Evidence map›Paper›PMID 28142321›Full record

ReviewAnnual review of immunology2017

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics.

Romain Banchereau, Alma-Martina Cepika, Jacques Banchereau, Virginia Pascual

Abstract readReview
In one paragraph

Review in Annual review of immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
3.8field-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

49 citing papers in PubMed, 97 citations in OpenAlex.

  1. Article
  2. A CD4Nature communications · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Materiobiology in the omics era.Materials today. Bio · 2025
    Review
  8. T-cell and autoantibody profiling for primary immune regulatory disorders.The Journal of allergy and clinical immunology · 2025
    Article
  9. Epitranscriptomic alterations induced by environmental toxins: implications for RNA modifications and disease.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2025
    Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
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

4 authors at 2 institutions in 1 country.

Romain BanchereauBaylor Institute for Immunology Research, Dallas, Texas 75204; email: romain.banchereau@bswhealth.org , almamartina.cepika@bswhealth.org , virginia.pascual@bswhealth.org.
Alma-Martina CepikaBaylor Institute for Immunology Research, Dallas, Texas 75204; email: romain.banchereau@bswhealth.org , almamartina.cepika@bswhealth.org , virginia.pascual@bswhealth.org.
Jacques BanchereauThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06030; email: jacques.banchereau@jax.org.
Virginia PascualBaylor Institute for Immunology Research, Dallas, Texas 75204; email: romain.banchereau@bswhealth.org , almamartina.cepika@bswhealth.org , virginia.pascual@bswhealth.org.
Baylor University · USJackson Laboratory · US

Funding

Vaccine Induced Activation of T Follicular Helper Cell SubsetsU19AI089987 · NIAID · BAYLOR RESEARCH INSTITUTE · PI PASCUAL, MARIA VIRGINIA · 2010 to 2015
$17.0M
Scientific CoreU19AI082715 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI PASCUAL, MARIA VIRGINIA · 2009 to 2018
$6.4M
Neutrophils in Lupus PathogenesisP50AR054083 · NIAMS · BAYLOR RESEARCH INSTITUTE · PI NUSSENZWEIG, MICHEL C · 2006 to 2010
$6.2M
NIAID NIH HHS U19 AI082715NIAID NIH HHS U19 AI089987NIAMS NIH HHS P50 AR054083
6 · The paper itself

Abstract

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Indexed as

TranscriptomeAutoimmune DiseasesDatasets as TopicHigh-Throughput Nucleotide SequencingHumansInflammationInformation Storage and RetrievalMolecular Targeted TherapyMonitoring, ImmunologicPrognosisautoimmunityautoinflammationmechanismspatient stratificationtherapeutic targetstranscriptomics

Identifiers

PMID28142321
PMCPMC5937945
OpenAlexW2526854172

What OpenQuestion holds

Textmetadata
LicenceTDM
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.