期刊
PLOS BIOLOGY
卷 16, 期 8, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pbio.2004974
关键词
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资金
- Wellcome Trust
- Royal Society [206250/Z/17/Z]
- Medical Research Council [MR/K021524/1, MR/J008761/1]
- Wellcome Trust [093488/Z/10/Z, 200861/Z/16/Z, 200187/Z/15/Z]
- National Institute for General Medical Sciences [MIDAS U01 GM110721- 01]
- National Institute for Health Research
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U01GM110721] Funding Source: NIH RePORTER
- MRC [MR/K021524/1, MR/J008761/1, MR/R015600/1] Funding Source: UKRI
Human immunity influences the evolution and impact of influenza strains. Because individuals are infected with multiple influenza strains during their lifetime, and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes that shape observed immune responses or to reliably detect recent infection from serological samples. Using a Bayesian model of antibody dynamics at multiple timescales, we explain complex cross-reactive antibody landscapes by inferring participants' histories of infection with serological data from cross-sectional and longitudinal studies of influenza A/H3N2 in southern China and Vietnam. We find that individual-level influenza antibody profiles can be explained by a short-lived, broadly cross-reactive response that decays within a year to leave a smaller long-term response acting against a narrower range of strains. We also demonstrate that accounting for dynamic immune responses alongside infection history can provide a more accurate alternative to traditional definitions of seroconversion for the estimation of infection attack rates. Our work provides a general model for quantifying aspects of influenza immunity acting at multiple timescales based on contemporary serological data and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescales for antigenic responses could also be applied to other multistrain pathogens such as dengue and related flaviviruses.
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