Evidence map›Paper›PMID 42649420›Full record

ArticleImmunogenetics2026

Naïve adaptive immune receptor repertoires in celiac disease assessed by machine learning; impact of the HLA-DQ2.5 allotype on the TCR repertoire.

Aengus Officer, Ida Lindeman, Milena Pavlovic, Christin Lund-Andersen, Eivind Ness-Jensen, Geir Kjetil Sandve, Ludvig M Sollid

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In one paragraph

Article in Immunogenetics, 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

7 authors.

Aengus OfficerNorwegian Coeliac Disease Research Centre, University of Oslo, Oslo, Norway. aengus.officer@medisin.uio.no.ORCID https://orcid.org/0009-0006-6799-8751
Ida LindemanNorwegian Coeliac Disease Research Centre, University of Oslo, Oslo, Norway.
Milena PavlovicNorwegian Coeliac Disease Research Centre, University of Oslo, Oslo, Norway.
Christin Lund-AndersenDepartment of Tumor Biology, Institute for Cancer Research, Oslo University Hospital - The Norwegian Radium Hospital, Oslo, Norway.
Eivind Ness-JensenHUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway.
Geir Kjetil SandveNorwegian Coeliac Disease Research Centre, University of Oslo, Oslo, Norway.
Ludvig M SollidNorwegian Coeliac Disease Research Centre, University of Oslo, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adaptive immune receptor repertoire (AIRR) - the collection of an individual's B-cell and T-cell receptors (BCRs and TCRs, respectively) - encodes cumulative immune history and is shaped by both germline genetics and environmental exposures. Skewed repertoires have been linked to infections, vaccination responses and autoimmune diseases such as celiac disease (CeD) where biased usage of immunoglobulin and T-cell receptor genes reactive to disease relevant antigens has been reported. Motivated by evidence that germline variation, notably human leukocyte antigen (HLA), influences naïve AIRRs and by prior machine-learning studies that classified CeD using naïve BCR AIRR-sequencing (AIRR-seq) data, we applied machine learning analysis to naïve CD4

Indexed as

Adaptive ImmunityCeliac DiseaseHLA-DQ AntigensMachine LearningReceptors, Antigen, T-CellCD4-Positive T-LymphocytesFemaleHumansMaleReceptors, Antigen, B-CellHLA-DQ2 antigenHLA-DQ AntigensReceptors, Antigen, B-CellReceptors, Antigen, T-CellAIRRB-cell receptorsCeliac diseaseHLAMachine learningNaive repertoiresT-cell receptors

Identifiers

PMID42649420
PMCPMC13518406

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.