Allele Frequencies Net Database Research Articles

HLA Variants and Their Association with IgE-Mediated Banana Allergy: A Cross-sectional Study

BackgroundBanana allergy is on the rise in tropical regions. Advances in genomics and candidate gene identification have increased interest in genetic factors in food allergies. However, the genetic basis of IgE-mediated banana allergy is underexplored. ObjectiveTo characterize HLA variants and their association with IgE-mediated banana allergy. MethodsThis cross-sectional study recruited banana-allergic adults, confirmed by allergology tests, with non-allergic individuals as controls. Genomic DNA extraction and sequencing BAM files for HLA typing were conducted. Allele frequency was calculated using the direct counting method, and odds ratio (OR) with 95 % confidence interval (CI) were determined. Fisher's exact or chi-square tests were used to assess associations with Bonferroni's correction for multiple tests. The allele frequency of the Thai population from The Allele Frequency Net Database was used to compute the allele enrichment ratio (ER). ResultsA total of 59 cases and 64 controls were recruited. HLA genotyping indicated potential associations of HLA-B*15:25 (OR 11.872; p-value 0.027), HLA-C*04:03 (OR 7.636; p-value 0.033), and HLA-DQB1*06:09 (OR 11.558; p-value 0.039) with banana allergy. However, after Bonferroni correction, none of these associations reached statistical significance. Comparing allele frequency with the general population from The Allele Frequency Net Database, our ER analysis revealed a higher prevalence in the banana allergy group for B*15:25 (ER 1.849), C*04:03 (ER 1.332), and DQB1*06:09 (ER 6.602) alleles. ConclusionsThis study provides initial genetic insights into banana allergy, suggesting potential links with specific HLA alleles. Despite 12 initially identifying alleles, none were statistically significant after multiple testing correction. Larger studies are needed to detect possible significant correlations.

Class I HLA Allele Predicted Restricted Antigenic Coverages for Fap2 Protein of Fusobacterium Nucleatum Are Associated with Colorectal Cancer Incidence.

This study investigates the association between HLA-A and -B allele diversity, Fusobacterium nucleatum Fap2 protein-derived antigenic coverage, and colorectal cancer (CRC) epidemiology across diverse populations. We examined 75 HLA-I alleles and explored 698 potential HLA-A and B-restricted Fap2-derived antigens, assessing how 21 countries may respond to these peptides based on their HLA-I distribution frequencies. Additionally, we correlated in-silico predicted Fap2 population coverage with CRC epidemiology. CRC incidence and mortality data were obtained from the Global Cancer Observatory, and HLA-A and HLA-B allele frequencies from the Allele Frequency Net Database. Binding predictions for Fap2 antigens were performed using netMHCpan4, with stringent selection criteria applied to identify relevant peptides. Population coverage was calculated using the IEDB population coverage tool, and data analysis conducted using the R programming language. Clustering of HLA-A and -B allele frequencies partially differentiated countries with lower CRC incidence from others. Distinct patterns of Fap2 protein coverage were observed among different populations. interestingly, we found a significant inverse correlation between CRC incidence (p = 0.0037, R = -0.6) and predicted Fap2 antigen coverage, as well as CRC mortality (p = 0.013, R = -0.53). Furthermore, we identified a specific set of Fap2-derived peptides that bind to HLA supertypes, providing a global coverage of 99.04%. Our population-based study is the first to demonstrate that higher Fap2 coverage is associated with lower CRC incidence, underscoring the potential significance of Fap2-specific CD8+ T cell responses in CRC tumorigenesis.

Characterization of Drug-Specific CD4+ T-Cells Reveals Possible Roles of HLA Class II in the Pathogenesis of Carbamazepine Hypersensitivity Reactions

