant rejection and in the pathogenesis of numerous infectious and autoimmune diseases. To date, over 35,000 HLA alleles have been published from the IPD-IMGT/HLA database, and specific HLA alleles and HLA haplotypes have been reported to be associated with more than 100 different diseases and phenotypes. Next generation sequencing (NGS) technology developed in recent years has provided breakthroughs in various HLA genomic/gene studies and transplant medicine. In this chapter, we review the current information on the HLA genomic structure and polymorphisms, as well as the genetic context in which numerous disease associations have been identified in this region.

Association of HLA class I and II genes with cervical cancer susceptibility in a Han Chinese population

Cervical cancer (CC) is one of the leading causes of cancer-related death in females worldwide. Genome-wide association studies (GWASs) have identified CC-related susceptibility loci in HLA regions. To investigate the associations between HLA genes and cervical intraepithelial neoplasia (CIN) or cervical cancer (CC), six loci of HLA class I (HLA-A, -B, and -C) and II (HLA-DRB1, -DPB1, and -DQB1) were selected for genotyping, and the associations between these alleles or their haplotypes with CIN or CC risk or protection from disease were evaluated. In total, 2193 participants, including 909 healthy individuals in the control group, 769 patients with CC, and 515 patients with CIN2+ (CIN II and III), were enrolled in the current study. HLA genes were genotyped using the NGSgo Illumina MiSeq workflow, and the associations between these loci and CIN2+ or CC at the allele and haplotype levels were analyzed. The allele frequencies of HLA-A*33:03, B*58:01, C*03:02, DPB1*05:01, and DRB1*12:01 were lower in both the CC and CIN2+ groups than in the control group, whereas those of B*55:02, C*04:03, and DPB1*03:01 were higher in the CC group than in the control group. In the histologic CC type analysis, the differences in the frequencies of these alleles in squamous cell carcinoma (SCC) of the cervix and stage I CC showed a consistent trend. In the haplotype analysis, the frequency of A*33:03-C*03:02-B*58:01 was lower in the CC and CIN2+ groups than in the control group, and that of A*24:02-C*04:03-B*15:25 was higher in the CC group than in both the control and CIN2+ groups. These three different haplotype frequencies were also identified in the FIGO CC stage analysis. In addition, in human papilloma virus (HPV) genotype analyses, the frequencies of HLA-C*03:02 and DPB1*05:01 were significantly lower in the CC and CIN2+ groups than in the control group, and in SCC subgroup, the frequencies of HLA-DQB1*04:01 and DRB1*04:05 were higher in the HPV other genotype infection group than in the HPV16 infection group. In both HPV16 single infection and coinfection with other HPVs, the frequency of haplotype A*33:03-C*03:02-B*58:01 was lower in both CC and CIN2+ than in the control group, while the frequencies of A*11:01-C*14:02-B*51:01 and A*24:02-C*03:04-B*13:01 were higher in the CIN2+ than in CC and the control group. In the HPV16 and other HPV infection comparisons, the frequencies of DRB1*04:05-DQB1*04:01-DPB1*02:01 and DRB1*11:01-DQB1*03:01-DPB1*05:01 were lower in the HPV16 infection group than in the other HPV infection group. Our results suggest that the HLA class I and II genes may affect the risk of CIN and CC as well as the histologic CC types and FIGO stages of CC in the Han Chinese population. In addition, HLA genes were associated with HPV16 infection at both the allelic and haplotype levels.

Imputation-Based HLA Typing with GWAS SNPs

SNP-based imputation approaches for human leukocyte antigen (HLA) typing take advantage of the haplotype structure within the major histocompatibility complex (MHC) region. These methods predict HLA classical alleles using dense SNP genotypes, commonly found on array-based platforms used in genome-wide association studies (GWAS). The analysis of HLA classical alleles can be conducted on current SNP datasets at no additional cost. Here, we describe the workflow of HIBAG, an imputation method with attribute bagging, to infer a sample's HLA classical alleles using SNP data. Two examples are offered to demonstrate the functionality using public HLA and SNP data from the latest release of the 1000 Genomes project: genotype imputation using pre-built classifiers in a GWAS, and model training to create a new prediction model. The GPU implementation facilitates model building, making it hundreds of times faster compared to the single-threaded implementation.

