HLA binding-groove motifs are associated with myocarditis induction after Pfizer-BioNTech BNT162b2 vaccination

We found a higher incidence of myocarditis in young males who had received Pfizer-BioNTech BNT162b2 vaccinations as compared with historical controls and unvaccinated individuals. The analyses focused on risk following the first and second vaccine in adults and adolescents, as well as risk in adults following the third (booster) vaccine. Males, mainly aged 12-30 years, were found to be at higher risk. However, the question remains what causes lead one specific young male, but not another, to develop post-vaccination myocarditis. The HLA molecule is known to play an important role in infectious and auto-inflammatory diseases. We hypothesized that differences in HLA alleles could lead to either protection or susceptibility to vaccination-induced myocarditis. On this basis, HLA typing was performed using next-generation sequencing technology for the HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 loci, in 21 wellcharacterized patients who developed myocarditis after the second Pfizer BNT162b2 vaccination. The HLA genotypes were compared with high-resolution HLA data of 272 healthy controls from the Hadassah Bone Marrow registry samples, who are representative of HLA frequencies in the Israeli population. Our findings demonstrated that in HLA class II, DRB1*14:01 (19.04% vs. 5.3%, Pcorr = 0.028, OR = 4.17), HLA-DQB1*05:03 (19.04% vs. 6.06%, Pcorr = 0.034, OR = 3.64) and DRB1*15:03 (7.14% vs. 0.0%, Pcorr = 0.003, OR = 41.76) were significantly associated with disease susceptibility. We further discovered susceptibility motifs in the HLA-DR peptidebinding grooves: His60 (Pcorr0.01, OR = 3.52) and Arg70 (Pcorr = 0.0047, OR = 3.43). Our findings suggest that immunogenetic fingerprints in HLA peptide-binding grooves may have changed the binding affinity of different peptides derived from the Pfizer-BioNTech BNT162b2 vaccination, and induced myocarditis.

Impact of SARS-CoV-2 on HLA serological phenotyping level in southern Portuguese solid organ donors

HLA molecules play a key role in transplant medicine and disease pathogenesis, being a useful tool in predicting disease progression and identifying potential solid organ donors (SOD). The Coronavirus disease 2019 (SARS-CoV-2) pandemic had a huge worldwide impact, which strongly affected the activity of different transplant programs. So far, it has been shown that HLA type may be a crucial differentiator between individuals who have varying occurrence, morbidity, and mortality response to SARS-CoV-2. In this work, we investigated if differences in the frequency of SOD HLA alleles, were impacted during SARS-CoV-2 pandemic. We performed a retrospective file audit of all HLA-typings done in 2 subsets of SOD pre-pandemic period (ppp) (n = 379) and pandemic period (pp) (n = 351), collected in equivalent timeframes. We discuss data for the major HLA-A, HLA-B, HLA-C, and HLA-DRB1 allele groups at serological phenotyping level. Overall, there was a 7% SOD decrease in the pp. Considering both periods, the most common allele groups were HLA-A2, HLA-B35, HLA-Cw7, HLA-DR7 and HLA-DQ2. For the ppp group, the most common alleles were HLA-A2, HLA-B35, HLA-Cw7, HLADR13 and HLA-DQ2, while in the pp group the most common alleles were HLA-A2, HLA-B44, HLA-Cw7, HLA-DR4 and HLA-DQ2. When comparing both populations at the serological phenotyping level an increased in relative frequency was found for 10, 12, 8, 8 and 2, and a decreased was found for 10, 24, 8, 6 and 5 for HLA-A, -B, -C, -DR and -DQ, respectively. The significant variation within the HLA frequencies between the different pre-pandemic and pandemic groups highlights the value of population-specific HLA-typing. Furthermore, the identification of different frequencies among both populations will impact in patients HLA compatibility with SOD thus impacting their transplantability.

