Selecting vaccine strains for H3N2 human influenza A virus.
Selecting vaccine strains for H3N2 human influenza A virus.
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DOI：
10.1016/j.mgene.2015.03.003
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发表时间：
2015-06
期刊：
影响因子：
0.7
通讯作者：
Suzuki, Yoshiyuki
中科院分区：
文献类型：
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作者：
Suzuki, Yoshiyuki
H3 N2人类甲型流感病毒主要在温带地区的冬季引起流感流行。由于这种病毒的抗原性迅速演变，已经进行了几次尝试，以预测在接种疫苗的目标季节的血凝素1（HA 1）的主要氨基酸序列。然而，预测序列的有用性尚不清楚，因为其与抗原性的关系尚不清楚。在这里，用于估计HA 1氨基酸序列之间的抗原差异程度（抗原距离）的抗原模型被整合到H3 N2人甲型流感病毒疫苗株的选择过程中。当使用毒株与目标季节采样的流行病毒之间的平均抗原距离回顾性评价目标季节的潜在疫苗毒株的有效性时，最有效的疫苗毒株主要在目标季节前一年的季节（前目标季节）鉴定。实际疫苗的有效性似乎平均低于在目标季节前随机选择的菌株。建议在每个目标季节用与目标前季节的其他毒株平均抗原距离最小的毒株替换疫苗毒株。本研究中描述的为未来流行季节选择疫苗株的程序在流感病毒预测系统（NASDAQ）中实施（http：//www.nsc.nagoya-cu.ac.jp/NASDAQ yossuzuk/influcast.html）。
H3N2 human influenza A virus causes epidemics of influenza mainly in the winter season in temperate regions. Since the antigenicity of this virus evolves rapidly, several attempts have been made to predict the major amino acid sequence of hemagglutinin 1 (HA1) in the target season of vaccination. However, the usefulness of predicted sequence was unclear because its relationship to the antigenicity was unknown. Here the antigenic model for estimating the degree of antigenic difference (antigenic distance) between amino acid sequences of HA1 was integrated into the process of selecting vaccine strains for H3N2 human influenza A virus. When the effectiveness of a potential vaccine strain for a target season was evaluated retrospectively using the average antigenic distance between the strain and the epidemic viruses sampled in the target season, the most effective vaccine strain was identified mostly in the season one year before the target season (pre-target season). Effectiveness of actual vaccines appeared to be lower than that of the strains randomly chosen in the pre-target season on average. It was recommended to replace the vaccine strain for every target season with the strain having the smallest average antigenic distance to the others in the pre-target season. The procedure of selecting vaccine strains for future epidemic seasons described in the present study was implemented in the influenza virus forecasting system (INFLUCAST) (http://www.nsc.nagoya-cu.ac.jp/~yossuzuk/influcast.html).