Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.

Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze da...

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Autores principales: Veronika I Zarnitsyna, Rama S Akondy, Hasan Ahmed, Donald J McGuire, Vladimir G Zarnitsyn, Mia Moore, Philip L F Johnson, Rafi Ahmed, Kelvin W Li, Marc K Hellerstein, Rustom Antia
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Publicado: Public Library of Science (PLoS) 2021
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Acceso en línea:https://doaj.org/article/d833a13fe7e34b38b5d1e8330ab10a2f
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spelling oai:doaj.org-article:d833a13fe7e34b38b5d1e8330ab10a2f2021-12-02T19:57:30ZDynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.1553-734X1553-735810.1371/journal.pcbi.1009468https://doaj.org/article/d833a13fe7e34b38b5d1e8330ab10a2f2021-10-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009468https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency of YFV-specific memory CD8 T cells and deuterium enrichment in those cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.1% per day, ∼ double the estimated values for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically.Veronika I ZarnitsynaRama S AkondyHasan AhmedDonald J McGuireVladimir G ZarnitsynMia MoorePhilip L F JohnsonRafi AhmedKelvin W LiMarc K HellersteinRustom AntiaPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 10, p e1009468 (2021)
institution DOAJ
collection DOAJ
language EN
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Veronika I Zarnitsyna
Rama S Akondy
Hasan Ahmed
Donald J McGuire
Vladimir G Zarnitsyn
Mia Moore
Philip L F Johnson
Rafi Ahmed
Kelvin W Li
Marc K Hellerstein
Rustom Antia
Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
description Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency of YFV-specific memory CD8 T cells and deuterium enrichment in those cells 42 days to 1 year post-vaccination. A different dataset, on the loss of YFV-specific CD8 T cells over three decades, was used to assess out of sample predictions of our models. The commonly used exponential and bi-exponential decline models performed relatively poorly. Models with the cell loss following a power law (exactly or approximately) were most predictive. Notably, using only the first year of data, these models accurately predicted T cell frequencies up to 30 years post-vaccination. Our analyses suggest that division rates of these cells drop and plateau at a low level (0.1% per day, ∼ double the estimated values for naive T cells) within one year following vaccination, whereas death rates continue to decline for much longer. Our results show that power laws can be predictive for T cell memory, a finding that may be useful for vaccine evaluation and epidemiological modeling. Moreover, since power laws asymptotically decline more slowly than any exponential decline, our results help explain the longevity of immune memory phenomenologically.
format article
author Veronika I Zarnitsyna
Rama S Akondy
Hasan Ahmed
Donald J McGuire
Vladimir G Zarnitsyn
Mia Moore
Philip L F Johnson
Rafi Ahmed
Kelvin W Li
Marc K Hellerstein
Rustom Antia
author_facet Veronika I Zarnitsyna
Rama S Akondy
Hasan Ahmed
Donald J McGuire
Vladimir G Zarnitsyn
Mia Moore
Philip L F Johnson
Rafi Ahmed
Kelvin W Li
Marc K Hellerstein
Rustom Antia
author_sort Veronika I Zarnitsyna
title Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
title_short Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
title_full Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
title_fullStr Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
title_full_unstemmed Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination.
title_sort dynamics and turnover of memory cd8 t cell responses following yellow fever vaccination.
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/d833a13fe7e34b38b5d1e8330ab10a2f
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