KIR2DL2/C1: A potential predictive immunogenetic marker to COVID-19 severity in Spanish patients

COVID-19 has aspects on its pathogenesis that still need elucidating and an analysis of clinical and immunogenetic factors in each cohort of patients is paramount to understanding how genetic variability can explain the multiple clinical spectra seen in patients infected with SARS-CoV-2. The aim of this study was to correlate the KIR polymorphism/HLA class I ligand interactions from patients and healthy subjects with either the susceptibility or severity to COVID-19. Genotyping of HLA-A, -B, -C and KIR genes were carried out from 459 symptomatic as well as 667 non-infected Spanish Caucasian individuals using Lifecodes HLA-SSO and KIR-SSO kits (ImmucorTM, USA) and analyzed in the Luminex in this uni-centre case-control study performed at the University Hospital of Salamanca, Spain. Comparative KIR gene analysis showed that KIR2DS4 was significantly more representative in healthy versus infected individuals. When comparing subgroups of infected patients, KIR2DS3 had a higher frequency in those who progressed to a more severity disease and yet with higher mortality rate. Three functional combinations were significant on univariate analysis: KIR2DL2/C1, KIR2DS2/C1, and KIR2DS3/C1. However, in the multivariate analysis, only the KIR2DL2/C1 interaction remained significant (OR = 15.2 (95% CI 1.5-147), p = 0.0189). Compared with the solo-clinical characteristics predictive model, that included well-known comorbidity variables such as hypertension, age, sex, diabetes, C-reactive protein, dyslipidemia, smoking, ferritin, and fibrinogen, the clinical-and-KIR-based model showed a better ability to discriminate between severe and nonsevere patients with higher sensitivity and specificity. Our results support a fundamental role of KIR/ligand interaction in the clinical course of COVID-19. Since the KIR2DL2 gene has a high frequency in Spain (60%), the analysis of the KIR2DL2/C1 in symptomatic patients who require hospitalization could be helpful to better determine their prognosis.

Role of HLA polymorphism in COVID-19 progression in the Bulgarian population

The SARS-CoV-2 outbreak has impacted different socioeconomic aspects of our societies and represents a global health problem. The different rates of infection are heavily influenced by host genetic factors such as the variability in the HLA region. The aim of our study was to evaluate the role of specific HLA alleles in the Bulgarian population that contribute to COVID-19 progression. 76 Bulgarian patients (median age 59.4;range 25-84) with COVID-19, separated into 3 groups based on the severity of the infection, were included in the study. All patients were typed at allele level for HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1. Data from a representative Bulgarian population control group of young individuals (n = 540;median age 28,5;range 18-38) with unknown infectious status was used for comparison. Among the patient group, HLA-A*23:01 (OR = 3.16;p = 0.016), and DQB1*05:03 (OR = 3.1;p = 0.0009) showed positive association with moderate course of COVID-19, whereas DRB1*07:01 (OR = 2.54;p = 0.018) was associated with more severe disease. We found that A*01:01 (OR = 1.82;p = 0.018), B*35:03 (OR = 2.22;p = 0.011), B*40:06 (OR = 23.59;p = 0.0001), and DRB1*14:01 (OR = 3.37;p = 0.015) strongly correlate with the disease progression and could be considered as high-risk alleles. Furthermore, A*02:01 (OR = 0.4;p = 0.02), and DQB1*03:01 (OR = 0.47;p = 0.025) were predominantly found in asymptomatic patients and controls and probably exert a protective effect. Population-based and intra-individual variability of the HLA complex could partially explain the different courses of COVID-19. Despite some limitations, our preliminary data shows that some HLA alleles may be associated with a more severe course of the SARS-Cov infection, while others could possibly be considered protective. This work was supported by grant KP06DK1/13, 2021, Ministry of Education and Science, Bulgaria.

Immunogenetics and SARS-CoV-2 infection

Since the beginning of the SARS-Cov-2 pandemic, in 2020, numerous data with respect to the influence of immunogenetics to the predisposition and infection severity have been reported worldwide. It is well accepted that immunogenetics plays a pivotal role in infection and vaccination, as well as vaccination failures and/or breakthrough. Factors of the major histocompatibility complex and the common ABO blood group system have been so far discussed. Here, we describe the association of HLA-A, -B, -C, -DRB1, -DRB345, -DQA1, -DQB1, -DPA1, -DPB1, and HLA-E, -F, -G, -H on the results of molecular detection of COVID-19 or in some cases on antibody detection upon first testing. Furthermore, we defined molecularly 22 blood group systems comprising 26 genes and 5 platelet antigen genes. We observed 37% COVID-19 PCR negative individuals and 63% positive. Within the negative subjects HLA-B*57:01, HLA-B*55:01, DRB1*13:01, DRB1*01:01, were enriched, and in the positive group homozygosity for DQA1/DQB1, DRB1*09:01 and DRB1*15:01. For HLA-DQA1 we observe an enrichment for DQA1*01:01, DQA1*02:01 and DQA1*01:03. For HLADQB1 we found HLA-DQB1*06:02 was enriched in the positive group while HLA-DQB1*05:01 and HLA-DQB1*06:03 in the negative group. We observed a significant enrichment of homozygosity for DQA1/DQB1 in the positive group. The homozygous platelet antigen HPA-1a was significantly enriched in the negative group, contrasting the result of HPA-1ab that was enriched in the COVID-19 infected group. Despite limitations of our study, the data presented here show clearly that COVID-19 infection and all the consequences of that are multifactorial and multigenetic. The virus is in a continuous mutation/selection process leading to escape possibilities. Therefore, associations are a momentum in science.

