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This is a collection of articles and preprints that might be relevant for investigating the association between HLA variability and Covid-19 phenotypes (no guarantee for completeness)
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Preprint/Peer-reviewed
AuthorsTitleYear
Journal/Server
AbstractDOILinkPubMedComment/Contributor
3
Peer-reviewed
Alicia Sanchez-Mazas
HLA studies in the context of coronavirus outbreaks
2020
Swiss Medical Weekly
The unique health situation that we humans are currently living in at the global scale due to the COVID-19 pandemic urges scientists to gain maximum understanding about the characteristics of the new SARS-CoV-2 coronavirus, the way it contaminates individuals, and the genetic and non-genetic factors that influence our susceptibility or protection to its too often severe consequences. Little is known at the moment about specific immune mechanisms that would work against SARS-CoV-2, although such knowledge is expected to play a vital role in the absence of efficient drugs and vaccines, as is the case today. In this context, a particular focus has to be given to the human leucocyte antigen (HLA) system that governs our adaptive immunity.
10.4414/smw.2020.20248https://doi.org/10.4414/smw.2020.2024832297958Review
4
Peer-reviewed
Wei Wang, Zhang Wei,Jingjing Zhang,Ji He,Faming Zhu
Distribution of HLA allele frequencies in 82 Chinese individuals with coronavirus disease-2019
2020HLA
COVID-19 is a respiratory disease caused by a novel coronavirus and is currently a global pandemic. HLA variation is associated with COVID-19, because HLA plays a pivotal role in the immune response to pathogens. Here, 82 individuals with COVID-19 were genotyped for HLA-A,
-B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1, and -DPB1 loci using next-generation sequencing. Frequencies of the HLA-C*07:29, C*08:01G, B*15:27, B*40:06, DRB1*04:06, and DPB1*36:01 alleles were higher, while the frequencies of the DRB1*12:02 and DPB1*04:01 alleles were lower in COVID-19 patients than in the control population, with uncorrected statistical significance. Only HLA-C*07:29 and B*15:27 were significant when the corrected P value was considered. These data suggested that some HLA alleles may be associated with the occurrence of COVID-19.
10.1111/tan.13941https://doi.org/10.1111/tan.1394132424945Brief Communication
5
Peer-reviewed
Syed Faraz Ahmed, Ahmed A. Quadeer, Matthew R. McKay
Human leukocyte antigen susceptibility map for SARS-CoV-2
2020
Journal of Virology
Genetic variability across the three major histocompatibility complex (MHC) class I genes (human leukocyte antigen [lsqb]HLA[rsqb] A, B, and C) may affect susceptibility to and severity of severe acute respiratory syndrome 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19). We execute a comprehensive in silico analysis of viral peptide-MHC class I binding affinity across 145 HLA -A, -B, and -C genotypes for all SARS-CoV-2 peptides. We further explore the potential for cross-protective immunity conferred by prior exposure to four common human coronaviruses. The SARS-CoV-2 proteome is successfully sampled and presented by a diversity of HLA alleles. However, we found that HLA-B*46:01 had the fewest predicted binding peptides for SARS-CoV-2, suggesting individuals with this allele may be particularly vulnerable to COVID-19, as they were previously shown to be for SARS (Lin M, Tseng H-K, Trejaut JA, Lee H-L, Loo J-H, Chu C-C, Chen P-J, Su Y-W, Lim KH, Tsai Z-U, Lin R-Y, Lin R-S, Huang C-H. BMC Med Genet 4:9. 2003.). Conversely, we found that HLA-B*15:03 showed the greatest capacity to present highly conserved SARS-CoV-2 peptides that are shared among common human coronaviruses, suggesting it could enable cross-protective T-cell based immunity. Finally, we report global distributions of HLA types with potential epidemiological ramifications in the setting of the current pandemic.
10.1128/JVI.00510-20
https://jvi.asm.org/content/early/2020/04/16/JVI.00510-20
32303592
6
Peer-reviewed
Syed Faraz Ahmed, Ahmed A. Quadeer, Matthew R. McKay
Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies
2020Viruses
The beginning of 2020 has seen the emergence of COVID-19 outbreak caused by a novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). There is an imminent need to better understand this new virus and to develop ways to control its spread. In this study, we sought to gain insights for vaccine design against SARS-CoV-2 by considering the high genetic similarity between SARS-CoV-2 and SARS-CoV, which caused the outbreak in 2003, and leveraging existing immunological studies of SARS-CoV. By screening the experimentally-determined SARS-CoV-derived B cell and T cell epitopes in the immunogenic structural proteins of SARS-CoV, we identified a set of B cell and T cell epitopes derived from the spike (S) and nucleocapsid (N) proteins that map identically to SARS-CoV-2 proteins. As no mutation has been observed in these identified epitopes among the 120 available SARS-CoV-2 sequences (as of 21 February 2020), immune targeting of these epitopes may potentially offer protection against this novel virus. For the T cell epitopes, we performed a population coverage analysis of the associated MHC alleles and proposed a set of epitopes that is estimated to provide broad coverage globally, as well as in China. Our findings provide a screened set of epitopes that can help guide experimental efforts towards the development of vaccines against SARS-CoV-2.
10.3390/v12030254https://doi.org/10.3390/v1203025432106567
7
Peer-reviewed
Chloe H. Lee, Hashem Koohy
In silico identification of vaccine targets for 2019-nCoV
2020
F1000Research
Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.