Carbamazepine (CBZ) is an aromatic anticonvulsant known to cause drug hypersensitivity reactions, which range in severity from relatively mild maculopapular exanthema to potentially fatal Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS-TEN). These reactions are known to be associated with human leukocyte antigen (HLA) class I alleles, and CBZ interacts preferentially with the related HLA proteins to activate CD8+ T-cells. This study aimed to evaluate the contribution of HLA class II in the effector mechanism(s) of CBZ hypersensitivity. CBZ-specific T-cells clones were generated from two healthy donors and two hypersensitive patients with high-risk HLA class I markers. Phenotype, function, HLA allele restriction, response pathways, and cross-reactivity of CBZ-specific T-cells were assessed using flow cytometry, proliferation analysis, enzyme-linked immunosorbent spot, and enzyme-linked immunosorbent assay. The association between HLA class II allele restriction and CBZ hypersensitivity was reviewed using Allele Frequency Net Database. Forty-four polyclonal CD4+ CBZ-specific T-cell clones were generated and found to be restricted to HLA-DR, particularly HLA-DRB1*07:01. This CD4+-mediated response proceeded through a direct pharmacological interaction between CBZ and HLA-DR molecules. Similar to the CD8+ response, CBZ-stimulated CD4+ clones secreted granulysin, a key mediator of SJS-TEN. Our database review revealed an association between HLA-DRB1*07:01 and CBZ-induced SJS-TEN. These findings implicate HLA class II antigen presentation as an additional pathogenic factor for CBZ hypersensitivity reactions. Both HLA class II molecules and drug-responsive CD4+ T-cells should be evaluated further to gain better insights into the pathogenesis of drug hypersensitivity reactions.

Distributing human leukocyte antigen (HLA) database in histocompatibility: a shift in HLA data governance

Aim: Human leukocyte antigen (HLA) population genetics has been a historical field centralizing data resource. HLA genetics databases typically facilitate access to frequencies of allele, haplotype, and genotype format information. Among many resources, the Allele Frequency Net Database (AFND) is a typical centralized repository that allows users to research and analyze immune gene frequencies in different populations around the world. With the massive increase in medical data and the strengthening of data governance laws, the proposal for a new distributed and secure model for the historical centralization method in population genetics has become important. In this paper, a new model of HLA population genetic resources, an alternative distributed version of HLA databases has been developed. It allows users to perform the same research and analysis with other remote sites without sharing their original data and monitoring data access. Methods: This new version uses the Master/Worker distributed model and offers distributed algorithms for the calculation of allelic frequencies, haplotypic frequencies and for individual genotypic calculations. The new model was evaluated on a distributed testbed for experiment-driven research Grid’5000 and has obtained good results of accuracy and execution time compared to the original centralized scheme used by researchers. Results: The results show that distributed algorithm applied to HLA population genetics resources enables usage control and enables enforcing the security framework of the data-owning institution. It gives the same results for all counting methods in population immunogenetics. With the same frequencies’ estimations, it yields a much quicker computation time in many cases, in particular for large samples. Conclusions: Distributing previously centralized resources is an interesting perspective enhancing better control of data sharing.

Allele and eight-locus haplotype frequencies in population of Belgorod region, Russia

This paper reports the HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1 and –DPB1 alleles and estimated haplotype frequencies in a population of 153 healthy potential blood marrow donors from Belgorod region, Russia. HLA genotyping was performed by next generation sequencing method (NGS). Statistical analysis were performed using Arlequin software packages. There was no deviation from Hardy-Weinberg Equilibrium detected at HLA-A, -B, -DRB1, -DQA1, -DQB1, and -DPA1 loci. Deviation was detected at the HLA-C and DPB1 locus probably due to an excess of C*12:03:01 and DPB1*04:01:01 homozygotes. These genotype data are available in the Allele Frequencies Net Database under the population name, “Russia, Belgorod Region” and the identifier: 3780.

In-silico study of influence of HLA heterogeneity on CTL responses across ethnicities to SARS-CoV-2

Differences in outcome to COVID-19 infection in different individuals is largely attributed to genetic heterogeneity leading to differential immune responses across individuals and populations. HLA is one such genetic factor that varies across individuals leading to differences in how T-cell responses are triggered against SARS-CoV-2, directly influencing disease susceptibility. HLA alleles that influence COVID-19 outcome, by virtue of epitope binding and presentation, have been identified in cohorts worldwide. However, the heterogeneity in HLA distribution across ethnic groups limits the generality of such association. In this study, we address this limitation by comparing the recognition of CTL epitopes across HLA genotypes and ethnic groups. Using HLA allele frequency data for ethnic groups from Allele Frequency Net Database (AFND), we construct synthetic populations for each ethnic group and show that CTL epitope strength varies across HLA genotypes and populations. We also observe that HLA genotypes, in certain cases, can have high CTL epitope strengths in the absence of top-responsive HLA alleles. Finally, we show that the theoretical estimate of responsiveness and hence protection offered by a HLA allele is bound to vary across ethnic groups, due to the influence of other HLA alleles within the HLA genotype on CTL epitope recognition. This emphasizes the need for studying HLA-disease associations at the genotype level rather than at a single allele level.