Impact of HLA diversity on humoral response to SARS-Cov-2 and HBV vaccines in liver transplant recipients

Organ transplant recipients show weaker immune responses to vaccines than immunocompetent individuals, which may be related to the repertoire of HLAbound vaccine antigens presented to T lymphocytes. The HLA evolutionary divergence (HED) metric, which quantifies pairwise allele divergence at each HLA locus, provides a primary measure of the breadth of the immunopeptidome. We recently showed that high class I HED of the donor is a strong and independent driver of allograft rejection in a large cohort of liver transplant recipients. Here, in the same cohort, we explored the relation between HED, the size of the predicted immunopeptidome derived from vaccine antigens, and the quality of vaccine responses. We analyzed humoral response to the SARS-CoV-2 BNT162b2 vaccine (n = 310 patients;undetectable anti-spike IgG titers considered as no response, <=250 BAU/mL as moderate and >250 BAU/mL as strong response) and Hepatitis B virus (HBV) vaccine (n = 424 patients;anti-HBs IgG <10 mIU/mL considered as no response, 10-100 mIU/mL as moderate and >=100 mIU/mL as strong response). HED at HLA-A, -B, -C, -DRB1, -DQA1 and -DQB1 loci were measured using the Grantham distance. NetMHCIIpan-4.0 was used to predict the binding to HLA-DQ molecules of all possible 15mer peptides derived from the Spike and HBS sequences. For each vaccine, HED at the DQB1 locus, but not at the other loci, was significantly higher in responders than in non-responders (p = 0.0003), independent of response-associated covariates (age, time since transplant, immunosuppression). Moreover, for both vaccines, there was a strong relationship between DQB1 HED, the diversity of the immunopeptidome and the quality of the vaccine response. In conclusion, DQB1 HED is a critical determinant of humoral response to vaccines in liver transplant recipients. This metric could guide the design of future vaccines as it predicts the magnitude of the repertoire of vaccine-derived peptides presented to CD4 helper T cells.

HLA Class I allele is associated with a lower risk to develop Post-COVID19 interstitial lung manifestations

Introduction: The HLA Class I genes codify crucial molecules in developing the immunological response against pathogenic agents such as SARS-CoV-2. We aimed to assess HLA-A alleles associated with COVID-19 subsequent pulmonary complications as interstitial lung manifestations (ILM). Material(s) and Method(s): 209 Mexican mestizo patients with a positive RT-PCR test for SARS-CoV-2 and confirmed clinical diagnosis of COVID-19 were included. The participants were monitored three months after the hospital discharge through tomography;They were divided into two groups, 1) patients who developed ILM post-COVID19 (n = 85) and 2) those patients without tomographic evidence of ILM (n = 124). The HLA-A locus was genotyped by endpoint PCR using Micro SSP Generic HLA Class I kits. The clinical and demographic variables were analyzed by SPSS software. The alleles and genotypes were analyzed by 2 x 2 contingency tables, the value of p was obtained by Yates' correction. Result(s): There is no significant difference in age, sex, BMI, hospitalization days, PAO2/FIO2, or invasive mechanical ventilation. The alleles HLA-A*02:01, *24:02, and *68:01 are the most frequent in both study groups, grouping more than 60% of the alleles identified. On the other hand, the frequency of the HLA-A*01:01 allele was decreased in the group with interstitial lung manifestations at 3 months of discharge, compared to the group without interstitial lung manifestations (p= 0.004, OR = 0.13, IC95% 0.03-0.58). There is no significant difference in the genotypic frequencies. Conclusion(s): Subjects carrying the HLA-A*01:01 allele have a lower risk of developing interstitial lung manifestations posterior from COVID-19.