Specificity of HLA monoclonal antibodies and their use to determine HLA expression on lymphocytes and peripheral blood stem cells

HLA Class I and II expression are known to differ locus-to-locus, however, HLA expression on the cell-surface is frequently reported as the total amount of HLA Class I or II antigens. This is despite evidence that indicates the differential expression of HLA can influence patient outcomes post-transplantation. Although numerous commercially available HLA monoclonal antibodies (mAbs) exist to characterize HLA expression, there is currently a lack of detailed information regarding their reactivities to HLA specificities. The specificities of locus-specific HLA mAbs (nine Class I and four Class II mAbs) were evaluated by two solid-phase Luminex single antigen bead assays. The reactivity patterns of these mAbs were then confirmed by flow cytometry using lymphocytes and PBSCs (peripheral blood stem cells). Out of the 13 HLA mAbs tested, only four (one Class I and three Class II mAbs) displayed intra-locus reactivity without also reacting to inter-locus specificities. Epitope analysis revealed the presence of shared epitopes across numerous HLA loci, explaining much of the observed inter-locus reactivity. The specificity of the HLA mAbs seen in solid-phase assays was confirmed against PBSCs and lymphocytes by flow cytometry. Using this method, we observed differences in the cell surface expression of HLA-C, HLA-DR, HLA-DQ, and HLA-DP between PBSCs and lymphocytes. Our results emphasize the need to characterize the reactivity patterns of HLA mAbs using solid-phase assays before their use on cells. Through understanding the reactivity of these HLA mAbs, the cellular expression of HLA can be more accurately assessed in downstream assays.

HLA-DPB1*13:01 associates with enhanced, and KIR2DS4*001 with diminished protection from developing severe COVID-19

Extreme polymorphism of HLA and killer-cell immunoglobulin-like receptors (KIR) differentiates immune responses across individuals. Additional to T cell receptor interactions, subsets of HLA class I act as ligands for inhibitory and activating KIR, allowing natural killer (NK) cells to detect and kill infected cells. We investigated the impact of HLA and KIR polymorphism on the severity of COVID-19. High resolution HLA class I and II and KIR genotypes were determined from 403 non-hospitalized and 1575 hospitalized SARS-CoV-2 infected patients from Italy collected in 2020. We observed that possession of the activating KIR2DS4*001 allotype is associated with severe disease, requiring hospitalization (OR = 1.48, 95% CI 1.20-1.85, pc  = 0.017), and this effect is greater in individuals homozygous for KIR2DS4*001 (OR = 3.74, 95% CI 1.75-9.29, pc  = 0.003). We also observed the HLA class II allotype, HLA-DPB1*13:01 protects SARS-CoV-2 infected patients from severe disease (OR = 0.49, 95% CI 0.33-0.74, pc  = 0.019). These association analyses were replicated using logistic regression with sex and age as covariates. Autoantibodies against IFN-α associated with COVID-19 severity were detected in 26% of 156 hospitalized patients tested. HLA-C*08:02 was more frequent in patients with IFN-α autoantibodies than those without, and KIR3DL1*01502 was only present in patients lacking IFN-α antibodies. These findings suggest that KIR and HLA polymorphism is integral in determining the clinical outcome following SARS-CoV-2 infection, by influencing the course both of innate and adaptive immunity.

Allele Frequency Net Database

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) system. In addition, over the last four years, AFND has also incorporated genotype raw data from 85,000 individuals comprising 215 population samples from 39 countries. Moreover, more population data sets containing next generation sequencing data spanning >3 million individuals have been added. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, epitope prediction algorithms for population coverage in vaccine development, population genetics, among many others. In this chapter, we present an update of the most used searching mechanisms as described in a previous volume and some of the latest developments included in AFND.

Regulation of expression quantitative trait loci by SVA retrotransposons within the major histocompatibility complex

Genomic and transcriptomic studies of expression quantitative trait loci (eQTL) revealed that SINE-VNTR-Alu (SVA) retrotransposon insertion polymorphisms (RIPs) within human genomes markedly affect the co-expression of many coding and noncoding genes by coordinated regulatory processes. This study examined the polymorphic SVA modulation of gene co-expression within the major histocompatibility complex (MHC) genomic region where more than 160 coding genes are involved in innate and adaptive immunity. We characterized the modulation of SVA RIPs utilizing the genomic and transcriptomic sequencing data obtained from whole blood of 1266 individuals in the Parkinson's Progression Markers Initiative (PPMI) cohort that included an analysis of human leukocyte antigen (HLA)-A regulation in a subpopulation of the cohort. The regulatory properties of eight SVAs located within the class I and class II MHC regions were associated with differential co-expression of 71 different genes within and 75 genes outside the MHC region. Some of the same genes were affected by two or more different SVA. Five SVA are annotated in the human genomic reference sequence GRCh38.p14/hg38, whereas the other three were novel insertions within individuals. We also examined and found distinct structural effects (long and short variants and the CT internal variants) for one of the SVA (R_SVA_24) insertions on the differential expression of the HLA-A gene within a subpopulation (550 individuals) of the PPMI cohort. This is the first time that many HLA and non-HLA genes (multilocus expression units) and splicing mechanisms have been shown to be regulated by eight structurally polymorphic SVA within the MHC genomic region by applying precise statistical analysis of RNA data derived from the blood samples of a human cohort population. This study shows that SVA within the MHC region are important regulators or rheostats of gene co-expression that might have potential roles in diversity, health, and disease.

