Evidence map›Paper›PMID 42711905›Full record

ReviewImmunological reviews2026

What Antibody Repertoires See: Structural and Immunogenetic Insights Into Influenza A Virus Hemagglutinin Recognition.

Bruno Bonnettaz, Goran Bajic

Abstract readReview
In one paragraph

Review in Immunological reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Bruno BonnettazDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID https://orcid.org/0009-0004-5355-1735
Goran BajicDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID https://orcid.org/0000-0003-0480-4324

Funding

Irma T. Hirschl Trust
6 · The paper itself

Abstract

Human infection with or vaccination against influenza A virus has been one of the most informative systems for understanding how human antibody repertoires recognize viral glycoproteins. Decades of antibody isolation, repertoire sequencing, lineage tracing, serology, viral antigenic evolution, and structural biology have shown that antibody recognition is not simply a matter of "which epitope is targeted." Instead, each surface on the viral hemagglutinin (HA) presents a distinct structural problem for the immune system. Repeated exposures through infection and vaccination coupled with continuous antigenic drift generate complex immune histories and reveal which viral surfaces evolve under antibody pressure. Structural studies have transformed the field by showing how antibody repertoires solve epitope-specific recognition problems. Some epitopes, such as the HA central stem, recruit highly stereotyped genetic and structural solutions. Others, such as the receptor-binding site, can be approached by genetically diverse antibodies that converge on common structural solutions of receptor mimicry. Additional epitopes, including the lateral patch, anchor, head interface, and head-stem junction, reveal intermediate patterns of repertoire constraint. Together, these examples show that what antibody repertoires "see" is determined by the interplay between viral glycoprotein structure, B cell precursor availability, somatic evolution, and population-level immunoglobulin diversity.

Indexed as

Antibodies, ViralHemagglutinin Glycoproteins, Influenza VirusInfluenza A virusInfluenza, HumanAnimalsEpitopesHumansProtein ConformationAntibodies, ViralEpitopesHemagglutinin Glycoproteins, Influenza Virusantibodyhemagglutinininfluenzarearrangementstructural convergence

Identifiers

PMID42711905
PMCPMC13554473

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.