Net treatment benefit of OSE2101 in HLA-A2+ non-small cell lung cancer (NSCLC) patients after failure to immune checkpoint inhibitors (IO) in phase III Atalante-1 randomized trial

Background: OSE2101 (Tedopi) is an anticancer vaccine that increased overall survival (OS) (HR 0.59, p=0.017) versus Standard of Care Chemotherapy in the population of interest (PoI N=118) of patients with IO secondary resistance after sequential CT-IO (ESMO 2021 #47LBA). The Net Treatment Benefit (NTB) is an original method combining efficacy and safety endpoints to test the overall improvement in health outcome between 2 treatments (Buyse M. Stat Med 2010). NTB was assessed in the overall population (N=219) from whom OS improvement of OSE2101 (HR 0.86, p=0.35) was lower than in PoI. Methods: NTB was tested by comparing prioritized outcomes using Generalized Paired Wise Comparisons (GPC). The prioritized outcomes were OS, then time to worsening ECOG (threshold=2 months) followed by severe adverse events, progression free survival (shorter vs. longer than 2 months) and Quality of Life (threshold=5 points on Global Health Status of EORTC-QLQC30). Analysis was stratified using the 3 strata of the study (histology, best response to 1rst line, line of prior IO) and enrollment time (before vs during COVID-19). Sensitivity analyses used no stratification, different thresholds of clinical relevance and PoI. Results: In the primary analysis (1088 pairs), NTB was 19% and reached statistical significance in favor of OSE2101 (p=0.035). In unstratified analysis (11120 pairs), NTB was 11% (p=0.188). In the PoI (388 pairs), NTB was 22% (p stratified=0.074) and 28% (p=0.014) in unstratified analysis (3040 pairs). Although the primary analysis was statistically positive, results were not consistent in some sensitivity analyses due to the limited sample size and the impact of stratification factors. Conclusions: An overall improvement in health outcome was observed with OSE2101 in the overall population of advanced NSCLC after IO failure with a NTB of 19% over SoC. In PoI with IO secondary resistance after CT-IO, the NTB was 22%. Post-hoc analyses are ongoing intended to explain the variability of NTB and will be detailed. Clinical trial identification: EudraCT: 2015-003183-36;NCT02654587. Editorial acknowledgement: We thank Pierre Attali (Medical Expert, MD) for his support in the writing of the . Legal entity responsible for the study: Ose Immunotherapeutics. Funding: Ose Immunotherapeutics. Disclosure: M.E. Buyse: Financial Interests, Personal, Officer, Chief Scientific Officer: IDDI;Financial Interests, Personal, Invited Speaker, Board Member: CluePoints;Financial Interests, Personal, Stocks/Shares: IDDI, CluePoints. F. Montestruc: Financial Interests, Personal, Member of the Board of Directors, CEO of the Company: eXYSTAT SAS;Financial Interests, Institutional, Other, Statistician Consultant: AbbVie, Biocodex, Geneuro, Gensight, Guerbet, Imcheck, Ose Immunotherapeutics, Pfizer, Takeda;Non-Financial Interests, Personal, Other, Statistician Consultant and Training: Institut Pasteur. J. Chiem: Financial Interests, Personal, Full or part-time Employment: IDDI. V. Deltuvaite-Thomas: Financial Interests, Personal, Full or part-time Employment: IDDI. S. Salvaggio: Financial Interests, Personal, Full or part-time Employment, Working as a statistician: International Drug Development Institute. M.R. Garcia Campelo: Financial Interests, Personal, Advisory Role: Roche/Genentech, MSD Oncology, AstraZeneca, Bristol-Myers Squibb, Pfizer, Novartis, Takeda, Boehringer Ingelheim, Janssen Oncology;Financial Interests, Personal, Speaker’s Bureau: Roche, AstraZeneca, Bristol-Myers Squibb, Pfizer, Novartis, Takeda, Boehringer Ingelheim, MSD Oncology, Sanofi/Aventis, Janssen Oncology, Amgen;Financial Interests, Personal, Other, Travel, Accommodations, Expenses: Roche/Genentech, MSD Oncology, Pfizer. F. Cappuzzo: Financial Interests, Personal, Invited Speaker: Roche, AstraZeneca, BMS, Pfizer, Takeda, Lilly, Bayer, Amgen, Sanofi, PharmaMar, Mirati, Novocure, OSE, and MSD;Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, BMS, Pfizer, Takeda, Lilly, Bayer, Amgen, Sanofi, Mirati, PharmaMar, Novocure, OSE, Galecto