Evidence map›Paper›PMID 41652567›Full record

ArticleBMC genomics2026

Evolutionary patterns of pH1N1 and H3N2 in relation to vaccine use.

Yi-Wen Lin, Li-Zhong Guo, Yun-Ting Tsai, Yi-Chieh Chu, Yu-Fang Lin, Kazuhiro Takemura, Chung-Hao Huang, Hsiao-Han Chang, Cheng-Sheng Lee

Abstract read
In one paragraph

Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yi-Wen Lin *Institute of Molecular and Cellular Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Li-Zhong Guo *Institute of Molecular and Cellular Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Yun-Ting Tsai *Institute of Bioinformatics and Structural Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Yi-Chieh ChuInstitute of Bioinformatics and Structural Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Yu-Fang LinInstitute of Molecular and Cellular Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Kazuhiro TakemuraInstitute of Bioinformatics and Structural Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan.
Chung-Hao HuangDivision of Infectious Disease, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Hsiao-Han ChangInstitute of Molecular and Cellular Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan. hhchang@life.nthu.edu.tw.
Cheng-Sheng LeeInstitute of Molecular and Cellular Biology, College of Life Sciences and Medicine, National Tsing-Hua University, Hsinchu, Taiwan. cslee@life.nthu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid evolution of viral antigens poses a major challenge to infectious disease control, particularly for pathogens like influenza that undergo frequent antigenic changes. While deep mutational scanning and platforms such as Nextstrain have advanced our understanding of mutation effects and population-level viral dynamics, they often rely on strain-level analyses that may overlook key within-strain antigenic changes. In this study, we adopted a site-based approach to systematically identify and analyze hemagglutinin (HA) mutations in influenza viruses that differed from vaccine strains, using publicly available genomic data. We found that nonsynonymous mutations exhibiting vaccine-associated allele frequency changes were significantly enriched in epitope regions in both pH1N1 and H3N2, and that pH1N1 showed a higher proportion of rapid allele-replacement events occurring within a single influenza season, whereas H3N2 substitutions more often occurred across multiple seasons. Geographically, several mutations displayed allele frequency changes correlated with local vaccination coverage. Phylogenetic analyses further revealed that five nonsynonymous mutations in H3N2 arose independently across multiple clades. Serological assays confirmed reduced neutralization for multiple pH1N1 mutations, and computational protein stability analyses indicated that observed mutations tended to increase protein stability in both subtypes, and that in pH1N1, potential epitope mutations were more stabilizing than those in non-epitope regions. By integrating bioinformatics with experimental validation, our approach provides a refined understanding of how selective pressures shape antigenic evolution at the site level, which could aid future studies on vaccine effectiveness and epidemic trends.

Indexed as

Evolution, MolecularInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza VaccinesEpitopesGene FrequencyHemagglutinin Glycoproteins, Influenza VirusHumansInfluenza, HumanMutationPhylogenyProtein StabilityEpitopesHemagglutinin Glycoproteins, Influenza VirusInfluenza VaccinesInfluenza virusProtein stabilitySite-based approach

Identifiers

PMID41652567
PMCPMC12973873

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.