抗原漂移和亚型干扰形状A ((H3N2) 在美国的流行病动态
Amanda C Perofsky1,2, John Huddleston3, Chelsea Hansen1,2
1Fogarty International Center, National Institutes of Health, United States.
medRxiv : the preprint server for health sciences
|October 24, 2023
概括
根据表面蛋白质血凝素 (HA) 和神经氨基酶 (NA) 的遗传距离来衡量流感A(H3N2) 病毒的演变,可以预测流行病的规模和强度. 流感A ((H1N1) 的亚型干扰也对A ((H3N2) 流行病产生了重大影响.
科学领域:
- 病毒学 病毒学
- 流行病学 流行病学
- 进化生物学 进化生物学
背景情况:
- 流感病毒通过血液凝聚素 (HA) 和神经氨基酶 (NA) 表面蛋白的突变不断演变新的抗原变体.
- 抗原漂移有助于再感染和年度流行病变化,但其确切影响尚不清楚.
研究的目的:
- 为了将流感A ((H3N2) 病毒的演变与1997-2019年美国地区流行病动态联系起来.
- 为了确定流感A(H3N2) 爆发的关键进化和流行病学预测因素.
主要方法:
- 综合表型HA抗原漂移测量与基于序列的HA和NA适应性数据.
- 季节性流感病毒之间的抗原和遗传距离的推断.
- 疫情规模,严重程度,时间,传播率,年龄特定模式和亚型主导性的估计.
- 应用随机森林模型来评估病毒演变和亚型干扰.
主要成果:
- 遗传距离,特别是跨HA和NA表位点的遗传距离,强烈预测流感A (H3N2) 流行病学.
- 增加季节性表位距离与更大,更强烈的流行病,更高的传播率和更大的A ((H3N2) 主导度相关.
- 流感A ((H1N1) 发病率对A ((H3N2) 流行病的影响比病毒演变更大,这表明亚型通过交叉免疫进行干扰.
结论:
- 流感A ((H3N2) 病毒的演变,特别是HA和NA的抗原漂移,是流行病变化的主要驱动因素.
- 亚型干扰,可能通过异型亚型交叉免疫,在流感A病毒动态中起着重要作用.
相关概念视频
Viral Recombination
23.5K
Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
23.5K
Viral Mutations
32.4K
A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
32.4K
Genetic Drift
39.8K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
39.8K
Mutation, Gene Flow, and Genetic Drift
58.5K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
58.5K
Steps in Outbreak Investigation
135
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
135