and MS . S. Viteri Ramirez: Financial Interests, Personal, Advisory Board: Merck Healthcare KGAA Germany, Bristol Myers Squibb S.A. U, Puma Biotechnology;Financial Interests, Personal, Invited Speaker: Takeda Farmaceutica España SA, MSD de España SA, AstraZeneca Farmaceutica Spain, Roche Farma SA;Financial Interests, Personal, Expert Testimony: Reddy Pharma Iberia SAU. W. Schuette: Financial Interests, Personal, Other, Honoraria: Roche, MSD, Novartis;Financial Interests, Personal, Advisory Role: Roche, MSD, Novartis. A. Zer: Financial Interests, Personal, Invited Speaker: Roche, BMS, MSD, Takeda, Pfizer, Novartis;Financial Interests, Personal, Advisory Board: AstraZeneca, Steba, Oncohost;Financial Interests, Personal, Stocks/Shares: Nixio;Financial Interests, Institutional, Research Grant: BMS. S. Comis: Financial Interests, Personal, Full or part-time Employment: Ose Immunotherapeutics. B. Vasseur: Financial Interests, Personal, Full or part-time Employment: Ose Immunotherapeutics;Financial Interests, Personal, Other, Actions: Ose Immunotherapeutics. R. Dziadziuszko: Financial Interests, Personal, Advisory Board: Roche, AstraZeneca, Seattle Genetics, Pfizer, Takeda, Regeneron, MSD, Bristol Myers-Squibb, PharmaMar, Bayer;Financial Interests, Personal, Invited Speaker: Boehringer Ingelheim, Foundation Medicine;Financial Interests, Personal, Expert Testimony: Novartis;Financial Interests, Personal and Institutional, Invited Speaker: Roche, AstraZeneca, MSD, Amgen, Celon Pharma, Pfizer, Novartis, Brsitol Myers-Squibb, Eli Lilly, Loxo;Financial Interests, Invited Speaker: BeiGene, Ardigen, Ose Immunotherapeutics;Financial Interests, Personal and Institutional, Other, Subinvestigator and ad hoc Consultant: PDC* line Pharma;Non-Financial Interests, Institutional, Product Samples: Novartis, Pfizer, AstraZeneca, Roche;Other, Travel: Roche, Bristol Myers-Squibb, AstraZeneca. G. Giaccone: Financial Interests, Personal, Advisory Board: Novartis;Financial Interests, Institutional, Research Grant: Karyopharm. B. Besse: Financial Interests, Institutional, Funding: 4D Pharma, AbbVie, Amgen, Aptitude Health, AstraZeneca, BeiGene, Blueprint Medicines, Boehringer Ingelheim, Celgene, Cergentis, Cristal Therapeutics, Daiichi Sankyo, Eli Lilly, GSK, Janssen, Onxeo, Ose Immunotherapeutics, Pfizer, Roche-Genentech, Sanofi, Takeda, Tolero Pharmaceuticals;Financial Interests, Institutional, Research Grant: Chugai Pharmaceutical, EISAI, Genzyme Corporation, Inivata, Ipsen, Turning Point Therapeutics. E. Felip: Financial Interests, Personal, Advisory Board: Amgen, AstraZeneca, Bayer, BeiGene, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Glaxo Smith Kline, Janssen, Medical Trends, Merck Sharp & Dohme, Pfizer, Puma, Sanofi, Takeda, Merck Serono, Peptomyc, Regeneron, Syneos Health, F. Hoffmann-La Roche;Financial Interests, Personal, Invited Speaker: AstraZeneca, Bristol Myers Squibb, Eli Lilly, Medscape, Merck Sharp & Dome, Peervoice, Pfizer, Springer, Touch Medical, Amgen, F. Hoffmann-La Roche, Janssen, Medical Trends, Merck Serono;Financial Interests, Personal, Invited Speaker, Independent member: Grifols;Financial Interests, Institutional, Invited Speaker, Clinical Trial: F. Hoffmann-La Roche Ltd, Merck Sharp & Dohme Corp, AstraZeneca AB, Daiichi Sankyo Inc, Exelixis Inc, Merck KGAA, Janssen Cilag International NV, GlaxoSmithKline Research & Development Limited, AbbVie Deutschland GmbH & Co KG, Novartis Farmaceutica SA, Bayer Consumer Care AG, Takeda Pharmaceuticals International, Boehringer Ingelheim International GmbH, Pfizer S.L.U., Amgen Inc, Bristol-Myers Squibb International Corporation (BMS), Mirati Therapeutics Inc;Non-Financial Interests, Leadership Role, President Elect (2021-2023): SEOM (Sociedad Espanola de Oncologia Medica);Non-Financial Interests, Member, Member of ESMO Nominating Committee and Compliance Committee: ESMO;Non-Financial Interests, Leadership Role, Member of Board of Directors and the Executive Committee (2017-Sept 2021): IASLC (International Association for the Study of Lung Cancer);Non-Fina cial Interests, Member of Scientific Committee: ETOP (European Thoracic Oncology Platform). All other authors have declared no conflicts of interest.

