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

• Type of Material: Article
• Authors: Veronika Zarnitsyna, Emory University; Rama Akondy, Emory University; Hasan Ahmed, Emory University; Donald J. McGuire, Emory University; Vladimir G. Zarnitsyn, Moonlight Therapeutics Inc.; Mia Moore, Fred Hutchinson Cancer Research Center; Philip L. F. Johnson, University of Maryland; Rafi Ahmed, Emory University; Kelvin W. Li, University of California Berkeley; Marc K. Hellerstein, University of California Berkeley; Rustom Antia, Emory University
• Language: English
• Date: 2021-10-01
• Publisher: PUBLIC LIBRARY SCIENCE
• Publication Version: Final Published Version
• Copyright Statement: © 2021 Zarnitsyna et al
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pcbi.1009468
• Title of Journal or Parent Work: PLOS COMPUTATIONAL BIOLOGY
• Volume: 17
• Issue: 10
• Start Page: e1009468
• End Page: e1009468
• Grant/Funding Information: VIZ, RAn were supported by National Institutes of Health grant U01 HL139483. RAn, VIZ, RAh were supported by National Institutes of Health grant U01 AI150747. RAn, HA were supported by National Institutes of Health grant U01 AI144616. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
• Keywords: SUBSET; INFECTION; Biochemistry & Molecular Biology; Biochemical Research Methods; HUMORAL IMMUNITY; IN-VITRO; SMALLPOX; EFFECTOR; PROLIFERATION; LIFE-SPAN; LYMPHOCYTES; Mathematical & Computational Biology; DIFFERENTIATION; Science & Technology; Life Sciences & Biomedicine
• Research Categories: Biology, Molecular; Chemistry, Biochemistry

Abstract

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.