Genome-wide association studies of response and side effects to the BNT162b2 vaccine in Italian healthcare workers: Increased antibody levels and side effects in carriers of the HLA-A*03:01 allele

The remarkable variability of response to vaccines against SARS-CoV-2 is apparent. The present study aims to estimate the extent to which the host genetic background contributes to this variability in terms of immune response and side effects following the administration of the BNT162b2 vaccine. We carried out a genome wide association study (GWAS) by genotyping 873 Italian healthcare workers who underwent anti-SARS-CoV-2 vaccination with the BNT162b2 vaccine and for whom information about anti-SARS-CoV-2 spike antibodies titers and vaccine side effects were available. The GWAS revealed a significant association between the HLA locus and the anti-SARS-CoV-2 Spike antibodies level at 2 months following the first dose of vaccine (SNP: rs1737060; p = 9.80 × 10-11 ). In particular, we observed a positive association between the antibody levels and the presence of the HLA-A*03:01 allele. The same allele was found associated with a 2-2.4-fold increased risk of experiencing specific side effects such as fever, chills and myalgia and a 1.5-1.8-fold increased risk of joint pain, nausea, fatigue, headache and asthenia, independently of age and sex. This study confirms that the heterogeneity in the immune response to the BNT162b2 vaccine and in its side effects are at least partially influenced by genetic variants. This information, integrated with individual biological and lifestyle-related correlates, could be of use in the definition of algorithms aimed at the identification of subjects in which the administration of additional vaccine doses would be particularly beneficial to maintain immunity against the virus.

B cell MHC haplotype affects follicular inclusion, germinal center participation and plasma cell differentiation in a mouse model of lupus

Introduction

MHC class II molecules are essential for appropriate immune responses against pathogens but are also implicated in pathological responses in autoimmune diseases and transplant rejection. Previous studies have shed light on the systemic contributions of MHC haplotypes to the development and severity of autoimmune diseases. In this study, we addressed the B cell intrinsic MHC haplotype impact on follicular inclusion, germinal center (GC) participation and plasma cell (PC) differentiation in the context of systemic lupus erythematosus (SLE).

Methods

We leveraged the 564Igi mouse model which harbors a B cell receptor knock-in from an autoreactive B cell clone recognizing ribonuclear components, including double-stranded DNA (dsDNA). This model recapitulates the central hallmarks of the early stages of SLE. We compared 564Igi heterozygous offspring on either H2b/b, H2b/d, or H2d/d background.

Results

This revealed significantly higher germinal center (GC) B cell levels in the spleens of H2b/b and H2b/d as compared to H2d/d (p<0.0001) mice. In agreement with this, anti-dsDNA-antibody levels were higher in H2b/b and H2b/d than in H2d/d (p<0.0001), with H2b/b also being higher compared to H2b/d (p<0.01). Specifically, these differences held true both for autoantibodies derived from the knock-in clone and from wild-type (WT) derived clones. In mixed chimeras where 564Igi H2b/b, H2b/d and H2d/d cells competed head-to-head in the same environment, we observed a significantly higher inclusion of H2b/b cells in GC and PC compartments relative to their representation in the B cell repertoire, compared to H2b/d and H2d/d cells. Furthermore, in mixed chimeras in which WT H2b/b and WT H2d/d cells competed for inclusion in GCs associated with an epitope spreading process, H2b/b cells participated to a greater extent and contributed more robustly to the PC compartment. Finally, immature WT H2b/b cells had a higher baseline of BCRs with an autoreactive idiotype and were subject to more stringent negative selection at the transitional stage.

Discussion

Taken together, our findings demonstrate that B cell intrinsic MHC haplotype governs their capacity for participation in the autoreactive response at multiple levels: follicular inclusion, GC participation, and PC output. These findings pinpoint B cells as central contributors to precipitation of autoimmunity.

