Evidence map›Paper›PMID 39833247›Full record

ReviewNPJ systems biology and applications2025

Immunopeptidomics for autoimmunity: unlocking the chamber of immune secrets.

Sanya Arshad, Benjamin Cameron, Alok V Joglekar

Abstract readReview
In one paragraph

Review in NPJ systems biology and applications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Methods for Isolating and Analyzing the HLA Class I Immunopeptidome.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  9. Review
  10. Review
  11. Machine learning approaches enable the discovery of therapeutics across domains.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  12. Review
  13. Article
  14. 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

3 authors.

Sanya Arshad *Department of Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
Benjamin Cameron *Department of Immunology, University of Pittsburgh, Pittsburgh, PA, USA.
Alok V JoglekarDepartment of Immunology, University of Pittsburgh, Pittsburgh, PA, USA. joglekar@pitt.edu.ORCID http://orcid.org/0000-0001-7554-7447

Funding

Unraveling microprotein biology with an evolutionary-immunological frameworkR01AT012826 · NCCIH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Alok Joglekar, Arvind Rasi Subramaniam · 2023 to 2026
$5.9M
Signaling via MHC: engineering immune cells with new capabilitiesDP2AI176138 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JOGLEKAR, ALOK · 2022 to 2025
$2.3M
NCCIH NIH HHS R01 AT012826NIAID NIH HHS DP2 AI176138U.S. Department of Health & Human Services | NIH | NIH Office of the Director (OD) 1DP2AI176138-01U.S. Department of Health & Human Services | NIH | NIH Office of the Director (OD) 1R01AT012826-01
6 · The paper itself

Abstract

T cells mediate pathogenesis of several autoimmune disorders by recognizing self-epitopes presented on Major Histocompatibility Complex (MHC) or Human Leukocyte Antigen (HLA) complex. The majority of autoantigens presented to T cells in various autoimmune disorders are not known, which has impeded autoantigen identification. Recent advances in immunopeptidomics have started to unravel the repertoire of antigenic epitopes presented on MHC. In several autoimmune diseases, immunopeptidomics has led to the identification of novel autoantigens and has enhanced our understanding of the mechanisms behind autoimmunity. Especially, immunopeptidomics has provided key evidence to explain the genetic risk posed by HLA alleles. In this review, we shed light on how immunopeptidomics can be leveraged to discover potential autoantigens. We highlight the application of immunopeptidomics in Type 1 Diabetes (T1D), Systemic Lupus Erythematosus (SLE), and Rheumatoid Arthritis (RA). Finally, we highlight the practical considerations of implementing immunopeptidomics successfully and the technical challenges that need to be addressed. Overall, this review will provide an important context for using immunopeptidomics for understanding autoimmunity.

Indexed as

Autoimmune DiseasesAutoimmunityAnimalsAutoantigensDiabetes Mellitus, Type 1EpitopesHLA AntigensHumansLupus Erythematosus, SystemicT-LymphocytesAutoantigensEpitopesHLA Antigens

Identifiers

PMID39833247
PMCPMC11747513

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.