Evidence map›Paper›PMID 23564181›Full record

ReviewImmunologic research2013

Genetics and autoantibodies.

Carlo Perricone, Nancy Agmon-Levin, Fulvia Ceccarelli, Guido Valesini, Juan-Manuel Anaya, Yehuda Shoenfeld

Abstract readReview
PubMed Publisher
In one paragraph

Review in Immunologic research, 2013. 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. Severe COVID-19European respiratory review : an official journal of the European Respiratory Society · 2023
    Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Vaccines, adjuvants and autoimmunity.Pharmacological research · 2015
    Review
  9. Functional autoantibodies in systemic sclerosis.Seminars in immunopathology · 2015
    Review
  10. Review
  11. Article
  12. Systemic lupus erythematosus 2014.Autoimmune diseases · 2014
    Article
  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

6 authors.

Carlo PerriconeReumatologia, Dipartimento di Medicina Interna e Specialità Mediche, Sapienza Università di Roma, Rome, Italy.
Nancy Agmon-Levin
Fulvia Ceccarelli
Guido Valesini
Juan-Manuel Anaya
Yehuda Shoenfeld

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoimmune diseases (ADs) are chronic conditions initiated by the loss of immunological tolerance to self-antigens. The pathogenic hypothesis comprises a complex interaction between genetic, environmental and hormonal factors that interact with an individual over time generating a dysregulation of the immune system leading to disease development. Several polymorphic genes contribute to the development of ADs. Furthermore, age and gender play a major role by influencing hormone levels that can represent the fulcrum unbalancing from susceptibility to protection. Evidences suggest that while all these steps occur, the susceptible individual develops autoantibodies over a long time lapse. Such autoantibody production is genetically determined and finally, their presence seems to determine the clinical presentation of ADs. The genetic predisposition to the developments of autoantibodies and toward the disease process may overlap. The unveiling of these mechanisms could allow not only to treat but also to prevent the development of autoimmune diseases.

Indexed as

AnimalsAutoantibodiesAutoantigensAutoimmune DiseasesGene-Environment InteractionGenetic Predisposition to DiseaseHLA AntigensHomeostasisHormonesHumansPolymorphism, GeneticSelf ToleranceAutoantibodiesAutoantigensHLA AntigensHormones

Identifiers

What OpenQuestion holds

Textmetadata
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.