KiT-GENIE, the French genetic biobank of kidney transplantation

KiT-GENIE is a monocentric DNA biobank set up to consolidate the very rich and homogeneous DIVAT French cohort of kidney donors and recipients (D/R) in order to explore the molecular factors involved in kidney transplantation outcomes. We collected DNA samples for kidney transplantations performed in Nantes, and we leveraged GWAS genotyping data for securing high-quality genetic data with deep SNP and HLA annotations through imputations and for inferring D/R genetic ancestry. Overall, the biobank included 4217 individuals (n = 1945 D + 2,272 R, including 1969 D/R pairs), 7.4 M SNPs and over 200 clinical variables. KiT-GENIE represents an accurate snapshot of kidney transplantation clinical practice in Nantes between 2002 and 2018, with an enrichment in living kidney donors (17%) and recipients with focal segmental glomerulosclerosis (4%). Recipients were predominantly male (63%), of European ancestry (93%), with a mean age of 51yo and 86% experienced their first graft over the study period. D/R pairs were 93% from European ancestry, and 95% pairs exhibited at least one HLA allelic mismatch. The mean follow-up time was 6.7 years with a hindsight up to 25 years. Recipients experienced biopsy-proven rejection and graft loss for 16.6% and 21.3%, respectively. KiT-GENIE constitutes one of the largest kidney transplantation genetic cohorts worldwide to date. It includes homogeneous high-quality clinical and genetic data for donors and recipients, hence offering a unique opportunity to investigate immunogenetic and genetic factors, as well as donor-recipient interactions and mismatches involved in rejection, graft survival, primary disease recurrence and other comorbidities.

Immunogenetics of autism spectrum disorder: A systematic literature review

The aetiology of autism spectrum disorder (ASD) is complex and, partly, accounted by genetic factors. Nonetheless, the genetic underpinnings of ASD are poorly defined. The presence of immune dysregulations in autistic individuals, and their families, supports a role of the immune system and its genetic regulators. Albeit immune responses belong either to the innate or adaptive arms, the overall immune system genetics is broad, and encompasses a multitude of functionally heterogenous pathways which may have different influences on ASD. Hence, to gain insights on the immunogenetic underpinnings of ASD, we conducted a systematic literature review of previous immune genetic and transcription studies in ASD. We defined a list of immune genes relevant to ASD and explored their neuro-immune function. Our review confirms the presence of immunogenetic variability in ASD, accounted by inherited variations of innate and adaptive immune system genes and genetic expression changes in the blood and post-mortem brain of autistic individuals. Besides their immune function, the identified genes control neurodevelopment processes (neuronal and synaptic plasticity) and are highly expressed in pre/peri-natal periods. Hence, our synthesis bolsters the hypothesis that perturbation in immune genes may contribute to ASD by derailing the typical trajectory of neurodevelopment. Our review also helped identifying some of the limitations of prior immunogenetic research in ASD. Thus, alongside clarifying the neurodevelopment role of immune genes, we outline key considerations for future work into the aetiology of ASD and possible novel intervention targets.

Abdominal surgery induces long-lasting changes in expression and binding of CTCF with impact on Major Histocompatibility Complex II transcription in circulating human monocytes

BACKGROUND

Postoperative immunosuppression has been recognized as an important driver of surgery-related morbidity and mortality. It is characterized by lymphocyte depression and impaired monocyte capability to present foreign antigens to T-cells via Major Histocompatibility Complex, Class II (MHC-II) molecules. In patients with postoperative abdominal sepsis, we previously detected a persisting differential binding of the CCCTC-Binding Factor (CTCF), a superordinate regulator of transcription, inside the MHC-II region with specific impact on human leucocyte antigen (HLA) gene expression. In this prospective exploratory study, we investigated to which extent major surgery affects the MHC-II region of circulating CD14+-monocytes.

RESULTS

In non-immunocompromised patients undergoing elective major abdominal surgery, a postoperative loss of monocyte HLA-DR surface receptor density was accompanied by a decline in the transcription levels of the classical MHC-II genes HLA-DRA, HLA-DRB1, HLA-DPA1 and HLA-DPB1. The surgical event decreased the expression of the transcriptional MHC-II regulators CIITA and CTCF and led to a lower CTCF enrichment at an intergenic sequence within the HLA-DR subregion. During the observation period, we found a slow and only incomplete restoration of monocyte HLA-DR surface receptor density as well as a partial recovery of CIITA, HLA-DRA and HLA-DRB1 expression. In contrast, transcription of HLA-DPA1, HLA-DPB1, CTCF and binding of CTCF within the MHC-II remained altered.

CONCLUSION

In circulating monocytes, major surgery does not globally affect MHC-II transcription but rather induces specific changes in the expression of selected HLA genes, followed by differential recovery patterns and accompanied by a prolonged reduction of CTCF expression and binding within the MHC-II region. Our results hint toward a long-lasting impact of a major surgical intervention on monocyte functionality, possibly mediated by epigenetic changes that endure the life span of the individual cell.