SARS-CoV-2 mRNA vaccine generates a CD8 T cell memory response in patients with haematological malignancies

Patients with haematological malignancies are prioritized for COVID-19 vaccine due to their high risk for SARS-CoV-2 infection related disease severity and mortality. Immune defects associated with malignancy and their treatment could influence vaccine driven immune response in these cancer patients. Thus, to understand T cell immunity, its long-term persistence, and correlation with antibody response, we evaluated the BNT162b2 SARS-CoV-2 mRNA vaccine-specific immune response in chronic lymphocytic leukaemia (CLL) and myeloid dysplastic syndrome (MDS) patients. Longitudinal analysis of CD8+ T cells using DNA-barcoded peptide-MHC multimers covering the full SARS-CoV-2 spike-protein showed vaccine-specific T cell activation and persistence of memory T cells up to 6 months post-vaccination. Surprisingly, a higher frequency of vaccine-induced antigen-specific CD8+ T cell was observed in the patient group compared to the healthy donor group. Furthermore, and importantly, immunization with the second booster dose significantly increased the frequency of antigen-specific CD8+ T cells as well as the total number of T cell specificities. Altogether, 23 immunogenic epitopes were identified and a strong immunodominance was observed for the two of the spike-specific T cell epitopes restricted to HLA-A24 (NYNYLYRLF) and HLA-A2 (YLQPRTFLL) with a prevalence of 100% and 80% respectively. In summary, we mapped the vaccine-induced antigen-specific CD8+ T cells and showed a booster-specific activation and enrichment of memory T cells that could be crucial for long-term disease protection for this patient group.

Human leukocyte antigen in COVID-19, a forgott en immune recognition mechanism: a scoping review

introduction. hla alleles play a fundamental role in the development of the immune response against viral infections. objective. Gather the information available on the association of different hla alleles with increased protection or susceptibility;furthermore, the impact on complications associated with sars-cov-2 infection. methodology. An information search was carried out in the Scopus, PubMed/Medline, lilacs and Academic Google databases that answered the research question: What is the association between hla and sars-cov-2 infection and the severity of the illness? Records of clinical trials from the databases of the who International Clinical Trials Platform were included. results. It was found that the hla-a* 25: 01, hla-b* 46: 01 and hla-c* 01: 02 alleles were associated with greater susceptibility to infection, while the hla-a* 02: 01 alleles, hla-a* 24: 02 and hla-b*27: 07 were associated with greater severity of the disease and the alleles hla-a* 02: 02, hla-b* 15: 03 and hla-c* 12: 03 as protective factor in covid-19. conclusions. The association between susceptibility, protection and severity with the different types of hla are mainly reported in silico analysis, and its precision is limited, requiring support based on in vitro and in vivo experimental studies and clinical trials in different populations. A greater focus is needed on the affinity of the various hla alleles by the sars-cov-2 proteome to elucidate the immunopathogenesis of the disease.

HLA typing for post-transfused patient: comparison between blood and buccal swab sample

