Evidence map›Paper›PMID 26907721›Full record

ReviewNature reviews. Genetics2016

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system.

Maria Gutierrez-Arcelus, Stephen S Rich, Soumya Raychaudhuri

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 152 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
152citing papers in PubMed, 5 pooled it
–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

152 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Association ofFrontiers in immunology · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Review
  8. Article
  9. Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. HE4: a potential diagnostic biomarker in autoimmune diseases.Central-European journal of immunology · 2026
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review

92 more citing papers are in PubMed but not listed here.

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.

Maria Gutierrez-ArcelusDivision of Genetics, and Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
Stephen S RichCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA.
Soumya RaychaudhuriDivision of Genetics, and Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.

Funding

Metabolomics Core U19AI111224 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI MURRAY, MEGAN, MURRAY, MEGAN B · 2015 to 2021
$20.4M
Genetic predictors of response to anti-TNF therapy in rheumatoid arthritisU01GM092691 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI BRENNER, MICHAEL B., RAYCHAUDHURI, SOUMYA · 2010 to 2014
$7.5M
Discovery and Functional Impact of Common and Rare Variants in RAR01AR063759 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Soumya Raychaudhuri · 2013 to 2026
$5.4M
RA-SLE Molecular Deconstruction Leadership CenterUH2AR067677 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI BRENNER, MICHAEL B., RAYCHAUDHURI, SOUMYA · 2014 to 2020
$4.3M
Fine-mapping the MHC associations in rheumatoid arthritis from GWAS dataR01AR062886 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI RAYCHAUDHURI, SOUMYA · 2012 to 2013
$783k
NIAID NIH HHS U19 AI111224NIAID NIH HHS U19 AI111224‑01NIAMS NIH HHS 1R01AR063759NIAMS NIH HHS 1UH2AR067677‑01NIAMS NIH HHS R01 AR062886NIAMS NIH HHS R01 AR063759NIAMS NIH HHS UH2 AR067677NIGMS NIH HHS 5U01GM092691‑05NIGMS NIH HHS U01 GM092691
6 · The paper itself

Abstract

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

Indexed as

Genetic VariationGenomicsAllelesAutoimmune DiseasesAutoimmunityChromosome MappingEpigenesis, GeneticGenetic LociGenetic Predisposition to DiseaseHumansImmune SystemImmunophenotypingModels, MolecularPhenotypePrevalenceRisk

Identifiers

PMID26907721
PMCPMC4896831

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.