10.12688/f1000research.22507.2
https://doi.org/10.12688/f1000research.22507.2
32269766
8
Peer-reviewed
Nicolas Vabret, Graham J. Britton, Conor Gruber, Samarth Hegde, Joel Kim, Maria Kuksin, Rachel Levantovsky, Louise Malle, Alvaro Moreira, Matthew D. Park, Luisanna Pia, Emma Risson, Miriam Saffern, Bérengère Salomé, Myvizhi Esai Selvan, Matthew P. Spindler, Jessica Tan, Verena van der Heide, Jill K. Gregory, Konstantina Alexandropoulos, Nina Bhardwaj, Brian D. Brown, Benjamin Greenbaum, Zeynep H. Gümüş, Dirk Homann, Amir Horowitz, Alice O. Kamphorst, Maria A. Curotto de Lafaille, Saurabh Mehandru, Miriam Merad, Robert M. Samstein, The Sinai Immunology Review Project
Immunology of COVID-19: current state of the science
2020
Immunity
The coronavirus disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has affected millions of people worldwide, igniting an unprecedented effort from the scientific community to understand the biological underpinning of COVID19 pathophysiology. In this review, we summarize the current state of knowledge of innate and adaptive immune responses elicited by SARS-CoV-2 infection and the immunological pathways that likely contribute to disease severity and death. We also discuss the rationale and clinical outcome of current therapeutic strategies as well as prospective clinical trials to prevent or treat SARS- CoV-2 infection.
10.1016/j.immuni.2020.05.002
https://doi.org/10.1016/j.immuni.2020.05.002
9
Peer-reviewed
Alba Grifoni, John Sidney, Yun Zhang Richard H. Scheuermann, Bjoern Peters, Alessandro Sette
A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2
2020
Cell Host & Microbe
Effective countermeasures against the recent emergence and rapid expansion of the 2019 novel coronavirus (SARS-CoV-2) require the development of data and tools to understand and monitor its spread and immune responses to it. However, little information is available about the targets of immune responses to SARS-CoV-2. We used the Immune Epitope Database and Analysis Resource (IEDB) to catalog available data related to other coronaviruses. This includes SARS-CoV, which has high sequence similarity to SARS-CoV-2 and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in SARS-CoV-2 that have high homology to the SARS-CoV virus. Parallel bioinformatic predictions identified a priori potential B and T cell epitopes for SARS-CoV-2. The independent identification of the same regions using two approaches reflects the high probability that these regions are promising targets for immune recognition of SARS-CoV-2. These predictions can facilitate effective vaccine design against this virus of high priority.
10.1016/j.chom.2020.03.002https://doi.org/10.1016/j.chom.2020.03.002
10
Peer-reviewed
Rodrigo Barquera Evelyn Collen Da Di Stéphane Buhler João Teixeira Bastien Llamas José M. Nunes Alicia Sanchez‐Mazas
Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide
2020HLA
We report detailed peptide‐binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV‐1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide‐binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV‐1. Among the strong HLA binders (IC50 ≤ 50), we uncovered 16 alleles (the top ones being A*02:02 , B*15:03 and DRB1*01:02 ) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA‐A*68:01 , B*15:25 , C*03:02 and DRB1*07:01 ) binding all viruses except HIV‐1, and 15 (top ones A*02:01 and C*14:02 ) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.
10.1111/tan.13956https://doi.org/10.1111/tan.1395632475052
11
Peer-reviewed
Ellinghaus D, Degenhardt F, Bujanda L, Buti M, Albillos A, Invernizzi P, Fernández J, Prati D, Baselli G, Asselta RA, Grimsrud MM, Milani C, Aziz FA, Kässens J, May S, Wendorff M, Wienbrandt L, Uellendahl-Werth F, Zheng T, Yi X, de Pablo R, Chercoles AG, Palom A, Garcia-Fernandez A-E, Rodriguez-Frias F, Zanella A, Bandera A, Protti A, Aghemo A, Lleo A, Biondi A, Caballero-Garralda A, Gori A, Tanck A, Nolla AC, Latiano A, Fracanzani AL, Peschuck A, Julià A, Pesenti A, Voza A, Jiménez D, Mateos B, Jimenez BN, Quereda C, Paccapelo C, Gassner C, Angelini C, Cea C, Solier A, Pestaña D, Muñiz-Diaz E, Sandoval E, Paraboschi EM, Navas E, Sánchez FG, Ceriotti F, Martinelli-Boneschi F, Peyvandi F, Blasi F, Téllez L, Blanco-Grau A, Hemmrich-Stanisak G, Grasselli G, Costantino G, Cardamone G, Foti G, Aneli S, Kurihara H, ElAbd H, My I, Galván-Femenia I, Martin J, Erdmann J, Ferrusquía-Acosta J, Garcia-Etxebarria K, Izquierdo-Sanchez L, Bettini LR, Sumoy L, Terranova L, Moreira L, Santoro L, Scudeller L, Mesonero F, Roade L, Rühlemann MC, Schaefer M, Carrabba M, Riveiro-Barciela M, Basso MEF, Valsecchi MG, Hernandez-Tejero M, Acosta-Herrera M, D'Angiò M, Baldini M, Cazzaniga M, Schulzky M, Cecconi M, Wittig M, Ciccarelli M, Rodríguez-Gandía M, Bocciolone M, Miozzo M, Montano N, Braun N, Sacchi N, Martínez N, Özer O, Palmieri O, Faverio P, Preatoni P, Bonfanti P, Omodei P, Tentorio P, Castro P, Rodrigues PM, Ortiz AB, de Cid R, Ferrer R, Gualtierotti R, Nieto R, Goerg S, Badalamenti S, Marsal S, Matullo G, Pelusi S, Juzenas S, Aliberti S, Monzani V, Moreno V, Wesse T, Lenz TL, Pumarola T, Rimoldi V, Bosari S, Albrecht W, Peter W, Romero-Gómez M, D'Amato, M, Duga S, Banales JM, Hov JR, Folseraas T, Valenti L, Franke A, Karlsen TH
Genomewide association study of severe Covid-19 with respiratory failure
2020
New England Journal of Medicine
