Evidence map›Paper›PMID 23122694›Full record

ReviewTrends in genetics : TIG2013

Genomic modulators of the immune response.

Julian C Knight

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Resolving trained immunity with systems biology.European journal of immunology · 2021
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Integration ofFrontiers in immunology · 2021
    Article
  12. Article
  13. Review
  14. Risk factors and disease mechanisms in myositis.Nature reviews. Rheumatology · 2018
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  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

1 author.

Julian C KnightWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, UK. julian@well.ox.ac.uk

Funding

European Research Council 281824Medical Research Council G1001708Wellcome Trust 074318Wellcome Trust 075491/Z/04Wellcome Trust 090532
6 · The paper itself

Abstract

Our understanding of immunity has historically been informed by studying heritable mutations in both the adaptive and innate immune responses, including primary immunodeficiency and autoimmune diseases. Recent advances achieved through the application of genomic and epigenomic approaches are reshaping the study of immune dysfunction and opening up new avenues for therapeutic interventions. Moreover, applying genomic techniques to resolve functionally important genetic variation between individuals is providing new insights into immune function in health. This review describes progress in the study of rare variants and primary immunodeficiency diseases arising from whole-exome sequencing (WES), and discusses the application, success, and challenges of applying genome-wide association studies (GWAS) to disorders of immune function and how they may inform more rational use of therapeutics. In addition, the application of expression quantitative-trait mapping to immune phenotypes, progress in understanding MHC disease associations, and insights into epigenetic mechanisms at the interface of immunity and the environment are reviewed.

Indexed as

EpigenomicsExomeGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenomicsHumansImmunityImmunologic Deficiency SyndromesSequence Analysis, DNA

Identifiers

PMID23122694
PMCPMC3605582

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.