Background: The polymorphic Human Leukocyte Antigens (HLA) play an important role in determining the best matched donor in a haematopoietic stem cell transplant (HSCT). Hence, accurate HLA typing results are crucial to determine the successfulness of a transplant. Most of the patients of hematologic diseases will receive blood transfusion regularly. There is a potential discrepancy result or ambiguous results when a patient already received non-leukoreduced blood component prior to blood sampling for HLA typing. Aims: To determine differences between the HLA typing result from the DNA extracted from blood sample and buccal swab sample. Methods: Blood sample and buccal swab sample were collected from a total of 66 patients with different hematologic diseases and plan to go for haematopoietic stem cell transplant. These patients received at least one pack of red blood cell or platelet between 1 and 14 days prior to blood sample taken. DNA was extracted from all 66 blood samples and 66 buccal swab samples. All samples were typed for six loci (HLA-A, HLA-B, HLA-C, HLA-DRB1, HLA-DQB1 and HLA-DPB1) with Next Generation Sequencing (NGS). NGS was performed in all those samples using the NGSgo-MX6-1 kit. After the library preparation by using NGSgo-LibrX ligation reagents and the NGSgoIndX adapter, it was sequenced in iSeq 100. The results were then analysed with NGSengine software. The results for blood sample and buccal swab sample were then compared. Results: Out of 66 patients, 25 patients received either red blood cell or platelet component prior to blood sample taken for HLA typing. One patient received red blood cell and plasma and the others received red blood cell and platelets before the sample was taken. There are no differences between the HLA typing result from the DNA extracted from blood sample or buccal swab sample for all the 66 patients. The sequencing noise level for both DNA extracted from blood and buccal swab was well separated from the alleles as we can see from the base variation plot. Summary/Conclusions: This preliminary study only focus on the adult patients with hematologic diseases (ALL, AML, CML, MDS, multiple myeloma, DLBCL, hemophagocytic lymphohistiocytosis, NKT Cell lymphoma and severe aplastic anaemia) for the past 1 year. From the findings of this study, blood samples from the patient who underwent blood transfusion can be used for HLA typing instead of using buccal swab samples. This will lower the risk of Covid-19 infection among the healthcare worker who performs the buccal swab sampling from the patient with unknown status of Covid-19 infectivity. However, an extensive study with the appropriate number of samples needed to confirm this finding in the near future.

HLA-association study with more than 16,000 participants shows no heterozygote advantage for COVID-19 and no protective HLAgenotypes

HLA molecules are key restrictive elements to present intracellular antigens for an effective T-cell response against SARS-CoV-2. HLA alleles vary with respect to their potential to present immunogenic viral epitopes and may therefore determine disease severity. Therefore, we set out to investigate the impact of individual HLA genotypes on the severity of SARS-CoV-2 infections. In August 2020 and July 2021, we performed cross-sectional studies among stem cell donors registered with DKMS in Germany. Volunteers registered for stem cell donation represent a comparable healthy subset of the working age population. Available genetic information was linked to self-reported COVID-19 outcome data. Multivariable regression models were fitted to determine the risk of contracting SARS-CoV-2, severe respiratory tract infection and respiratory hospitalization. More than 200,000 registered donors provided informed consent and participated in the study. Their age ranged from 18 to 61 years. Altogether 16,121 participants donors reported a history of COVID-19. Asymptomatic courses were reported by 1428 participants, mild/moderate symptoms by 10,353 participants, severe respiratory infections by 3913 not requiring hospitalization and respiratory hospitalizations by 427 patients. Notably, we did not observe a heterozygote advantage. The risk for severe infections was not statistically different among individuals with or without homozygosity at HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1. Of 84 HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 alleles which were prevalent in more than 400 participants only the presence of HLA-B∗39:01 had significant impact on the risk for respiratory hospitalization (OR 2.23, p = 0.01) at a significance level of 1%. These findings suggest that the HLA genotype is no major factor determining COVID-19 severity. It is therefore possible that the relatively large viral genome of 29.8 kb encodes for abundant epitopes to mount T-cell responses not limited by the HLA genotype.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection and Vaccination

Background. T cells are central to the early identification and clearance of viral infections and support antibody generation by B cells, making them desirable for assessing the immune response to SARS-CoV-2 infection and vaccines. We combined 2 high-throughput immune profiling methods to create a quantitative picture of the SARS-CoV-2 T-cell response that is highly sensitive, durable, diagnostic, and discriminatory between natural infection and vaccination. Methods. We deeply characterized 116 convalescent COVID-19 subjects by experimentally mapping CD8 and CD4 T-cell responses via antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I and 284 class II viral peptides. We also performed T-cell receptor (TCR) repertoire sequencing on 1815 samples from 1521 PCR-confirmed SARS-CoV-2 cases and 3500 controls to identify shared public TCRs from SARS-CoV-2-associated CD8 and CD4 T cells. Combining these approaches with additional samples from vaccinated individuals, we characterized the response to natural infection as well as vaccination by separating responses to spike protein from other viral targets. Results. We find that T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the SARS-CoV-2 T-cell response peaks about 1-2 weeks after infection and is detectable at least several months after recovery. Applying these data, we trained a classifier to diagnose past SARS-CoV-2 infection based solely on TCR sequencing from blood samples and observed, at 99.8% specificity, high sensitivity soon after diagnosis (Day 3-7 = 85.1%;Day 8-14 = 94.8%) that persists after recovery (Day 29+/convalescent = 95.4%). Finally, by evaluating TCRs binding epitopes targeting all non-spike SARS-CoV-2 proteins, we were able to separate natural infection from vaccination with > 99% specificity. Conclusion. TCR repertoire sequencing from whole blood reliably measures the adaptive immune response to SARS-CoV-2 soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points, and distinguishes post-infection vs. vaccine immune responses with high specificity. This approach to characterizing the cellular immune response has applications in clinical diagnostics as well as vaccine development and monitoring.