Assessing HLA imputation accuracy in a West African population

The Human Leukocyte Antigen (HLA) region plays an important role in autoimmune and infectious diseases. HLA is a highly polymorphic region and thus difficult to impute. We, therefore, sought to evaluate HLA imputation accuracy, specifically in a West African population, since they are understudied and are known to harbor high genetic diversity. The study sets were selected from 315 Gambian individuals within the Gambian Genome Variation Project (GGVP) Whole Genome Sequence datasets. Two different arrays, Illumina Omni 2.5 and Human Hereditary and Health in Africa (H3Africa), were assessed for the appropriateness of their markers, and these were used to test several imputation panels and tools. The reference panels were chosen from the 1000 Genomes (1kg-All), 1000 Genomes African (1kg-Afr), 1000 Genomes Gambian (1kg-Gwd), H3Africa, and the HLA Multi-ethnic datasets. HLA-A, HLA-B, and HLA-C alleles were imputed using HIBAG, SNP2HLA, CookHLA, and Minimac4, and concordance rate was used as an assessment metric. The best performing tool was found to be HIBAG, with a concordance rate of 0.84, while the best performing reference panel was the H3Africa panel, with a concordance rate of 0.62. Minimac4 (0.75) was shown to increase HLA-B allele imputation accuracy compared to HIBAG (0.71), SNP2HLA (0.51) and CookHLA (0.17). The H3Africa and Illumina Omni 2.5 array performances were comparable, showing that genotyping arrays have less influence on HLA imputation in West African populations. The findings show that using a larger population-specific reference panel and the HIBAG tool improves the accuracy of HLA imputation in a West African population.

Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci

BACKGROUND

DEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate susceptibility regions by considering the risk signals from overlapping groups of sequential variants across the genome.

METHODS

We applied a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer data from the Colon Cancer Family Registry (CCFR; 5,735 cases and 3,688 controls), and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO; 8,865 cases and 10,285 controls) studies. A DEPTH score > 1 was used to identify candidate susceptibility regions common to both analyses. We compared DEPTH results against those from conventional genome-wide association study (GWAS) analyses of these two studies as well as against 132 published susceptibility regions.

RESULTS

Initial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) candidate susceptibility regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 candidate susceptibility regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 regions that would not be detected using conventional GWAS methods, nor had they been identified by previous colorectal cancer GWASs. We found four reproducible candidate susceptibility regions (2q22.2, 2q33.1, 6p21.32, 13q14.3). The highest DEPTH scores were in the human leukocyte antigen locus at 6p21 where the strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data.

CONCLUSIONS

DEPTH can identify candidate susceptibility regions for colorectal cancer not identified using conventional analyses of larger datasets.

IMPACT

DEPTH has potential as a powerful complementary tool to conventional GWAS analyses for discovering susceptibility regions within the genome.

The genetic variant rs55986091 HLA-DQB1 is associated with a protective effect against cervical cancer

Introduction

Cervical cancer (CC) is a prevalent malignancy affecting women globally. The primary causative factor of CC is the high-risk oncogenic human papillomavirus (HR-HPV). However, it is noteworthy that not all women infected with HR-HPV develop cancer, indicating the potential involvement of genetic predisposition in the development of CC. This study aims to identify genetic risks and their distribution in groups of women with different epidemiological features of HR-HPV.

Materials and methods

A comparison was conducted among four groups of women, comprising 218 HPV-negative women, 120 HPV-positive women, 191 women diagnosed with cervical intraepithelial neoplasia (CIN) grade 2 or 3, and 124 women diagnosed with CC. The analysis focused on four single nucleotide polymorphisms (SNPs): rs55986091 in HLA-DQB1, rs138446575 in TTC34, rs1048943 in CYP1A1, and rs2910164 in miRNA-146a.

Results

The rs55986091-A allele exhibited a protective effect within the "CC" group when compared to the "HPV-Negative" group (OR = 0.4, 95% CI= 0.25-0.65) using a log-additive model. Additionally, similar protective effects were observed in the "CIN 2/3" group compared to the "HPV-Negative" group (OR = 0.47, 95% CI = 0.28-0.79).

Conclusion

The data obtained emphasize the importance of developing PCR-based diagnostic kits for the identification of SNP alleles, particularly for rs55986091, among HR-HPV-positive women within the Russian population.