Predicted impact of the viral mutational landscape on the cytotoxic response against SARS-CoV-2.

The massive assessment of immune evasion due to viral mutations that increase COVID-19 susceptibility can be computationally facilitated. The adaptive cytotoxic T response is critical during primary infection and the generation of long-term protection. Here, potential HLA class I epitopes in the SARS-CoV-2 proteome were predicted for 2,915 human alleles of 71 families using the netMHCIpan EL algorithm. Allele families showed extreme epitopic differences, underscoring genetic variability of protective capacity between humans. Up to 1,222 epitopes were associated with any of the twelve supertypes, that is, allele clusters covering 90% population. Next, from all mutations identified in ~118,000 viral NCBI isolates, those causing significant epitope score reduction were considered epitope escape mutations. These mutations mainly involved non-conservative substitutions at the second and C-terminal position of the ligand core, or total ligand removal by large recurrent deletions. Escape mutations affected 47% of supertype epitopes, which in 21% of cases concerned isolates from two or more sub-continental areas. Some of these changes were coupled, but never surpassed 15% of evaded epitopes for the same supertype in the same isolate, except for B27. In contrast to most supertypes, eight allele families mostly contained alleles with few SARS-CoV-2 ligands. Isolates harboring cytotoxic escape mutations for these families co-existed geographically within sub-Saharan and Asian populations enriched in these alleles according to the Allele Frequency Net Database. Collectively, our findings indicate that escape mutation events have already occurred for half of HLA class I supertype epitopes. However, it is presently unlikely that, overall, it poses a threat to the global population. In contrast, single and double mutations for susceptible alleles may be associated with viral selective pressure and alarming local outbreaks. The integration of genomic, geographical and immunoinformatic information eases the surveillance of variants potentially affecting the global population, as well as minority subpopulations.

Evaluation of different types of milk proteins-derived epitopes using in-silico tools: a primarily study to propose a new definition for bioactive peptides

Bioactive peptides are digestion-resistant and absorbable peptides released from dietary parent proteins. Dietary epitopes exert their effects on the body without absorption and release from parent protein. In this study, the epitope content of milk proteins was discovered, and a new definition for BPs is provided alongside the classic definition. In this study, LBtope, ABCpred, and SVMTriP servers were used to find Linear B cell epitopes. Besides, to predict T cell epitopes, the major histocompatibility complex I (MHC-I) and MHC-II alleles that were more abundant among Iranian people were first found from the Allele Frequency Net Database (AFND). Consequently, the IEDB, RANKPEP, SYFPEITHI, EpiJen, and EpiTOP3 servers were used for MHC binding epitopes. In the current study, MHC-II, MHC-I, and B-cell epitopes of milk proteins were discovered. The most important B-cell epitopes discovered by LBtope, ABCpred, and SVMtrip databases for αS1-casein included APSFSDIPNPIGSEN (176-190), AESISSSEEIVPNSVE (62-77), and VFGKEKVNELSKDIGS (31-46). The high rank of αS1-casein derived from MHC-II epitopes and discovered from the SYFPEITHI database included KEKVNELSKDIGSES (34-48), RFFVAPFPEVFGKEK (22-36), and PELFRQFYQLDAYPS (147-161). The epitopes of dietary proteins and endogenous proteins could be considered as BPs. Epitopes exert their biological effects without absorption and release from parent proteins.

Next-generation sequencing and genotype association studies reveal the association of HLA-DRB3*02:02 with delayed hypersensitivity to penicillins.

