Evidence map›Paper›PMID 24699432›Full record

ArticlePloS one2014

Influenza A H1N1 pandemic strain evolution--divergence and the potential for antigenic drift variants.

Eili Y Klein, Adrian W R Serohijos, Jeong-Mo Choi, Eugene I Shakhnovich, Andrew Pekosz

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Antigenic characterization of influenza and SARS-CoV-2 viruses.Analytical and bioanalytical chemistry · 2022
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Genetic divergence of Influenza A(H3N2) amino acid substitutions mark the beginning of the 2016-2017 winter season in Israel.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2017
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

5 authors.

Eili Y KleinCenter for Advanced Modeling in the Social, Behavioral, and Health Sciences, Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America; Center for Disease Dynamics, Economics, and Policy, Washington, DC, United States of America.
Adrian W R SerohijosDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Jeong-Mo ChoiDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Eugene I ShakhnovichDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.
Andrew PekoszW. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

Funding

Computational Models of Infectious Disease ThreatsU01GM070708 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BURKE, DONALD SCOTT · 2004 to 2008
$3.8M
Behavioral Epidemiology: Applications of Agent-Based Modeling to Infectious DiseaDP1OD003874 · OD · JOHNS HOPKINS UNIVERSITY · PI EPSTEIN, JOSHUA M. · 2008 to 2011
$2.8M
NIGMS NIH HHS U01 GM070708NIGMS NIH HHS U01GM070708NIH HHS DP1 OD003874NIH HHS DP1OD003874
6 · The paper itself

Abstract

The emergence of a novel A(H1N1) strain in 2009 was the first influenza pandemic of the genomic age, and unprecedented surveillance of the virus provides the opportunity to better understand the evolution of influenza. We examined changes in the nucleotide coding regions and the amino acid sequences of the hemagglutinin (HA), neuraminidase (NA), and nucleoprotein (NP) segments of the A(H1N1)pdm09 strain using publicly available data. We calculated the nucleotide and amino acid hamming distance from the vaccine strain A/California/07/2009 for each sequence. We also estimated Pepitope-a measure of antigenic diversity based on changes in the epitope regions-for each isolate. Finally, we compared our results to A(H3N2) strains collected over the same period. Our analysis found that the mean hamming distance for the HA protein of the A(H1N1)pdm09 strain increased from 3.6 (standard deviation [SD]: 1.3) in 2009 to 11.7 (SD: 1.0) in 2013, while the mean hamming distance in the coding region increased from 7.4 (SD: 2.2) in 2009 to 28.3 (SD: 2.1) in 2013. These trends are broadly similar to the rate of mutation in H3N2 over the same time period. However, in contrast to H3N2 strains, the rate of mutation accumulation has slowed in recent years. Our results are notable because, over the course of the study, mutation rates in H3N2 similar to that seen with A(H1N1)pdm09 led to the emergence of two antigenic drift variants. However, while there has been an H1N1 epidemic in North America this season, evidence to date indicates the vaccine is still effective, suggesting the epidemic is not due to the emergence of an antigenic drift variant. Our results suggest that more research is needed to understand how viral mutations are related to vaccine effectiveness so that future vaccine choices and development can be more predictive.

Indexed as

Biological EvolutionAntigens, ViralHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza, HumanUnited StatesAntigens, Viral

Identifiers

PMID24699432
PMCPMC3974778

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.