Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
PLoS Biol. 2015 Mar 3;13(3):e1002082. doi: 10.1371/journal.pbio.1002082. eCollection 2015 Mar.
The immunity of a host population against specific influenza A strains can influence a number of important biological processes, from the emergence of new virus strains to the effectiveness of vaccination programmes. However, the development of an individual's long-lived antibody response to influenza A over the course of a lifetime remains poorly understood. Accurately describing this immunological process requires a fundamental understanding of how the mechanisms of boosting and cross-reactivity respond to repeated infections. Establishing the contribution of such mechanisms to antibody titres remains challenging because the aggregate effect of immune responses over a lifetime are rarely observed directly. To uncover the aggregate effect of multiple influenza infections, we developed a mechanistic model capturing both past infections and subsequent antibody responses. We estimated parameters of the model using cross-sectional antibody titres to nine different strains spanning 40 years of circulation of influenza A(H3N2) in southern China. We found that "antigenic seniority" and quickly decaying cross-reactivity were important components of the immune response, suggesting that the order in which individuals were infected with influenza strains shaped observed neutralisation titres to a particular virus. We also obtained estimates of the frequency and age distribution of influenza infection, which indicate that although infections became less frequent as individuals progressed through childhood and young adulthood, they occurred at similar rates for individuals above age 30 y. By establishing what are likely to be important mechanisms driving epochal trends in population immunity, we also identified key directions for future studies. In particular, our results highlight the need for longitudinal samples that are tested against multiple historical strains. This could lead to a better understanding of how, over the course of a lifetime, fast, transient antibody dynamics combine with the longer-term immune responses considered here.
宿主群体对特定甲型流感株的免疫力可以影响许多重要的生物学过程，从新病毒株的出现到疫苗接种计划的有效性。然而，个体对甲型流感的长期抗体反应的发展在一生中仍然知之甚少。准确描述这一免疫学过程需要从根本上了解增强和交叉反应的机制如何应对反复感染。建立这些机制对抗体滴度的贡献仍然具有挑战性，因为一生中免疫反应的总效应很少直接观察到。为了揭示多次流感感染的总效应，我们开发了一种既能捕捉过去感染又能捕捉随后抗体反应的机制模型。我们使用跨越中国南方 40 年甲型流感（H3N2）循环的 9 种不同株系的横断面抗体滴度来估计模型的参数。我们发现，“抗原年龄”和迅速衰减的交叉反应是免疫反应的重要组成部分，这表明个体感染流感株系的顺序塑造了对特定病毒的观察中和滴度。我们还获得了流感感染的频率和年龄分布的估计值，这表明尽管随着个体进入儿童期和青年期，感染的频率降低，但 30 岁以上个体的感染率相似。通过确定可能是驱动人群免疫阶段性趋势的重要机制，我们还确定了未来研究的关键方向。特别是，我们的结果强调了需要针对多个历史株系进行纵向采样的必要性。这可能会更好地了解在一生中，快速、短暂的抗体动力学如何与这里考虑的长期免疫反应相结合。