Nonimmediate (delayed)-allergic reactions to penicillins are common and some of them can be life-threatening. The genetic factors influencing these reactions are unknown/poorly known/poorly understood. We assessed the genetic predictors of a delayed penicillin allergy that cover the HLA loci. Using next-generation sequencing (NGS), we genotyped the MHC region in 24 patients with delayed hypersensitivity compared with 20 patients with documented immediate hypersensitivity to penicillins recruited in Italy. Subsequently, we analyzed in silico Illumina Immunochip genotyping data that covered the HLA loci in 98 Spanish patients with delayed hypersensitivity and 315 with immediate hypersensitivity compared to 1,308 controls. The two alleles DRB3*02:02:01:02 and DRB3*02:02:01:01 were reported in twenty cases with delayed reactions (83%) and ten cases with immediate reactions (50%), but not in the Allele Frequency Net Database. Bearing at least one of the two alleles increased the risk of delayed reactions compared to immediate reactions, with an OR of 8.88 (95% CI, 3.37-23.32; p<.0001). The haplotype (ACAA) from rs9268835, rs6923504, rs6903608, and rs9268838genetic variants of the HLA-DRB3genomic region was significantly associated with an increased risk of delayed hypersensitivity to penicillins (OR, 1.7; 95% CI: 1.06-1.92; p=.001), but not immediate hypersensitivity. We showed that the HLA-DRB3locus is strongly associated with an increased risk of delayed penicillin hypersensitivity, at least in Southwestern Europe. The determination of HLA-DRB3*02:02 alleles in the risk management of severe delayed hypersensitivity to penicillins should be evaluated further in larger population samples of different origins.

899 Population coverage of HLA-A*02:01, *02:05, *02:06 across selected cancer types in the United States

BackgroundGSK is investigating an autologous TCR T-cell therapy for solid tumors that recognizes the cancer testis antigen, NY-ESO-1, presented on the cancer cell surface by specific HLA-A*02 sub-types. The aim of this study was to estimate the number of patients in the US in 2020 with HLA-A*02 genotype subtypes HLA-A*02:01, 02:05, 02:06 across selected cancer types (invasive lung, ovarian, gastric, esophageal, invasive and in-situ bladder and multiple myeloma), accounting for racial variation.MethodsThis study was carried out in three parts utilizing three national datasets.1. The prevalence of each cancer type was estimated by race utilizing prevalence rates from US Surveillance, Epidemiology, and End Results (SEER) 1975–2018 data.1 2. The US population coverage for the specific HLA-A*02 subtype (%) by race in 2020, was estimated utilizing Hardy Weinberg Principles and allele frequencies extracted from the allele frequency net database (US National Marrow Donor Program (NMDP) population only).2 3. The estimated population coverage for the specific HLA-A*02 subtype expression (%) by cancer subtype, was calculated using US Census (2019) data.3 For the purpose of this analyses, single race population estimates were used. Race was categorized as ‘White’, ‘Black’, ‘Asian/Pacific Islander’, ‘Native American’ and ‘Other’. The Hispanic population was included as a proportion of each category, where appropriate. Limitations include the seven assumptions underlying Hardy-Weinberg equilibrium, which were met, and the assumption that the NMDP, SEER and US Census data are reflective of the US population. Predictive and prognostic clinical characteristics including histological subtypes were not accounted for in this analysis.ResultsAcross selected cancer types, the most prevalent race category was White, reflecting the racial distribution of the US (table 1). Of these cancer types, multiple myeloma and invasive gastric cancer are represented by the lowest proportion of White patients and the highest proportion of Black patients. Results of the HLA sub-type distribution by race are presented in the table below. The overall proportion of patients who are HLA-A*02:01, *02:05 or *02:06 positive is estimated to be between 41.7% (multiple myeloma) and 45.8% (invasive and in-situ bladder) in the US accounting for the racial variations in each cancer type of interest.Abstract 899 Table 1Proportion of patients who are HLA-A*02:01, *02:05, or *02:06 positive by race and cancer subtypeConclusionsThe proportion of patients with specific HLA-A*02 subtypes is similar across selected cancers, accounting for racial variation in the US. Racial variation by cancer type is an important consideration when estimating the size of eligible populations for T-cell therapies requiring specific HLA-A*02 histocompatibility.AcknowledgementsFundingGlaxoSmithKlineReferencesHowlader N, Noone AM, Krapcho M, Miller D, Brest A, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds). SEER Cancer Statistics Review, 1975–2018, National Cancer Institute. Bethesda, MD, [https://seer.cancer.gov/csr/1975_2018/], based on November 2020 SEER data submission, posted to the SEER web site, April 2021 (Accessed July 2021).Gonzalez-Galarza FF, McCabe A, Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, Del Cid-Pavon GM, Ramsbottom K, Ghattaoraya GS, Alfirevic A, Middleton D, Jones AR. Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools. Nucleic Acids Res 2020;48:D783–8.U S Census Bureau (2011). ACS demographic and housing estimates. [https://data.census.gov/cedsci/table?q=United%20States&amp;g=0100000US&amp;tid=ACSDP1Y2017.DP05&amp;vintage=2017&amp;layer=state&amp;cid=DP05_0001E] (Accessed July 2021).