Effects of Human Leukocyte Antigen DRB1 Genetic Polymorphism on Anti-Cyclic Citrullinated Peptide (ANTI-CCP) and Rheumatoid Factor (RF) Expression in Rheumatoid Arthritis (RA) Patients

Rheumatoid arthritis (RA) is a systemic disease characterized by non-infectious inflammation of the joints and surrounding tissues, which can cause severe health problems, affect the patient's daily life, and even cause death. RA can be clinically diagnosed by the occurrence of blood serological markers, rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (anti-CCP). However, about 20% of RA patients exhibit negative results for both markers, which makes RA diagnosis difficult and, therefore, may delay the effective treatment. Previous studies found some evidence that human leukocyte antigen (HLA)-related genes might be the susceptibility genes for RA and their polymorphisms might contribute to varieties of susceptibility and disease severity. This study aimed for the genetic polymorphisms of the RA patient genome and their effects on the RA patient's serological makers, RF and anti-CCP. A total of 4580 patients' electronic medical records from 1992 to 2020 were retrieved from the China Medical University Hospital database. The most representative single-nucleotide polymorphisms (SNPs) were identified through a genome-wide association study (GWAS) followed by enzyme-linked immunosorbent assay (ELISA) validation using the blood from 30 additional RA patients. The results showed significant changes at the position of chromosome 6 with rs9270481 being the most significant locus, which indicated the location of the HLA-DRB1 gene. Further, patients with the CC genotype at this locus were more likely to exhibit negative results for RF and anti-CCP than those with the TT genotype. The C allele was also more likely to be associated with negative results for RF and anti-CCP. The results demonstrated that a genetic polymorphism at rs9270481 affected the expression of RF and anti-CCP in RA patients, which might indicate the necessity to develop a personalized treatment plan for each individual patient based on the genetic profile.

Strategies for overcoming bottlenecks in allogeneic CAR-T cell therapy

Patient-derived autologous chimeric antigen receptor (CAR)-T cell therapy is a revolutionary breakthrough in immunotherapy and has made impressive progress in both preclinical and clinical studies. However, autologous CAR-T cells still have notable drawbacks in clinical manufacture, such as long production time, variable cell potency and possible manufacturing failures. Allogeneic CAR-T cell therapy is significantly superior to autologous CAR-T cell therapy in these aspects. The use of allogeneic CAR-T cell therapy may provide simplified manufacturing process and allow the creation of 'off-the-shelf' products, facilitating the treatments of various types of tumors at less delivery time. Nevertheless, severe graft-versus-host disease (GvHD) or host-mediated allorejection may occur in the allogeneic setting, implying that addressing these two critical issues is urgent for the clinical application of allogeneic CAR-T cell therapy. In this review, we summarize the current approaches to overcome GvHD and host rejection, which empower allogeneic CAR-T cell therapy with a broader future.

Improved haplotype resolution of highly duplicated MHC genes in a long-read genome assembly using MiSeq amplicons

Long-read sequencing offers a great improvement in the assembly of complex genomic regions, such as the major histocompatibility complex (MHC) region, which can contain both tandemly duplicated MHC genes (paralogs) and high repeat content. The MHC genes have expanded in passerine birds, resulting in numerous MHC paralogs, with relatively high sequence similarity, making the assembly of the MHC region challenging even with long-read sequencing. In addition, MHC genes show rather high sequence divergence between alleles, making diploid-aware assemblers incorrectly classify haplotypes from the same locus as sequences originating from different genomic regions. Consequently, the number of MHC paralogs can easily be over- or underestimated in long-read assemblies. We therefore set out to verify the MHC diversity in an original and a haplotype-purged long-read assembly of one great reed warbler Acrocephalus arundinaceus individual (the focal individual) by using Illumina MiSeq amplicon sequencing. Single exons, representing MHC class I (MHC-I) and class IIB (MHC-IIB) alleles, were sequenced in the focal individual and mapped to the annotated MHC alleles in the original long-read genome assembly. Eighty-four percent of the annotated MHC-I alleles in the original long-read genome assembly were detected using 55% of the amplicon alleles and likewise, 78% of the annotated MHC-IIB alleles were detected using 61% of the amplicon alleles, indicating an incomplete annotation of MHC genes. In the haploid genome assembly, each MHC-IIB gene should be represented by one allele. The parental origin of the MHC-IIB amplicon alleles in the focal individual was determined by sequencing MHC-IIB in its parents. Two of five larger scaffolds, containing 6-19 MHC-IIB paralogs, had a maternal and paternal origin, respectively, as well as a high nucleotide similarity, which suggests that these scaffolds had been incorrectly assigned as belonging to different loci in the genome rather than as alternate haplotypes of the same locus. Therefore, the number of MHC-IIB paralogs was overestimated in the haploid genome assembly. Based on our findings we propose amplicon sequencing as a suitable complement to long-read sequencing for independent validation of the number of paralogs in general and for haplotype inference in multigene families in particular.

Exploring the Immunomodulatory Properties of Stem Cells in Combating COVID-19: Can We Expect More?