BACKGROUND There is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19). Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19. METHODS We conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe. After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis. In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case–control panels. RESULTS We detected cross-replicating associations with rs11385942 at locus 3p21.31 and with rs657152 at locus 9q34.2, which were significant at the genomewide level (P<5×10−8) in the meta-analysis of the two case–control panels (odds ratio, 1.77; 95% confidence interval [CI], 1.48 to 2.11; P=1.15×10−10; and odds ratio, 1.32; 95% CI, 1.20 to 1.47; P=4.95×10−8, respectively). At locus 3p21.31, the association signal spanned the genes SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6 and XCR1. The association signal at locus 9q34.2 coincided with the ABO blood group locus; in this cohort, a blood-group–specific analysis showed a higher risk in blood group A than in other blood groups (odds ratio, 1.45; 95% CI, 1.20 to 1.75; P=1.48×10−4) and a protective effect in blood group O as compared with other blood groups (odds ratio, 0.65; 95% CI, 0.53 to 0.79; P=1.06×10−5). CONCLUSIONS We identified a 3p21.31 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system. (Funded by Stein Erik Hagen and others.)
10.1056/NEJMoa2020283https://doi.org/10.1056/NEJMoa202028332558485
GWAS on severe covid-19, showing no major effect in HLA region
12
Peer-reviewed
Alba Grifoni, Daniela Weiskopf, Sydney I. Ramirez, Jose Mateus, Jennifer M. Dan, Carolyn Rydyznski Moderbacher, Stephen A. Rawlings, Aaron Sutherland, Lakshmanane Premkumar, Ramesh S. Jadi, Daniel Marrama, Aravinda M. de Silva, April Frazier, Aaron F. Carlin, Jason A. Greenbaum, Bjoern Peters, Florian Krammer, Davey M. Smith, Shane Crotty, Alessandro Sette
Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals
2020Cell
Understanding adaptive immunity to SARS-CoV-2 is important for vaccine development, interpreting coronavirus disease 2019 (COVID-19) pathogenesis, and calibration of pandemic control measures. Using HLA class I and II predicted peptide “megapools,” circulating SARS-CoV-2-specific CD8+ and CD4+ T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively. CD4+ T cell responses to spike, the main target of most vaccine efforts, were robust and correlated with the magnitude of the anti-SARS-CoV-2 IgG and IgA titers. The M, spike, and N proteins each accounted for 11%–27% of the total CD4+ response, with additional responses commonly targeting nsp3, nsp4, ORF3a, and ORF8, among others. For CD8+ T cells, spike and M were recognized, with at least eight SARS-CoV-2 ORFs targeted. Importantly, we detected SARS-CoV-2-reactive CD4+ T cells in ∼40%–60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating “common cold” coronaviruses and SARS-CoV-2.
10.1016/j.cell.2020.05.015https://doi.org/10.1016/j.cell.2020.05.01532473127
Highlights Spike and M protein as main targets of CD8+ Tcells, but also shows targeting of CD4+ Tcells to several proteins
13
Preprint
Brandon Malone, Boris Simovski, Clément Moliné, Jun Cheng, Marius Gheorghe, Hugues Fontenelle, Ioannis Vardaxis, Simen Tennøe, Jenny-Ann Malmberg, Richard Stratford, Trevor Clancy
Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2: toward universal blueprints for vaccine designs
2020BioRxiv
The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goals of this study were to use artificial intelligence (AI) to predict blueprints for designing universal vaccines against SARS-CoV-2, that contain a sufficiently broad repertoire of T-cell epitopes capable of providing coverage and protection across the global population. To help achieve these aims, we profiled the entire SARS-CoV-2 proteome across the most frequent 100 HLA-A, HLA-B and HLA-DR alleles in the human population, using host-infected cell surface antigen presentation and immunogenicity predictors from the NEC Immune Profiler suite of tools, and generated comprehensive epitope maps. We then used these epitope maps as input for a Monte Carlo simulation designed to identify statistically significant “epitope hotspot” regions in the virus that are most likely to be immunogenic across a broad spectrum of HLA types. We then removed epitope hotspots that shared significant homology with proteins in the human proteome to reduce the chance of inducing off-target autoimmune responses. We also analyzed the antigen presentation and immunogenic landscape of all the nonsynonymous mutations across 3400 different sequences of the virus, to identify a trend whereby SARS-COV-2 mutations are predicted to have reduced potential to be presented by host-infected cells, and consequently detected by the host immune system. A sequence conservation analysis then removed epitope hotspots that occurred in less-conserved regions of the viral proteome. Finally, we used a database of the HLA genotypes of approximately 22 000 individuals to develop a “digital twin” type simulation to model how effective different combinations of hotspots would work in a diverse human population, and used the approach to identify an optimal constellation of epitopes hotspots that could provide maximum coverage in the global population. By combining the antigen presentation to the infected-host cell surface and immunogenicity predictions of the NEC Immune Profiler with a robust Monte Carlo and digital twin simulation, we have managed to profile the entire SARS-CoV-2 proteome and identify a subset of epitope hotspots that could be harnessed in a vaccine formulation to provide a broad coverage across the global population.
