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Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination
bioRxiv - Immunology Pub Date : 2021-01-23 , DOI: 10.1101/2021.01.23.427919
Veronika I. Zarnitsyna , Rama S. Akondy , Hasan Ahmed , Don J. McGuire , Vladimir G. Zarnitsyn , Mia Moore , Philip L. F. Johnson , Rafi Ahmed , Kelvin Li , Marc Hellerstein , Rustom Antia

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 and division rates of YFV-specific memory CD8 T 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 (0.001 per day, ∼double estimates 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.

中文翻译:

黄热病疫苗接种后记忆CD8 T细胞反应的动态和更新

了解免疫记忆如何持续一生需要量化记忆细胞数量的变化以及它们的分裂和死亡率随时间的变化。我们通过使用统计学上强大的混合效应微分方程框架来分析来自两项人类研究的数据,这些研究遵循CD8 T细胞对黄热病疫苗(YFV-17D)的反应,从而解决了这些问题。疫苗接种后42天至1年,模型首先适合YFV特异性记忆CD8 T细胞的频率和分裂率。一个关于YFV特异性CD8 T细胞在过去三十年中丢失的不同数据集被用来评估我们模型的样本预测。常用的指数和双指数下降模型的表现相对较差。遵循幂律(精确或近似)的细胞丢失的模型最具预测性。值得注意的是,仅使用第一年的数据,这些模型就可以准确预测疫苗接种后长达30年的T细胞频率。我们的分析表明,在接种疫苗后的一年内,这些细胞的分裂率下降并趋于平稳(每天0.001,是幼稚T细胞的双倍估计值),而死亡率持续下降的时间更长。我们的结果表明,幂律可以预测T细胞记忆,这一发现可能对疫苗评估和流行病学建模有用。而且,由于幂律的渐近性比任何指数性的下降都缓慢,因此我们的结果有助于从现象学上解释免疫记忆的寿命。我们的分析表明,这些细胞的分裂率在接种疫苗后的一年内下降并保持平稳(每天0.001,对原始T细胞的双倍估计),而死亡率持续下降的时间更长。我们的结果表明,幂律可以预测T细胞记忆,这一发现可能对疫苗评估和流行病学建模有用。而且,由于幂律的渐近性比任何指数性的下降都缓慢,因此我们的结果有助于从现象学上解释免疫记忆的寿命。我们的分析表明,在接种疫苗后的一年内,这些细胞的分裂率下降并趋于平稳(每天0.001,是幼稚T细胞的双倍估计值),而死亡率持续下降的时间更长。我们的结果表明,幂律可以预测T细胞记忆,这一发现可能对疫苗评估和流行病学建模有用。而且,由于幂律的渐近性比任何指数性的下降都缓慢,因此我们的结果有助于从现象学上解释免疫记忆的寿命。可能对疫苗评估和流行病学建模有用的发现。而且,由于幂律的渐近性比任何指数性的下降都缓慢,因此我们的结果有助于从现象学上解释免疫记忆的寿命。可能对疫苗评估和流行病学建模有用的发现。而且,由于幂律的渐近性比任何指数性的下降都缓慢,因此我们的结果有助于从现象学上解释免疫记忆的寿命。
更新日期:2021-01-24
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