Since the first appearance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in December 2019, the disease has displayed a remarkable interindividual variability in the global population, resulting in different mortality and morbidity rates. Still, an effective cure against SARS-CoV-2 has not been developed, and therefore, alternative therapeutic protocols must also be evaluated. Considering that stem cells, especially Mesenchymal Stromal Cells (MSCs), are characterized by both regenerative and immunomodulatory properties and that their safety and tolerability have been investigated previously, these cells could potentially be applied against coronavirus disease 19 (COVID-19). In addition, an individual's genetic background is further related to disease pathogenesis, especially rare Inborn Errors of Immunity (IEIs), autoantibodies against Interferon type I, and the presence of different Human Leukocyte Antigens (HLA) alleles, which are actively associated with protection or susceptibility in relation to SARS-CoV-2. Herein, the use of MSCs as a potential stem cell therapy will require a deep understanding of their immunomodulatory properties associated with their HLA alleles. In such a way, HLA-restricted MSC lines can be developed and applied precisely, offering more solutions to clinicians in attenuating the mortality of SARS-CoV-2.

Frequency changes in HLA-I alleles: A marker to guide immunotherapy in lung adenocarcinoma patients and its relationship with tumor mutational burden and PD-L1 expression

BACKGROUND

The aim of the study was to investigate differences in HLA-I alleles between lung adenocarcinoma patients and healthy controls and determine their association with PD-L1 expression and tumor mutational burden (TMB) to understand the mechanism underlying lung adenocarcinoma susceptibility.

METHODS

Differences in HLA allele frequencies between the two groups were analyzed in a case-control study. PD-L1 expression and TMB in lung adenocarcinoma patients were determined and their relationships with HLA-I were analyzed.

RESULTS

The lung adenocarcinoma group showed significantly higher HLA-A*30:01 (p = 0.0067, odds ratio [OR], 1.834; 95% confidence interval [CI]: 1.176-2.860), B*13:02 (p = 0.0050, OR, 1.855; 95% CI: 1.217-2.829), and C*06:02 (p = 0.0260, OR, 1.478; 95% CI: 1.060-2.060) and significantly lower B*51:01 (p = 0.0290, OR, 0.6019; 95% CI: 0.3827-0.9467), and C*14:02 (p = 0.0255, OR, 0.5089; 95% CI: 0.2781-0.9312) than the control group. Haplotype analysis results showed that HLA-A*30:01-B*13:02 (p = 0.0100, OR, 1.909; 95% CI: 1.182-3.085), A*11:01-C*01:02 (p = 0.0056, OR, 1.909; 95% CI: 1.182-3.085), A*30:01-C*06:02 (p = 0.0111, OR, 1.846; 95% CI: 1.147-2.969), and B*13:02-C*06:02 (p = 0.0067, OR, 1.846; 95% CI: 1.147-2.969) frequencies significantly increased and B*51:01-C*14:02 (p = 0.0219, OR, 0.490; 95% CI: 0.263-0.914) frequency significantly decreased in lung adenocarcinoma patients. Three-locus haplotype analysis showed that HLA-A*30:01-B*13:02-C*06:02 frequency (p = 0.0100, OR, 1.909; 95% CI: 1.182-3.085) significantly increased in patients.

CONCLUSION

HLA-A*30:01, B*13:02, and C*06:02 may be the susceptibility genes and HLA-B*51:01 and C*14:01 act as the resistance genes of lung adenocarcinoma. The changes in HLA-I allele frequencies had no association with PD-L1 expression and TMB among these patients.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

Detection of Nonsynonymous Single Variants in Human HLA-DRB1 Exon 2 Associated with Renal Transplant Rejection

Background: HLA-DRB1 is the most polymorphic gene in the human leukocyte antigen (HLA) class II, and exon 2 is critical because it encodes antigen-binding sites. This study aimed to detect functional or marker genetic variants of HLA-DRB1 exon 2 in renal transplant recipients (acceptance and rejection) using Sanger sequencing. Methods: This hospital-based case-control study collected samples from two hospitals over seven months. The 60 participants were equally divided into three groups: rejection, acceptance, and control. The target regions were amplified and sequenced by PCR and Sanger sequencing. Several bioinformatics tools have been used to assess the impact of non-synonymous single-nucleotide variants (nsSNVs) on protein function and structure. The sequences data that support the findings of this study with accession numbers (OQ747803-OQ747862) are available in National Center for Biotechnology Information (GenBank database). Results: Seven SNVs were identified, two of which were novel (chr6(GRCh38.p12): 32584356C>A (K41N) and 32584113C>A (R122R)). Three of the seven SNVs were non-synonymous and found in the rejection group (chr6(GRCh38.p12): 32584356C>A (K41N), 32584304A>G (Y59H), and 32584152T>A (R109S)). The nsSNVs had varying effects on protein function, structure, and physicochemical parameters and could play a role in renal transplant rejection. The chr6(GRCh38.p12):32584152T>A variant showed the greatest impact. This is because of its conserved nature, main domain location, and pathogenic effects on protein structure, function, and stability. Finally, no significant markers were identified in the acceptance samples. Conclusion: Pathogenic variants can affect intramolecular/intermolecular interactions of amino acid residues, protein function/structure, and disease risk. HLA typing based on functional SNVs could be a comprehensive, accurate, and low-cost method for covering all HLA genes while shedding light on previously unknown causes in many graft rejection cases.