10.1101/2020.04.21.052084
https://doi.org/10.1101/2020.04.21.052084NA
14
Preprint
Katie M. Campbell, Gabriela Steiner, Daniel K. Wells, Antoni Ribas, Anusha Kalbasi
Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles
2020BioRxiv
Elucidating antiviral CD8 T lymphocyte responses to SARS-CoV-2 may shed light on the heterogeneity of clinical outcomes and inform vaccine or therapeutic approaches. To facilitate the evaluation of antiviral CD8 T cell responses to SARS-CoV-2, we generated a publicly accessible database of epitopes predicted to bind any class I HLA protein across the entire SARS-CoV-2 proteome. While a subset of epitopes from earlier betacoronaviruses, such as SARS-CoV (SARS), have been validated experimentally, validation systems are often biased toward specific HLA haplotypes (notably HLA-A*02:01) that only account for a fraction of the haplotypes of individuals affected by the SARS-CoV-2 pandemic. To enable evaluation of epitopes across individuals with a variety of HLA haplotypes, we computed the predicted binding affinities between 9-mer peptides derived from the annotated SARS-CoV-2 peptidome across 9,360 MHC class I HLA-A, -B, and -C alleles. There were 6,748 unique combinations of peptides and HLA alleles (pMHCs) with a predicted binding affinity of less than 500nM, including 1,103 unique peptides and 1,022 HLA alleles, spanning 11 annotated superfamilies. These peptides were derived from all 11 proteins spanning the SARS-CoV-2 peptidome, including peptides that have previously been validated experimentally. We also show evidence that these previously validated epitopes may be relevant in other HLA contexts. This complete dataset is available publicly: gs://pici-covid19-data-resources/mhci/peptide_predictions.
10.1101/2020.03.30.016931
https://doi.org/10.1101/2020.03.30.016931NA
15
Preprint
William Chour, Alex M Xu, Alphonsus H.C. Ng, Jongchan Choi, Jingyi Xie, Dan Yuan, John K. Lee, Diane C. Delucia, Rick Edmark, Lesley Jones, Thomas M. Schmitt, Mary E. Chaffee, Venkata Duvvuri, Philip D. Greenberg, Kim Murray, Julie Wallick, Heather A. Algren, William R. Berrington, D. Shane O'Mahoney, Jason D. Goldman, James R Heath
Shared Antigen-specific CD8+ T cell Responses Against the SARS-COV-2 Spike Protein in HLA A*02:01 COVID-19 Participants
2020MedRxiv
We report here on antigens from the SARS-CoV-2 virus spike protein, that when presented by Class I MHC, can lead to cytotoxic CD8+ T cell anti-viral responses in COVID-19 patients. We present a method in which the SARS-CoV-2 spike protein is converted into a library of peptide antigen-Major Histocompatibility Complexes (pMHCs) as single chain trimers that contain the peptide antigen, the MHC HLA allele, and the β-2 microglobulin sub-unit. That library is used to detect the evolution of virus-specific T cell populations from two COVID-19 patients, at two time points over the course of infection. Both patients exhibit similar virus-specific T cell populations, but very different time-trajectories of those populations. These results can be used to track those virus-specific T cell populations over the course of an infection, thus providing deep insight into the variations in immune system trajectories observed in different COVID-19 patients.
10.1101/2020.05.01.20088054
https://doi.org/10.1101/2020.05.04.20085779
NA
16
Preprint
Linda Kachuri, Stephen S Francis, Maike Morrison, Taylor B Cavazos, Sara R Rashkin, Elad Ziv, John S Witte
The landscape of host genetic factors involved in infection to common viruses and SARS-CoV-2
2020MedRxiv
Humans and viruses have co-evolved for millennia resulting in genetic polymorphisms that affect response to viral infection. We conducted a comprehensive study in the UK biobank linking germline genetic variation and gene expression with 28 antigens for 16 viruses in 7924 subjects. We discovered 7 novel loci associated with antibody response (P<5.0×10-8), including FUT2 for human polyomavirus BKV, TMEM173 for Merkel cell polyomavirus (MCV), and TBKBP1 for human herpesvirus 7. Transcriptome-wide analyses identified 114 genes association with response to viral infection, including ECSCR: P=5.0×10-15 (MCV), NTN5: P=1.1×10-9 (BKV), and P2RY13: P=1.1×10-8 (Epstein-Barr virus nuclear antigen). Signals in human leukocyte antigen (HLA) class II region dominated the landscape of viral antibody response, with 40 independent loci and 14 independent classical alleles, 7 of which exhibited pleiotropic effects across viral families. We also link viral response genes with complex diseases, such as C4A expression in varicella zoster virus and schizophrenia. Lastly, based on 1028 subjects tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we identify 7 class II HLA susceptibility alleles (5 associated with other viruses). We also observe that genetic determinants of ACE2 expression may influence SARS- CoV-2 susceptibility. Our findings elucidate the genetic architecture of host response to viral infection, with potential implications for complex diseases and COVID-19.
