bioRxivImmunology
Deciphering the quality of SARS-CoV-2 specific T-cell response associated with disease severity, immune memory and heterologous response
A. Perez-Gomez, M. C. Gasca-Capote, J. Vitalle, F. J. Ostos, A. Serna-Gallego, M. Trujillo-Rodriguez, E. Munoz-Muela, T. Giraldez-Perez, J. Praena-Segovia, M. D. Navarro-Amuedo, M. Paniagua-Garcia, M. Garcia-Gutierrez, M. Aguilar-Guisado, I. Rivas-Jeremias, M. R. Jimenez-Leon, S. Bachiller, A. Fernandez-Villar, A. Perez-Gonzalez, A. Gutierrez-Valencia, M. Rafii-El-Idrissi Benhnia, D. Weiskopf, A. Sette, L. F. Lopez-Cortes, E. Poveda, E. Ruiz-Mateos
Abstract
SARS-CoV-2 specific T-cell response has been associated with disease severity, immune memory and heterologous response to endemic coronaviruses. However, an integrative approach combining a comprehensive analysis of the quality of SARS-CoV-2 specific T-cell response with antibody levels in these three scenarios is needed. In the present study we found that, in acute infection, while mild disease was associated with high T-cell polyfunctionality biased to IL-2 production and inversely correlated with anti-S IgG levels, combinations only including IFN-{gamma} with absence of perforin production predominated in severe disease. Seven months after infection, both non-hospitalized and previously hospitalized patients presented robust anti-S IgG levels and SARS-CoV-2 specific T-cell response. In addition, only previously hospitalized patients showed a T-cell exhaustion profile. Finally, combinations including IL-2 in response to S protein of endemic coronaviruses, were the ones associated with SARS-CoV-2 S-specific T-cell response in pre-COVID-19 healthy donors samples. These results have implications for protective immunity against SARS-CoV-2 and recurrent COVID-19 and may help for the design of new prototypes and boosting vaccine strategies.
- organism: human
- assay: proteomics
- assay: flow cytometry
- research focus: host-pathogen & immune response
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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