LATIN AMERICAN GENOMICS CONSORTIUM: AN INTRODUCTION

A total of 125 Costa Ricans of Amerindian descent were genotyped at high-resolution for the human leukocyte antigen loci HLA-A, -B, -C, and -DRB1 using sequence-based typing methods. The respective allele and extended haplotype frequencies, as well as Hardy-Weinberg proportions were calculated. The most frequent extended haplotype identified was A*24:02:01-B*40:02:01-C*03:05-DRB1*04:07:01G, with an estimated frequency of 8.26%. A deviation from Hardy-Weinberg Equilibrium was detected at the DRB1 locus (p = 0.099). The HLA genotypic data of the population sample reported here are available publicly in the Allele Frequencies Net Database under the population name “Costa Rica Amerindians” and the identifier AFN3608.

Abstract 3020: Human leukocyte antigen (HLA) typing of a broad panel of cancer patient-derived xenograft (PDX) models for immune therapies

Abstract Background In immuno-oncology research, an appropriate microenvironment for both human tumor cells and human immune cells is an important but challenging factor for successful development of relevant preclinical models. Humanized patient-derived xenograft (PDX) models can support establishment of such an environment based on matching human leukocyte antigen (HLA) profiles of PDX and compatible human immune cell populations. In this study, we determined the individual HLA types of a broad panel of 291 established PDX models from 18 different tumor entities. Furthermore, we performed comprehensive HLA matching analyses of all PDX models and 13 peripheral blood mononuclear cell (PBMC) donors to enable personalized studies with HLA-matched PDX. Methods The HLA profile of each PDX was determined comprising HLA class I, II and non-class types in 4-digit resolution. Matching analyses were performed according to donor-recipient HLA matching criteria recommended by the Blood and Marrow Transplant Clinical Trials Network (BMT CTN). For comparative HLA profile analyses, allele frequencies of 8862 German stem cell donors provided by The Allele Frequency Net Database were downloaded. Results The individual HLA profiles of all PDX models were generated comprising HLA-A, -B and -C (class I), HLA-DQA1, -DQB1, -DRB1, -DPA1 and -DPB1 (class II) as well as HLA-H (non-class) types. Comparative analyses of HLA profiles revealed that obtained frequencies of PDX HLA alleles are comparable with frequencies of a representative population of 8862 German stem cell donors. HLA profile matching analyses performed for all PDX models and PBMC donors resulted in 15 matches regarding PDX from head and neck, lung, mammary and pancreatic carcinoma as well as from endometrial cancer, glioma, lymphoma, melanoma and sarcoma. Dependence of immune therapy efficacy on matched HLA profiles was shown exemplarily for a head and neck squamous cell cancer (HNSCC) PDX. The HNSCC PDX was humanized with PBMC from 5 donors representing different degrees of HLA matching (33 - 100 %). Treatment with the checkpoint inhibitor Nivolumab caused a more powerful tumor growth inhibition in matched HLA profiles compared to non-matched profiles. This indicated a relation between antitumoral immune therapy effect and HLA matching in preclinical models. Conclusions We generated a comprehensive HLA profile portfolio containing information of a broad panel of PDX models. Matched HLA profiles of PDX models and PBMC donors enable personalized, preclinical immune-oncology studies to support the development of novel therapeutic strategies. Citation Format: Theresia Conrad, Annika Wulf-Goldenberg, Maria Stecklum, Michael Becker, Konrad Klinghammer, Jens Hoffmann. Human leukocyte antigen (HLA) typing of a broad panel of cancer patient-derived xenograft (PDX) models for immune therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3020.

