Evidence map›Paper›PMID 36690876›Full record

ReviewImmunologic research2023

Human antibody profiling technologies for autoimmune disease.

Lauren H Carlton, Reuben McGregor, Nicole J Moreland

Open access · hybridAbstract readReview
In one paragraph

Review in Immunologic research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Peptide Epitopes of NC16A BP180 in the Diagnostics of Bullous Pemphigoid.JID innovations : skin science from molecules to population health · 2025
    Article
  7. Article
  8. Article
  9. PhIP-Seq: methods, applications and challenges.Frontiers in bioinformatics · 2024
    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 at 1 institution in 1 country.

Lauren H CarltonSchool of Medical Sciences, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand. l.carlton@auckland.ac.nz.ORCID 0000-0002-2665-805X
Reuben McGregorSchool of Medical Sciences, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.ORCID 0000-0003-0684-7635
Nicole J MorelandSchool of Medical Sciences, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand. n.moreland@auckland.ac.nz.ORCID 0000-0001-6548-637X
University of Auckland · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoimmune diseases are caused by the break-down in self-tolerance mechanisms and can result in the generation of autoantibodies specific to human antigens. Human autoantigen profiling technologies such as solid surface arrays and display technologies are powerful high-throughput technologies utilised to discover and map novel autoantigens associated with disease. This review compares human autoantigen profiling technologies including the application of these approaches in chronic and post-infectious autoimmune disease. Each technology has advantages and limitations that should be considered when designing new projects to profile autoantibodies. Recent studies that have utilised these technologies across a range of diseases have highlighted marked heterogeneity in autoantibody specificity between individuals as a frequent feature. This individual heterogeneity suggests that epitope spreading maybe an important mechanism in the pathogenesis of autoimmune disease in general and likely contributes to inflammatory tissue damage and symptoms. Studies focused on identifying autoantibody biomarkers for diagnosis should use targeted data analysis to identify the rarer public epitopes and antigens, common between individuals. Thus, utilisation of human autoantigen profiling technology, combined with different analysis approaches, can illuminate both pathogenesis and biomarker discovery.

Indexed as

Autoimmune DiseasesAutoantibodiesAutoantigensEpitopesHumansAutoantibodiesAutoantigensEpitopesAutoantigensAutoimmune diseaseBiomarker discoveryEpitope spreadingPhIP-SeqProtein array

Identifiers

PMID36690876
PMCPMC9870766
OpenAlexW4317788233

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.