10.1101/2020.05.01.20088054
https://doi.org/10.1101/2020.05.01.20088054
NA
17
Preprint
Marek Prachar, Sune Justesen, Daniel Bisgaard Steen-Jensen, Stephan Thorgrimsen, Erik Jurgons, Ole Winther, Frederik Otzen Bagger
COVID-19 Vaccine Candidates: Prediction and Validation of 174 SARS-CoV-2 Epitopes
2020BioRxiv
The recent outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested 19 epitope-HLA-binding prediction tools, and using an in vitro peptide MHC stability assay, we assessed 777 peptides that were predicted to be good binders across 11 MHC allotypes. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allotype in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA allotypes. Our findings may contribute to the design of an efficacious vaccine against COVID-19.
10.1101/2020.03.20.000794
https://doi.org/10.1101/2020.03.20.000794NA
18
Preprint
Daniel Ward, Matthew Higgins, Jody E. Phelan, Martin L. Hibberd, Susana Campino, Taane G Clark
An integrated in silico immuno-genetic analytical platform provides insights into COVID-19 serological and vaccine targets
2020BioRxiv
Background The COVID-19 pandemic is causing a major global health and socio-economic burden, instigating the mobilisation of resources into the development of control tools, such as diagnostics and vaccines. The poor performance of some diagnostic serological tools has emphasised the need for up to date immune-informatic analyses to inform the selection of viable targets for further study. This requires the integration and analysis of genetic and immunological data for SARS-CoV-2 and its homology with other human coronavirus species to understand cross-reactivity. Methods We have developed an online tool for SARS-CoV-2 research, which combines an extensive epitope mapping and prediction meta-analysis, with an updated variant database (55,944 non-synonymous mutations) based on 16,087 whole genome sequences, and an analysis of human coronavirus homology. To demonstrate its utility, we present an integrated analysis of the SARS-CoV-2 spike and nucleocapsid proteins, which are candidate vaccine and serological diagnostic targets. Results Our analysis reveals that the nucleocapsid protein in its native form appears to be a sub-optimal target for use in serological diagnostic platforms. Whilst, a further analysis suggests that orf3a proteins may be a suitable alternative target for diagnostic assays. Conclusions The tool can be accessed online (http://genomics.lshtm.ac.uk/immuno) and will serve as a useful tool for biological discovery in the fight against SARS-CoV-2. Further, it may be adapted to inform on biological targets in future outbreaks, including new human coronaviruses that spill over from animal hosts.
10.1101/2020.05.11.089409
https://doi.org/10.1101/2020.05.11.089409NA
19
Preprint
Leticia Kuri-Cervantes, M. Betina Pampena, Wenzhao Meng, Aaron M. Rosenfeld, Caroline A.G. Ittner, Ariel R. Weisman, Roseline Agyekum, Divij Mathew, Amy E. Baxter, Laura Vella, Oliva Kuthuru, Sokratis Apostolidis, Luanne Bershaw, Jeannete Dougherty, Allison R. Greenplate, Ajinkya Pattekar, Justin Kim, Nicholas Han, Sigrid Gouma, Madison E. Weirick, Claudia P. Arevalo, Marcus J. Bolton, Eileen C. Goodwin, Elizabeth M. Anderson, Scott E. Hensley, Tiffanie K. Jones, Nilam S. Mangalmurti, Eline T. Luning Prak, E. John Wherry, Nuala J. Meyer, Michael R. Betts
Immunologic perturbations in severe COVID-19/SARS-CoV-2 infection
2020BioRxiv
Although critical illness has been associated with SARS-CoV-2-induced hyperinflammation, the immune correlates of severe COVID-19 remain unclear. Here, we comprehensively analyzed peripheral blood immune perturbations in 42 SARS-CoV-2 infected and recovered individuals. We identified broad changes in neutrophils, NK cells, and monocytes during severe COVID-19, suggesting excessive mobilization of innate lineages. We found marked activation within T and B cells, highly oligoclonal B cell populations, profound plasmablast expansion, and SARS-CoV-2-specific antibodies in many, but not all, severe COVID-19 cases. Despite this heterogeneity, we found selective clustering of severe COVID-19 cases through unbiased analysis of the aggregated immunological phenotypes. Our findings demonstrate broad immune perturbations spanning both innate and adaptive leukocytes that distinguish dysregulated host responses in severe SARS-CoV-2 infection and warrant therapeutic investigation.
10.1101/2020.05.18.101717
https://doi.org/10.1101/2020.05.18.101717NA
20
Preprint
Divij Mathew, Josephine R. Giles, Amy E. Baxter, Allison R. Greenplate, Jennifer E. Wu, Cécile Alanio, Derek A. Oldridge, Leticia Kuri-Cervantes, M. Betina Pampena, Kurt D’Andrea, Sasikanth Manne, Zeyu Chen, Yinghui Jane Huang, John P. Reilly, Ariel R Weisman, Caroline A.G. Ittner, Oliva Kuthuru, Jeanette Dougherty, Kito Nzingha, Nicholas Han, Justin Kim, Ajinkya Pattekar, Eileen C. Goodwin, Elizabeth M. Anderson, Madison E. Weirick, Sigrid Gouma, Claudia P. Arevalo, Marcus J. Bolton, Fang Chen, Simon F. Lacey, Scott E. Hensley, Sokratis Apostolidis, Alexander C. Huang, Laura A. Vella, The UPenn COVID Processing Unit, Michael R. Betts, Nuala J. Meyer, E. John Wherry
Deep immune profiling of COVID-19 patients reveals patient heterogeneity and distinct immunotypes with implications for therapeutic interventions
2020BioRxiv
COVID-19 has become a global pandemic. Immune dysregulation has been implicated, but immune responses remain poorly understood. We analyzed 71 COVID-19 patients compared to recovered and healthy subjects using high dimensional cytometry. Integrated analysis of ∼200 immune and >30 clinical features revealed activation of T cell and B cell subsets, but only in some patients. A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses could reach >30% of circulating B cells. However, another subgroup had lymphocyte activation comparable to uninfected subjects. Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change. These analyses identified three “immunotypes” associated with poor clinical trajectories versus improving health. These immunotypes may have implications for therapeutics and vaccines.
