Evidence map›Paper›PMID 41311460›Full record

ArticleImmunoinformatics (Amsterdam, Netherlands)2025

Is the vaccination-induced B cell receptor repertoire predictable?

Eve Richardson, Lisa Willemsen, Pramod Shinde, Morten Nielsen, Bjoern Peters

Abstract read
In one paragraph

Article in Immunoinformatics (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026
    Article
  2. AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026
    Review
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.

Eve RichardsonLa Jolla Institute for Immunology, San Diego, CA, United States.
Lisa WillemsenLa Jolla Institute for Immunology, San Diego, CA, United States.
Pramod ShindeLa Jolla Institute for Immunology, San Diego, CA, United States.
Morten NielsenDepartment of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark.
Bjoern PetersLa Jolla Institute for Immunology, San Diego, CA, United States.

Funding

IMMUNE EPITOPE AND ANALYSIS PROGRAM: Transplantation of organs, tissues and cells 75N93019C00001 · NIAID · LA JOLLA INSTITUTE FOR IMMUNOLOGY · PI WILSON, STEPHEN · 2019 to 2025
$23.1M
Developing computational models to predict the immune response to B. pertussis booster vaccinationU01AI150753 · NIAID · LA JOLLA INSTITUTE FOR IMMUNOLOGY · PI PETERS, BJOERN · 2020 to 2024
$7.1M
NIAID NIH HHS 75N93019C00001NIAID NIH HHS U01 AI150753
6 · The paper itself

Abstract

Vaccines trigger an immune response that results in a population of memory cells that can quickly respond to subsequent antigen re-encounters. Most vaccines are designed to induce memory B cells with vaccine-specific B cell receptors (BCRs). Post-vaccination, clonal expansion of B cells results in measurably expanded vaccine-specific BCR clonotypes. We set out to determine to what extent it is predictable which specific BCR clonotypes are vaccine-induced in an individual. We sequenced the BCR heavy chain repertoire in a cohort of 19 individuals prior- and 7 days post Tdap booster vaccination. We tested two modalities to predict which clonotypes were expanded post-vaccination: first, we utilized a small database of monoclonal antibodies with known specificity to Tdap vaccine antigens and tested various sequence look-up methods, identifying clonal look-up as the best method. We then utilized a leave-one-out approach in which expanded clonotypes in one individual were predicted using data from other members of the cohort. The second approach significantly outperformed the first, indicating that BCR clonotype expansion can be learned across subjects. These results support the utility of systematically collecting BCR specificity data through efforts like the Immune Epitope database and highlight the limitations on general prediction approaches resulting from relatively small dataset sizes for BCRs with known specificities. Additionally, our study provides 1) a comparison of several BCR specificity prediction methods, 2) a dataset that can be used for benchmarking of subsequent methods, and 3) a methodological framework for comparing BCR repertoires pre- and post-vaccination.

Identifiers

PMID41311460
PMCPMC12657037

What OpenQuestion holds

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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.