Loss of an Immunodominant HLA-Α *01:01 Restricted Epitope for CD8+ Cytotoxic T Lymphocytes (CTLs) in the Delta Variant of COVID-19: An Example of Immunologic Escape and Implications for Immunologic Treatment

SARS-COV-2 (COVID-19) has resulted in over 4 million deaths worldwide. While vaccination has decreased mortality, there remains a need for curative therapies for active infections. Uncertainties regarding the duration of post-vaccination immunity and the rapidity of mutational evolution by this virus suggest that it is unwise to rely on preventative measures alone. Humoral and cellular immunity provide selective pressure for the emergence of variant strains which have eliminated target epitopes. Elimination of immunodominant epitopes provides the strongest advantage to newly emerging strains and, consequently, immunodominant epitopes would be expected to be preferentially eliminated compared to subdominant epitopes in emerging variants. Immunologic treatments for SARS-COV-2 need to be continuously reassessed as new sequence information becomes available. TVGN-489 is a clinical grade product consisting of highly enriched, highly potent CD8+ CTLs recognizing peptides derived from COVID-19 gene/ORF products in an HLA restricted manner. CTLs are generated from apheresis products from individuals who have recovered from COVID-19 infections. Lymphocytes are serially primed and selected using APCs from these donors pulsed with small numbers of peptides encoded by the COVID-19 genome predicted or demonstrated to bind to specific HLA class I alleles. The resulting products are typically >95% CD3+/CD8+, >60% positive by tetramer staining and demonstrate strong cytolytic activity with >60% lysis of peptide pulsed targets typically at an effector to target ratio of 3:1 (See Figure). Given the immunologic pressure to lose dominant target epitopes, we assessed whether the peptides derived from genomic sequences from early SARS-COV-2 strains (and successfully used to generate CTLs from donors infected with these early strains) were still present in the more recently evolved Delta variant. Seven peptides were used to generate CTL products restricted by HLA-A*02:01, the most common allele worldwide. These peptides are derived from the spike (S) and nucleocapsid (N) proteins as well as ORF3a and ORF1ab. The contributions of these peptides to the overall cytotoxicity and tetramer staining range from 2% to 18% without clear immunodominance by one of these peptides. Though identified in early viral strains, these sequences persist in 97.5%-100% of the more than 120 Delta variant sequences present in the NIH database. For HLA-A*01:01, eight peptides derived from the matrix (M) protein as well as ORF1ab and ORF3a were utilized to generate CTLs. Seven of the eight peptides showed binding similar to what was seen with the HLA-A*02:01 peptides (1% to 18%). However, in contrast to HLA-A*02:01, an immunodominant peptide (TTDPSFLGRY, ORF1ab 1637-1646) was noted which was responsible for over half of the observed tetramer binding. This region of ORF1ab was mutated in the Delta variant resulting in loss of this immunodominant epitope from nearly 93% of the Delta genomic sequences in the NIH database. The remaining subdominant peptides were all preserved in 100% of the sequences. Given the growing number of Delta cases, it will be essential to remove this peptide from the HLA-A*01:01 peptide pool used to stimulate SARS-COV-2-specific CD8+ CTLs to avoid encouraging the expansion of cells which would recognize early strains of the virus, but not Delta variants. The remaining CTLs, generated in the absence of TTDPSFLGRY, should be capable of eradicating Delta as well as the earlier prototypic strains of COVID-19. The loss of immunodominant epitopes is not surprising in a virus such as SARS-COV-2, with a high frequency of mutation. This provides an example of immunologic escape similar to what has been described for the Delta variant in the case of HLA-A24. These data are consistent with the hypothesis that immunodominant epitopes will be preferentially eliminated as the virus continues to evolve. They further illustrate the need to monitor viral sequences and to tune the production of CTLs in order to ensure that they can continue to recognize and e fectively treat newly emerging variants of COVID-19. [Formula presented] Disclosures: No relevant conflicts of interest to declare. OffLabel Disclosure: The drug is Cytotoxic T lymphocytes that are specific to COVID-19. Preclinical data.