10.1101/2020.05.20.106401
https://doi.org/10.1101/2020.05.20.106401NA
21
Preprint
Ang Gao, Zhilin Chen, Florencia Pereyra Segal, Mary Carrington, Hendrik Streeck, Arup K. Chakraborty, Boris Julg
Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2
2020BioRxiv
We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given a Human Leukocyte Antigen (HLA) genotype. The model was trained and tested on experimental data on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. The method is more accurate than publicly available models. Our model predicts that only a fraction of SARS-CoV-2 epitopes that have been predicted to bind to HLA molecules is immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but the immunogenic epitopes in the SARS-CoV-2 spike protein alone are unlikely to do so. Our model predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to those contained in low-pathogenicity coronaviruses circulating in the population. Thus, we suggest that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.
10.1101/2020.05.14.095885
https://doi.org/10.1101/2020.05.14.095885NA
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Preprint
Yiwen Zhang, Junsong Zhang, Yingshi Chen, Baohong Luo, Yaochang Yuan, Feng Huang, Tao Yang, Fei Yu, Jun Liu, Bingfen Liu, Zheng Song, Jingliang Chen, Ting Pan, Xu Zhang, Yuzhuang Li, Rong Li, Wenjing Huang, Fei Xiao, Hui Zhang
The ORF8 Protein of SARS-CoV-2 Mediates Immune Evasion through Potently Downregulating MHC-I
2020BioRxiv
SARS-CoV-2 infection have caused global pandemic and claimed over 5,000,000 tolls1–4. Although the genetic sequences of their etiologic viruses are of high homology, the clinical and pathological characteristics of COVID-19 significantly differ from SARS5,6. Especially, it seems that SARS-CoV-2 undergoes vast replication in vivo without being effectively monitored by anti-viral immunity7. Here, we show that the viral protein encoded from open reading frame 8 (ORF8) of SARS-CoV-2, which shares the least homology with SARS-CoV among all the viral proteins, can directly interact with MHC-I molecules and significantly down-regulates their surface expression on various cell types. In contrast, ORF8a and ORF8b of SARS-CoV do not exert this function. In the ORF8-expressing cells, MHC-I molecules are selectively target for lysosomal degradation by an autophagy-dependent mechanism. As a result, CTLs inefficiently eliminate the ORF8-expressing cells. Our results demonstrate that ORF8 protein disrupts antigen presentation and reduces the recognition and the elimination of virus-infected cells by CTLs8. Therefore, we suggest that the inhibition of ORF8 function could be a strategy to improve the special immune surveillance and accelerate the eradication of SARS-CoV-2 in vivo.
10.1101/2020.05.24.111823
https://doi.org/10.1101/2020.05.24.111823NA
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PreprintEthan Fast, Russ B. Altman, Binbin Chen
Potential T-cell and B-cell Epitopes of 2019-nCoV
2020BioRxiv
As of early March, 2019-nCoV has infected more than one hundred thousand people and claimed thousands of lives. 2019-nCoV is a novel form of coronavirus that causes COVID-19 and has high similarity with SARS-CoV. No approved vaccine yet exists for any form of coronavirus. Here we use computational tools from structural biology and machine learning to identify 2019-nCoV T-cell and B-cell epitopes based on viral protein antigen presentation and antibody binding properties. These epitopes can be used to develop more effective vaccines and identify neutralizing antibodies. We identified 405 viral peptides with good antigen presentation scores for both human MHC-I and MHC-II alleles, and two potential neutralizing B-cell epitopes near the 2019-nCoV spike protein receptor binding domain (440-460 and 494-506). Analyzing mutation profiles of 68 viral genomes from four continents, we identified 96 coding-change mutations. These mutations are more likely to occur in regions with good MHC-I presentation scores (p=0.02). No mutations are present near the spike protein receptor binding domain. Based on these findings, the spike protein is likely immunogenic and a potential vaccine candidate. We validated our computational pipeline with SARS-CoV experimental data.
10.1101/2020.02.19.955484
https://doi.org/10.1101/2020.02.19.955484NA
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Preprint
Marco Antonio M Pretti, Romulo G Galvani, Gustavo Fioravanti Vieira, Adriana Bonomo, Martin Hernan Bonamino, Mariana Boroni
Class I HLA allele restricted antigenic coverage for Spike and N proteins is associated with divergent outcomes for COVID-19
2020MedRxiv
The world is dealing with the worst pandemics ever. SARS-CoV-2 is the etiological agent of COVID-19 that has already spread to more than 200 countries. However, infectivity, severity and mortality rates do not affect all countries equally. Here we investigate the landscape of potential HLA-I A and B restricted SARS-CoV-2-derived antigens and how different populations in the world are predicted to respond to those peptides considering their HLA-I distribution frequencies. Clustering of HLA-A and HLA-B allele frequencies partially separates most countries with the lowest number of deaths per million inhabitants from the other countries. We further correlated the patterns of in silico predicted strong binder peptides and epidemiological data. The number of deaths per million inhabitants inversely correlated with the antigen coverage of peptides derived from viral protein S, while a direct correlation was observed for those derived from viral protein N, highlighting a potential risk group carrying HLAs associated with the latter. In addition, we identified 7 potential antigens bearing at least one amino acid of the small insertion that differentiates SARS-CoV-2 from previous coronavirus strains. We believe these data can contribute to the search for peptides with the potential to be used in vaccine strategies.