HLA-A, -C, -B, -DRB1, -DQA1, and -DQB1 Allele and Haplotype Repertoires in the Albanian Population from Kosovo

ABSTRACT To give new insight into the huge polymorphism of HLA system and supplement the existing data, an analysis of HLA alleles and HLA-A~C~B~DRB1~DQA1~DQB1 haplotype distribution in 124 Albanian individuals from Kosovo was performed. All samples were HLA-typed applying the polymerase chain reaction-sequence specific oligonucleotide probing (PCR-SSOP) method and all ambiguous HLA typing results were additionally confirmed by the standard PCR-Sequence Specific Primers (PCR-SSP) high-resolution protocol. Twenty-two HLA-A, 21 HLA-C, 37 HLA-B, 27 HLA-DRB1, 11 HLA-DQA1 and 14 HLA-DQB1 allele groups were detected. Sixteen out of 172 different six-locus estimated haplotypes were found at a frequency higher than 1.00% with a cumulative frequency of 28.82%. The most prevalent haplotype was found to be HLA-A*02:01~C*07:01~B*18:01~DRB1*11:04~DQA1*05:05~DQB1*03:0(5.2%).A total of 13 haplotypes were observed with higher frequency than in populations reported in HaploStats and The Allele Frequency Net Database. The proposed origin of the most frequent haplotypes reflects a basic Euro-Mediterranean background of Albanians in Kosovo. This is the first report of high-resolution HLA-A~C~B~DRB1~DQA1~DQB1 haplotype distribution among the Albanian population from Kosovo, which provides valuable anthropological data and confirms population-specific characteristics.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach.

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

Predictive immunogenetic markers in COVID-19

Immunorelevant genes are among the most probable modulators of coronavirus disease 2019 (COVID-19) progression and prognosis. However, in the few months of the pandemic, data generated on host genetics has been scarce. The present study retrieved data sets of HLA-B alleles, KIR genes and functional single nucleotide polymorphisms (SNPs) in cytokines related to COVID-19 cytokine storm from two publicly available databases: Allele Frequency Net Database and Ensembl, and correlated these frequency data with Case Fatality Rate (CFR) and Daily Death Rates (DDR) across countries. Correlations of eight HLA-B alleles and polymorphisms in three cytokine genes (IL6, IL10, and IL12B) were observed and were mainly associated with DDR. Additionally, HLA-B correlations suggest that differences in allele affinities to SARS-CoV-2 peptides are also associated with DDR. These results may provide rationale for future host genetic marker surveys on COVID-19.

NGS-based typings for 7 HLA loci in three populations from Rio de Janeiro, RJ, Brazil

We investigated HLA class I (HLA-A, -B, and -C) and class II (HLA-DRB1, -DQB1, -DPA1, and -DPB1) alleles by NGS-based typing among 759 Brazilian individuals from three populations in the Rio de Janeiro city based on their self-declared skin color (Caucasian, N = 521, AFND-ID: 3730; Parda, N = 170, AFND-ID: 3728; Black, N = 68, AFND-ID: 3727) to calculate allelic and haplotypic frequencies, plus linkage disequilibrium. Only HLA-DRB1 locus deviated from Hardy-Weinberg equilibrium (in Caucasian and Black populations). The three populations shared the most frequent allele on HLA-A, -C, -DRB1, -DPA1, and -DPB1. Genotype and frequency data are available in the Allele Frequencies Net Database.

NGS-based typings for 7 HLA loci in two populations from Barra Mansa, RJ, Brazil

We investigated HLA class I (HLA-A, -B, and -C) and class II (HLA-DRB1, -DQB1, -DPA1, and -DPB1) alleles by NGS-based typing among 478 Brazilian individuals from two populations in the Barra Mansa city based on their self-declared skin color (Caucasian, N = 405, AFND-ID: 3729; Black, N = 73, AFND-ID: 3731) to calculate allelic and haplotypic frequencies, plus linkage disequilibrium. No locus deviated from Hardy-Weinberg equilibrium. Both populations shared the most frequent allele on HLA-A, -C, -DPA1, and -DPB1. Genotype and frequency data are available in the Allele Frequencies Net Database.

Population Difference in Allele Frequency of HLA-C*05 and Its Correlation with COVID-19 Mortality.