Resurrecting the alternative splicing landscape of archaic hominins using machine learning

Alternative splicing contributes to adaptation and divergence in many species. However, it has not been possible to directly compare splicing between modern and archaic hominins. Here, we unmask the recent evolution of this previously unobservable regulatory mechanism by applying SpliceAI, a machine-learning algorithm that identifies splice-altering variants (SAVs), to high-coverage genomes from three Neanderthals and a Denisovan. We discover 5,950 putative archaic SAVs, of which 2,186 are archaic-specific and 3,607 also occur in modern humans via introgression (244) or shared ancestry (3,520). Archaic-specific SAVs are enriched in genes that contribute to traits potentially relevant to hominin phenotypic divergence, such as the epidermis, respiration and spinal rigidity. Compared to shared SAVs, archaic-specific SAVs occur in sites under weaker selection and are more common in genes with tissue-specific expression. Further underscoring the importance of negative selection on SAVs, Neanderthal lineages with low effective population sizes are enriched for SAVs compared to Denisovan and shared SAVs. Finally, we find that nearly all introgressed SAVs in humans were shared across the three Neanderthals, suggesting that older SAVs were more tolerated in human genomes. Our results reveal the splicing landscape of archaic hominins and identify potential contributions of splicing to phenotypic differences among hominins.

Juvenile idiopathic arthritis-associated genetic loci exhibit spatially constrained gene regulatory effects across multiple tissues and immune cell types

Juvenile idiopathic arthritis (JIA) is an autoimmune, inflammatory joint disease with complex genetic etiology. Previous GWAS have found many genetic loci associated with JIA. However, the biological mechanism behind JIA remains unknown mainly because most risk loci are located in non-coding genetic regions. Interestingly, increasing evidence has found that regulatory elements in the non-coding regions can regulate the expression of distant target genes through spatial (physical) interactions. Here, we used information on the 3D genome organization (Hi-C data) to identify target genes that physically interact with SNPs within JIA risk loci. Subsequent analysis of these SNP-gene pairs using data from tissue and immune cell type-specific expression quantitative trait loci (eQTL) databases allowed the identification of risk loci that regulate the expression of their target genes. In total, we identified 59 JIA-risk loci that regulate the expression of 210 target genes across diverse tissues and immune cell types. Functional annotation of spatial eQTLs within JIA risk loci identified significant overlap with gene regulatory elements (i.e., enhancers and transcription factor binding sites). We found target genes involved in immune-related pathways such as antigen processing and presentation (e.g., ERAP2, HLA class I and II), the release of pro-inflammatory cytokines (e.g., LTBR, TYK2), proliferation and differentiation of specific immune cell types (e.g., AURKA in Th17 cells), and genes involved in physiological mechanisms related to pathological joint inflammation (e.g., LRG1 in arteries). Notably, many of the tissues where JIA-risk loci act as spatial eQTLs are not classically considered central to JIA pathology. Overall, our findings highlight the potential tissue and immune cell type-specific regulatory changes contributing to JIA pathogenesis. Future integration of our data with clinical studies can contribute to the development of improved JIA therapy.

Protection of cell therapeutics from antibody-mediated killing by CD64 overexpression

Allogeneic cell therapeutics for cancer therapy or regenerative medicine are susceptible to antibody-mediated killing, which diminishes their efficacy. Here we report a strategy to protect cells from antibody-mediated killing that relies on engineered overexpression of the IgG receptor CD64. We show that human and mouse iPSC-derived endothelial cells (iECs) overexpressing CD64 escape antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity from IgG antibodies in vitro and in ADCC-enabled mice. When CD64 expression was combined with hypoimmune genetic modifications known to protect against cellular immunity, B2M-/-CIITA-/- CD47/CD64-transgenic iECs were resistant to both IgG antibody-mediated and cellular immune killing in vitro and in humanized mice. Mechanistic studies demonstrated that CD64 or its intracellularly truncated analog CD64t effectively capture monomeric IgG and occupy their Fc, and the IgG bind and occupy their target antigens. In three applications of the approach, human CD64t-engineered thyroid epithelial cells, pancreatic beta cells and CAR T cells withstood clinically relevant levels of graft-directed antibodies and fully evaded antibody-mediated killing.