The Ongoing Epidemics of Seasonal Influenza A(H3N2) in Hangzhou, China, and Its Viral Genetic Diversity

This study examined the genetic and evolutionary features of influenza A/H3N2 viruses in Hangzhou (2010-2022) by analyzing 28,651 influenza-like illness samples from two sentinel hospitals. Influenza A/H3N2 coexisted with other subtypes, dominating seasonal peaks (notably summer). Whole-genome sequencing of 367 strains was performed on GridION platforms. Phylogenetic analysis showed they fell into 16 genetic groups, with multiple clades circulating simultaneously. Shannon entropy indicated HA, NA, and NS gene segments exhibited significantly higher variability than other genomic segments, with HA glycoprotein mutations concentrated in antigenic epitopes A-E. Antiviral resistance showed no inhibitor resistance mutations in PA, PB1, or PB2, but NA mutations were detected in some strains, and most strains harbored M2 mutations. A Bayesian molecular clock showed the HA segment exhibited the highest nucleotide substitution rate (3.96 × 10<sup>-3</sup> substitutions/site/year), followed by NA (3.77 × 10<sup>-3</sup>) and NS (3.65 × 10<sup>-3</sup>). Selective pressure showed A/H3N2 strains were predominantly under purifying selection, with only sporadic positive selection at specific sites. The Pepitope model demonstrated that antigenic epitope mismatches between circulating H3N2 variants and vaccine strains led to a significant decline in influenza vaccine effectiveness (VE), particularly in 2022. Overall, the study underscores the complex circulation patterns of influenza in Hangzhou and the global importance of timely vaccine strain updates.

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Publication Details

Journal
Viruses
Published
2025-04-04
DOI
https://doi.org/10.3390/v17040526
Citations
3
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
4.06

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article

The Ongoing Epidemics of Seasonal Influenza A(H3N2) in Hangzhou, China, and Its Viral Genetic Diversity

Xiaofeng Qiu, Lijiao Ao, Feifei Cao, Xuhui Yang et al.
3 citations
Viruses
Influenza Virus Research Studies
4.06
article

The Ongoing Epidemics of Seasonal Influenza A(H3N2) in Hangzhou, China, and Its Viral Genetic Diversity

Xiaofeng Qiu, Lijiao Ao, Feifei Cao, Xuhui Yang, Zhou Sun, Yinyan Zhou, Xinfen Yu, Yue Yu, Xueling Zheng, Jun Li, Shi Cheng
article en
3 citations

Abstract

This study examined the genetic and evolutionary features of influenza A/H3N2 viruses in Hangzhou (2010-2022) by analyzing 28,651 influenza-like illness samples from two sentinel hospitals. Influenza A/H3N2 coexisted with other subtypes, dominating seasonal peaks (notably summer). Whole-genome sequencing of 367 strains was performed on GridION platforms. Phylogenetic analysis showed they fell into 16 genetic groups, with multiple clades circulating simultaneously. Shannon entropy indicated HA, NA, and NS gene segments exhibited significantly higher variability than other genomic segments, with HA glycoprotein mutations concentrated in antigenic epitopes A-E. Antiviral resistance showed no inhibitor resistance mutations in PA, PB1, or PB2, but NA mutations were detected in some strains, and most strains harbored M2 mutations. A Bayesian molecular clock showed the HA segment exhibited the highest nucleotide substitution rate (3.96 × 10<sup>-3</sup> substitutions/site/year), followed by NA (3.77 × 10<sup>-3</sup>) and NS (3.65 × 10<sup>-3</sup>). Selective pressure showed A/H3N2 strains were predominantly under purifying selection, with only sporadic positive selection at specific sites. The Pepitope model demonstrated that antigenic epitope mismatches between circulating H3N2 variants and vaccine strains led to a significant decline in influenza vaccine effectiveness (VE), particularly in 2022. Overall, the study underscores the complex circulation patterns of influenza in Hangzhou and the global importance of timely vaccine strain updates.

VirusesVol. 17(4)
Hangzhou Center for Disease Control and Prevention (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 7%
Influenza Virus Research Studies
4.06
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