@article{9eb84063c2384428bf4a5dc0b827bc6c,
title = "Total predicted MHC-I epitope load is inversely associated with population mortality from SARS-CoV-2",
abstract = "Polymorphisms in MHC-I protein sequences across human populations significantly affect viral peptide binding capacity, and thus alter T cell immunity to infection. 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 are identified using a consensus MHC-I binding and presentation prediction algorithm called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolve a few hundred highly probable MHC-I peptides. By weighing individual MHC allele-specific SARS-CoV-2 binding capacity with population frequency in 23 countries, we discover a strong inverse correlation between predicted population SARS-CoV-2 peptide binding capacity and mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produce a stronger association with observed mortality rate, highlighting the importance of S, N, M, and E proteins in driving productive immune responses. Wilson et al. define a predicted MHC allele-specific hierarchy for the presentation of peptides derived from SARS-CoV-2 viral proteins. They find that a composite population-level metric combining predicted MHC allele SARS-CoV-2 binding capacity and endemic allele frequencies is inversely correlated with deaths per million.",
keywords = "CD8, EnsembleMHC, MHC-I, SARS-CoV-2, epitope, immunoinformatics, population dynamics, risk",
author = "Wilson, {Eric A.} and Gabrielle Hirneise and Abhishek Singharoy and Anderson, {Karen S.}",
note = "Funding Information: We would like to thank Drs. Diego Chowell, Matthew Scotch, Sri Krishna, and Shay Ferdosi as well as Mr. John Vant, Mr. Ryan Boyd, and Ms. Mollie Peters for critical feedback and discussion. Finally, we would like to thank ASU Research computing for allocating the computational resources used in this study. We acknowledge start-up funds from the SMS and CASD at Arizona State University. A.S. acknowledges funding from the CAREER award from NSF (MCB-1942763) and the Gordon and Betty Moore foundation. E.A.W. A.S. and K.S.A. contributed to the study design and interpretation. E.A.W. performed the data collection and analysis. E.A.W. G.H. A.S. and K.S.A contributed to writing the manuscript. All of the authors reviewed and approved the final version of the manuscript. E.A.W. A.S. and K.S.A. have a patent application on EnsembleMHC and T cell targeting using epitopes described in this article, licensed to SafeGen Therapeutics (K.S.A. co-founder). The authors declare no other competing interests. Funding Information: We would like to thank Drs. Diego Chowell, Matthew Scotch, Sri Krishna, and Shay Ferdosi as well as Mr. John Vant, Mr. Ryan Boyd, and Ms. Mollie Peters for critical feedback and discussion. Finally, we would like to thank ASU Research computing for allocating the computational resources used in this study. We acknowledge start-up funds from the SMS and CASD at Arizona State University . A.S. acknowledges funding from the CAREER award from NSF ( MCB-1942763 ) and the Gordon and Betty Moore foundation. Publisher Copyright: {\textcopyright} 2021 The Author(s)",
year = "2021",
month = mar,
day = "16",
doi = "10.1016/j.xcrm.2021.100221",
language = "English (US)",
volume = "2",
journal = "Cell Reports Medicine",
issn = "2666-3791",
publisher = "Cell Press",
number = "3",
}