10.1101/2020.06.03.20121301
https://doi.org/10.1101/2020.06.03.20121301
NA
25
Preprint
Eric Wilson, Gabrielle Hirneise, Abhishek Singharoy, Karen S Anderson
Total predicted MHC-I epitope load is inversely associated with mortality from SARS-CoV-2
2020MedRxiv
Polymorphisms in MHC-I protein sequences across human populations significantly impacts viral peptide binding capacity and thus alters T cell immunity to infection. Consequently, allelic variants of the MHC-I protein have been found to be associated with patient outcome to various viral infections, including SARS-CoV. In the present study, we assess the relationship between observed SARS-CoV-2 population mortality and the predicted viral binding capacities of 52 common MHC-I alleles. Potential SARS-CoV-2 MHC-I peptides were identified using a consensus MHC-I binding and presentation prediction algorithm, called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolved a few hundred high-confidence MHC-I peptides. By weighing individual MHC allele SARS-CoV-2 binding capacity by population frequency in 23 countries, we discover a strong inverse correlation between the predicted population SARS-CoV-2 peptide binding capacity and observed mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produces a stronger association with observed mortality rate, highlighting the importance of S, N, M, E proteins in driving productive immune responses. These results bring to light how molecular changes in the MHC-I proteins may affect population-level outcomes of viral infection.
10.1101/2020.05.08.20095430
https://doi.org/10.1101/2020.05.08.20095430
NA
26
PreprintYosuke Tanigawa, Manuel Rivas
Initial Review and Analysis of COVID-19 Host Genetics and Associated Phenotypes
2020
Preprints.org
The global pandemic of COVID-19 accounts for more than 14,000 deaths worldwide. However, little is known about the host genetics interaction with infection and COVID-19 progression. To better understand the role of host genetics, we review the current literature, aggregate readily available genetic resources, and provide some updated analysis relevant to COVID-19 and associated phenotypes. Using the unrelated individuals in UK Biobank (total n = 337,579 across 5 populations), we aggregate human leukocyte antigen and ABO blood type frequencies. We find significant and consistent risk reduction of blood group O reported in Zhao et al. and encourage broad sharing of ABO blood type frequencies that are readily accessible across COVID-19 with mild, moderate, and severe/critical symptoms for robust inferences at https://tinyurl.com/abo-covid19. In addition, we generate polygenic risk scores (PRSs) weights for 29 blood measurements, including clinically relevant haematological measurements for COVID-19, such as lymphocyte count and percentage. Focusing on the 8 most COVID-19 clinically relevant blood measurements, we performed PRS-PheWAS analysis across 44 disease antigen measurements (n = 6,643 unrelated individuals in White British group), infectious diseases and acute respiratory infections (n = 20,928 cases and 349,000 controls across 3 population groups) and deaths (n = 1,846 cases and 368,082 controls), recorded in hospital inpatient record and death registry data, respectively, in UK Biobank, and find host genetic PRS associations with disease risk. Taken together, we anticipate these resources (https://github.com/rivas-lab/covid19) will aid in improving our understanding of host genetic risk factors playing a role in SARS-CoV-2 infection and COVID-19 disease severity.
10.20944/preprints202003.0356.v1https://doi.org/10.20944/preprints202003.0356.v1NA
27
PreprintRene L Warren, Inanc Birol
HLA predictions from the bronchoalveolar lavage fluid samples of five patients at the early stage of the Wuhan seafood market COVID-19 outbreak
2020ArXiv
We are in the midst of a global viral pandemic, one with no cure and a high mortality rate. The Human Leukocyte Antigen (HLA) gene complex plays a critical role in host immunity. We predicted HLA class I and II alleles from the transcriptome sequencing data prepared from the bronchoalveolar lavage fluid samples of five patients at the early stage of the COVID-19 outbreak. We identified the HLA-I allele A*24:02 in four out of five patients, which is higher than the expected frequency (17.2%) in the South Han Chinese population. The difference is statistically significant with a p-value less than 10−4. Our analysis results may help provide future insights on disease susceptibility.
