Evidence map›Paper›PMID 24167296›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Immunosignatures can predict vaccine efficacy.

Joseph Barten Legutki, Stephen Albert Johnston

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

29 citing papers in PubMed, 52 citations in OpenAlex.

  1. Trial
  2. Immunoproteomics: The Evolution from Classical Methods to Emerging Techniques.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  3. Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025
    Article
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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

2 authors at 2 institutions in 1 country.

Joseph Barten LegutkiCenter for Innovations in Medicine, Biodesign Institute, Arizona State University, Tempe, AZ 85287.
Stephen Albert Johnston
Arizona State University · USCenter for Innovation · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of new vaccines would be greatly facilitated by having effective methods to predict vaccine performance. Such methods could also be helpful in monitoring individual vaccine responses to existing vaccines. We have developed "immunosignaturing" as a simple, comprehensive, chip-based method to display the antibody diversity in an individual on peptide arrays. Here we examined whether this technology could be used to develop correlates for predicting vaccine effectiveness. By using a mouse influenza infection, we show that the immunosignaturing of a natural infection can be used to discriminate a protective from nonprotective vaccine. Further, we demonstrate that an immunosignature can determine which mice receiving the same vaccine will survive. Finally, we show that the peptides comprising the correlate signatures of protection can be used to identify possible epitopes in the influenza virus proteome that are correlates of protection.

Indexed as

AnimalsDrug DiscoveryEpitopesFemaleImmunity, HumoralInfluenza A Virus, H1N1 SubtypeInfluenza VaccinesMiceMice, Inbred BALB CMicroarray AnalysisPeptidesPredictive Value of TestsEpitopesInfluenza VaccinesPeptidesantibody repertoireepitope predictionimmune profilepeptide microarraysystems vaccinology

Identifiers

PMID24167296
PMCPMC3831987
OpenAlexW1965934122

What OpenQuestion holds

Textmetadata
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.