Background: coronavirus disease 2019 (COVID-19) causes severe illness including cytokine storms, but mortality among countries differs largely. In the present study, we investigated the association between human leukocyte antigen (HLA) class I, which plays a major role in susceptibility to viral infections, and the mortality of COVID-19. Methods: data of allele frequencies of HLA-A, -B and -C and COVID-19 mortality were obtained for 74 countries from the Allele Frequency Net Database and worldometer.info. Association between allele frequency of each HLA and mortality was assessed by linear regression followed by multivariable regression. Subsequently, association of HLA-C*05 to its receptor KIR2DS4fl, expressed on natural killer (NK) cells, and differential mortality to historic pandemics were analyzed. Results: HLA-A*01, -B*07, -B*08, -B*44 and -C*05 were significantly associated with the risk of deaths (adjusted p = 0.040, 0.00081, 0.047, 0.0022, 0.00032, respectively), but only HLA-C*05 remained statistically significant (p = 0.000027) after multivariable regression. A 1% increase in the allele frequency of HLA-C*05 was associated with an increase of 44 deaths/million. Countries with different mortality could be categorized by the distribution of HLA-C*05 and its receptor KIR2DS4fl, which in combination cause NK cell-induced hyperactive immune response. Countries with similar ethnic and/or geographic background responded in a similar pattern to each pandemic. Conclusions: we demonstrated that allele frequency of HLA-C*05 and the distribution pattern with its receptor KIR2DS4fl strongly correlated with COVID-19 mortality. Host genetic variance of innate immunity may contribute to the difference in mortality among various countries and further investigation using patient samples is warranted.

High resolution allele genotyping and haplotype frequencies for NGS based HLA 11 loci of 5266 Hong Kong Chinese bone marrow donors

Next-generation sequencing (NGS) at the HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 loci was performed on 5,266 southern Chinese unrelated donors of the Hong Kong Bone Marrow Donor Registry. High-resolution HLA genotypes defined by full sequencing of class I loci and extended coverage of class II loci were attained to determine allele frequencies and estimate haplotype frequencies. This study provides allele and haplotype frequencies on 11 loci estimated for the first time in the Hong Kong Chinese population. These results describe extended haplotypes including the less frequently typed HLA-DPA1, -DPB1 and -DQA1 loci and distinctive haplotype associations. The present data are timely in that they allow the permissible matching in HLA-DPB1 for Chinese patients awaiting haematopoietic stem cell transplantation upon applying the latest requirement of NMDP matching guidelines. Overall, these results provide a useful reference source for population genetics studies, HLA-disease association studies and for improving donor recruitment and selection strategies of bone marrow registries. The allele and haplotype data are available in the Allele Frequencies Net Database under the population name ‘‘Hong Kong Chinese HKBMDR, HLA 11 loci’’ and the identifier (AFND3724) [1].

Identification of Novel Candidate Epitopes on SARS-CoV-2 Proteins for South America: A Review of HLA Frequencies by Country.

Coronavirus disease (COVID-19), caused by the virus SARS-CoV-2, is already responsible for more than 4.3 million confirmed cases and 295,000 deaths worldwide as of May 15, 2020. Ongoing efforts to control the pandemic include the development of peptide-based vaccines and diagnostic tests. In these approaches, HLA allelic diversity plays a crucial role. Despite its importance, current knowledge of HLA allele frequencies in South America is very limited. In this study, we have performed a literature review of datasets reporting HLA frequencies of South American populations, available in scientific literature and/or in the Allele Frequency Net Database. This allowed us to enrich the current scenario with more than 12.8 million data points. As a result, we are presenting updated HLA allelic frequencies based on country, including 91 alleles that were previously thought to have frequencies either under 5% or of an unknown value. Using alleles with an updated frequency of at least ≥5% in any South American country, we predicted epitopes in SARS-CoV-2 proteins using NetMHCpan (I and II) and MHC flurry. Then, the best predicted epitopes (class-I and -II) were selected based on their binding to South American alleles (Coverage Score). Class II predicted epitopes were also filtered based on their three-dimensional exposure. We obtained 14 class-I and four class-II candidate epitopes with experimental evidence (reported in the Immune Epitope Database and Analysis Resource), having good coverage scores for South America. Additionally, we are presenting 13 HLA-I and 30 HLA-II novel candidate epitopes without experimental evidence, including 16 class-II candidates in highly exposed conserved areas of the NTD and RBD regions of the Spike protein. These novel candidates have even better coverage scores for South America than those with experimental evidence. Finally, we show that recent similar studies presenting candidate epitopes also predicted some of our candidates but discarded them in the selection process, resulting in candidates with suboptimal coverage for South America. In conclusion, the candidate epitopes presented provide valuable information for the development of epitope-based strategies against SARS-CoV-2, such as peptide vaccines and diagnostic tests. Additionally, the updated HLA allelic frequencies provide a better representation of South America and may impact different immunogenetic studies.