NAhttps://arxiv.org/abs/2004.07108NA
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Papers on previous coronaviruses or relevant outbreaks (not complete)
31
Peer-reviewed
Yuying Sun, Yz Xi
Association Between HLA Gene Polymorphism and the Genetic Susceptibility of SARS Infection
2014
IntechOpen
Theoretically, any infectious disease with an infection source, transmission route, and susceptible population is able to infect any population. However, studies of human development history, especially those of infectious disease history, have clearly shown that ethnic and regional differences in susceptibility to some infectious diseases actually exist, even if their infection sources and transmission routes are the same. In terms of the 40 types of new infectious diseases that have occurred worldwide in the past 40 years, the epidemiology of some infectious diseases (including severe acute respiratory syndrome (SARS)) has been dominated by regional/territorial or ethnic oriented infections. Examples, along with the year of first occurrence, include:Ebola hemorrhagic fever caused by Ebola virus (1977), Legionnaires' disease caused by Legionella pneumophila (1977), hemorrhagic fever with renal syndrome caused by hantavirus (1977), T cell lymphoma leukemia caused by human T-lymphotropic virus type I (1980), hemorrhagic colitis caused by E. coli O157:H7 (1982), hairy cell leukemia caused by human T-lymphotropic virus type II (1982), and the British BSE (bovine spongiform encephalopathy) that created worldwide shock. Along with the effects of infection sources and transmission routes, the contributions of racial or genetic factors to these regional/territorial diseases are still under discussion. Clearly, these infectious diseases occurred more frequently and with greater severity in certain regions and ethnicities. The SARS outbreak in 2002-2003 spread mainly in Asia, especially in China; the most susceptible populations were mainland and overseas Chinese. These observations lead us to consider the important theoretical and practical topic of the relationship between SARS genetic predisposition and individual clinical onset. However, the sudden disappearance of SARS also left us with many revelations.
10.5772/57561https://doi.org/10.5772/57561
This is a book chapter about SARS (not Covid19 but Cov1) from a book entitled: "HLA and associated important diseases" which one can find here: https://www.intechopen.com/books/hla-and-associated-important-diseases
32
Peer-reviewed
Marie Lin, Hsiang-Kuang Tseng, Jean A Trejaut, Hui-Lin Lee, Jun-Hun Loo, Chen-Chung Chu, Pei-Jan Chen, Ying-Wen Su, Ken Hong Lim, Zen-Uong Tsai, Ruey-Yi Lin, Ruey-Shiung Lin & Chun-Hsiung Huang
Association of HLA class I with severe acute respiratory syndrome coronavirus infection
2003
BMC Medical Genetics
Background:The human leukocyte antigen (HLA) system is widely used as a strategy in the search for the etiology of infectious diseases and autoimmune disorders. During the Taiwan epidemic of severe acute respiratory syndrome (SARS), many health care workers were infected. In an effort to establish a screening program for high risk personal, the distribution of HLA class I and II alleles in case and control groups was examined for the presence of an association to a genetic susceptibly or resistance to SARS coronavirus infection. Methods: HLA-class I and II allele typing by PCR-SSOP was performed on 37 cases of probable SARS, 28 fever patients excluded later as probable SARS, and 101 non-infected health care workers who were exposed or possibly exposed to SARS coronavirus. An additional control set of 190 normal healthy unrelated Taiwanese was also used in the analysis. Results: Woolf and Haldane Odds ratio (OR) and corrected P-value (Pc) obtained from two tails Fisher exact test were used to show susceptibili y of HLA class I or class II alleles with coronavirus infection. At first, when analyzing infected SARS patients and high risk health care workers groups, HLA-B*4601 (OR = 2.08, P = 0.04, Pc = n.s.) and HLA-B*5401 (OR = 5.44, P = 0.02, Pc = n.s.) appeared as the most probable elements that may be favoring SARS coronavirus infection. After selecting only a "severe cases" patient group from the infected "probable SARS" patient group and comparing them with the high risk health care workers group, the severity of SARS was shown to be significantly associated with HLA-B*4601 (P = 0.0008 or Pc = 0.0279). Conclusions: Densely populated regions with genetically related southern Asian populations appear to be more affected by the spreading of SARS infection. Up until recently, no probable SARS patients were reported among Taiwan indigenous peoples who are genetically distinct from the Taiwanese general population, have no HLA-B* 4601 and have high frequency of HLA-B* 1301. While increase of HLA-B* 4601 allele frequency was observed in the "Probable SARS infected" patient group, a further significant increase of the allele was seen in the "Severe cases" patient group. These results appeared to indicate association of HLA-B* 4601 with the severity of SARS infection in Asian populations. Independent studies are needed to test these results.
10.1186/1471-2350-4-9https://doi.org/10.1186/1471-2350-4-912969506Paper on SARS (Cov1)
33
Peer-reviewed
Naoto Keicho, Satoru Itoyama,a Koichi Kashiwase, Nguyen Chi Phi, Hoang Thuy Long, Le Dang Ha, Vo Van Ban, Bach Khanh Hoa, Nguyen Thi Le Hang, Minako Hijikata, Shinsaku Sakurada, Masahiro Satake, Katsushi Tokunaga, Takehiko Sasazuki, and Tran Quy
Association of human leukocyte antigen class II alleles with severe acute respiratory syndrome in the Vietnamese population
2009
Human Immunology
Excessive immune response is believed to play a role in the development of severe acute respiratory syndrome (SARS). Inhomogeneous spread of SARS led one to think of an Asian genetic predisposition and contribution of human leukocyte antigen (HLA) to the disease susceptibility. However, past case-control studies showed inconsistent results. In Viet Nam, of 62 patients with SARS, 44 participated in the present study together with 103 individuals who had contact with SARS patients and 50 without contact history. HLA-DRB1*12 was more frequently shown in SARS patients than in controls (corrected p = 0.042). HLA-DRB1*1202, the predominant allele in the Vietnamese population showed the strongest association with SARS in a dominant model (corrected p = 0.0065 and 0.0052, depending on the controls to be compared). Our results and accumulated data on HLA in the Asian populations would help in the understanding of associations with emerging infectious diseases.
10.1016/j.humimm.2009.05.006
https://doi.org/10.1016/j.humimm.2009.05.006
19445991Paper on SARS (Cov1)
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