A deterministic model for homologous antibody dependant enhancement on influenza infection

IF 8.8 3区 医学 Q1 Medicine
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Abstract

Antibody dependant enhancement refers that viral infectivity was unexpectedly enhanced at low antibody concentration compared to when antibodies were absent, such as Dengue, Zika and influenza virus. To mathematically describe switch from enhancement to neutralisation with increase of antibody concentration, one hyperbolic tangent variant is used as switching function in existed models. However, switching function with hyperbolic tangent contains four parameters, and does not always increase with antibody concentration. To address this problem, we proposed a monotonically increasing Logistical function variant as switching function, which only contains position parameter and magnitude parameter. Analysing influenza viral titre estimated from 21 focus reduction assay (FRA) datasets from neutralisation group (viral titre lower than negative control on all serial dilutions) and 20 FRA dataset from enhancement group (viral titre higher than negative control on high serial dilution), switching function with Logistic function performs better than existed model independent of both groups and exhibited different behaviour/character; specifically, magnitude parameter estimated from enhancement group is lower, but position parameter estimated from enhancement group is higher. A lower magnitude parameter refers that enhancement group more rapidly switches from enhancement to neutralisation with increase of antibody concentration, and a higher position parameter indicates that enhancement group provides a larger antibody concentration interval corresponding to enhancement. Integrating estimated neutralisation kinetics with viral replication, we demonstrated that antibody-induced bistable influenza kinetics exist independent of both groups. However, comparing with neutralisation group, enhancement group provides higher threshold value of antibody concentration corresponding to influenza infectivity. This explains the observed phenomenon that antibody dependent enhancement enhances susceptibility, severity, and mortality to influenza infection. On population level, antibody dependant enhancement can promote H1N1 and H3N2 influenza virus cooperate to sustain long-term circulation on human populations according to antigenic seniority theory.

同源抗体对流感感染增强作用的确定性模型
抗体依赖性增强是指与没有抗体时相比,病毒的感染性在抗体浓度较低时意外增强,如登革热、寨卡病毒和流感病毒。为了在数学上描述抗体浓度增加时病毒从增强到中和的过程,现有模型中使用了双曲正切变体作为切换函数。然而,双曲正切的切换函数包含四个参数,并不总是随抗体浓度的增加而增加。针对这一问题,我们提出了一种单调递增的 Logistical 函数变体作为切换函数,它只包含位置参数和幅度参数。通过分析中和组 21 个病灶缩小检测(FRA)数据集(所有序列稀释的病毒滴度均低于阴性对照)和增强组 20 个病灶缩小检测数据集(高序列稀释的病毒滴度高于阴性对照)估算的流感病毒滴度,Logistic 函数的切换函数比独立于两组的模型表现更好,并且表现出不同的行为/特征;具体来说,增强组估算的幅度参数较低,但增强组估算的位置参数较高。幅度参数越低,说明随着抗体浓度的增加,增强组更快地从增强转为中和,而位置参数越高,说明增强组提供的与增强相对应的抗体浓度间隔越大。将估计的中和动力学与病毒复制相结合,我们证明了抗体诱导的双稳态流感动力学与两个组别无关。然而,与中和组相比,增强组提供了与流感感染性相对应的更高的抗体浓度阈值。这就解释了所观察到的现象,即抗体依赖性增强提高了对流感感染的易感性、严重程度和死亡率。在人群层面,根据抗原资历理论,抗体依赖性增强可促进 H1N1 和 H3N2 流感病毒合作,在人群中长期流行。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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