A bioinformatic analysis of T-cell epitope diversity in SARS-CoV-2 variants: association with COVID-19 clinical severity in the United States population

• DOI: 10.3389/fimmu.2024.1357731
• Publication Date: 2024-05-09T09:37:06Z
• Authors: Grace J. Kim; Jacob H. Elnaggar; Mallory Varnado; Amy K. Feehan; Darlene Tauzier; Rebecca Rose; Susanna L. Lamers; Maya Sevalia; Najah Nicholas; Elizabeth Gravois; Daniel Fort; Judy S. Crabtree; Lucio Miele
• Keywords: 0301 basic medicine; HLA-A Antigens; SARS-CoV-2; Immunology; Epitopes, T-Lymphocyte; COVID-19; Computational Biology; bioinformatics; CD8 T cell epitope; RC581-607; CD8-Positive T-Lymphocytes; Severity of Illness Index; United States; HLA; 03 medical and health sciences; HLA-B Antigens; Spike Glycoprotein, Coronavirus; Humans; Immunologic diseases. Allergy; T cell epitope; Alleles

Long-term immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the identification of T-cell epitopes affecting host immunogenicity. In this computational study, we explored CD8 + epitope diversity estimated in 27 most common HLA-A and HLA-B alleles, representing United States population. Analysis 16 SARS-CoV-2 variants [B.1, Alpha (B.1.1.7), five Delta (AY.100, AY.25, AY.3, AY.3.1, AY.44), nine Omicron (BA.1, BA.1.1, BA.2, BA.4, BA.5, BQ.1, BQ.1.1, XBB.1, XBB.1.5)] analyzed MHC class I alleles revealed that conservation was at 87.6%–96.5% spike (S), 92.5%–99.6% membrane (M), 94.6%–99% nucleocapsid (N). As virus mutated, an increasing proportion S experienced reduced predicted binding affinity: 70% BQ.1-XBB.1.5 decreased binding, as compared with ~3% ~15% earlier strains AY.100–AY.44 BA.1–BA.5, respectively. Additionally, identified several novel candidate HLA may be more susceptible to disease, notably HLA-A*32:01 , HLA-A*26:01 HLA-B*53:01 relatively protected from such HLA-A*31:01 HLA-B*40:01 HLA-B*44:03 HLA-B*57:01. Our findings support hypothesis viral genetic variation immunogenicity contributes determining clinical severity COVID-19. Achieving long-term COVID-19 will require understanding relationship between T cells, variants, genetics. This project is one first explore putatively impacts much