AUTHOR=Pretti Marco Antônio M. , Galvani Rômulo G. , Vieira Gustavo Fioravanti , Bonomo Adriana , Bonamino Martín H. , Boroni Mariana TITLE=Class I HLA Allele Predicted Restricted Antigenic Coverages for Spike and Nucleocapsid Proteins Are Associated With Deaths Related to COVID-19 JOURNAL=Frontiers in Immunology VOLUME=11 YEAR=2020 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2020.565730 DOI=10.3389/fimmu.2020.565730 ISSN=1664-3224 ABSTRACT=

The world is dealing with one of 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 consider 140 HLA alleles and extensively investigate the landscape of 3,723 potential HLA-I A and B restricted SARS-CoV-2-derived antigens and how 37 countries in the world are predicted to respond to those peptides considering their HLA-I distribution frequencies. The 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 population coverage and epidemiological data. The number of deaths per million inhabitants correlates to the predicted antigen coverage of S and N derived peptides and its module is influenced if a given set of frequent or rare HLA alleles are analyzed in a given population. Moreover, we highlighted a potential risk group carrying HLAs associated with an elevated number of deaths per million inhabitants. In addition, we identified three potential antigens bearing at least one amino acid of the four-length 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 considering the role of herd immunity to hamper the spread of the disease. Importantly, to the best of our knowledge, this work is the first to use a populational approach in association with COVID-19 outcome.