Evidence map›Paper›PMID 34492105›Full record

ReviewInternational immunology2021

Therapeutic immunoglobulin A antibody for dysbiosis-related diseases.

Reiko Shinkura

Open access · bronzeAbstract readReview
In one paragraph

Review in International immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

1 author at 1 institution in 1 country.

Reiko ShinkuraLaboratory of Immunology and Infection Control, Institute for Quantitative Biosciences, University of Tokyo, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.ORCID 0000-0002-7976-9933
Japan Agency for Medical Research and Development · JP

Funding

Japan Agency for Medical Research and Development JP17gm1010008h9904
6 · The paper itself

Abstract

Dysbiosis is alterations in the microbial composition compared with a healthy microbiota and often features a reduction in gut microbial diversity and a change in microbial taxa. Dysbiosis, especially in the gut, has also been proposed to play a crucial role in the pathogenesis of a wide variety of diseases, including inflammatory bowel disease, colorectal cancer, cardiovascular disease, obesity, diabetes and multiple sclerosis. A body of evidence has shown that intestinal polymeric immunoglobulin A (IgA) antibodies are important to regulate the gut microbiota as well as to exclude pathogenic bacteria or viral infection such as influenza and SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) at mucosal sites. Since the 1970s, trials for oral administration of therapeutic IgA or IgG have been performed mainly to treat infectious enteritis caused by pathogenic Escherichia coli or Clostridium difficile. However, few of them have been successfully developed for clinical application up to now. In addition to the protective function against intestinal pathogens, IgA is well known to modulate the gut commensal microbiota leading to symbiosis. Nevertheless, the development of therapeutic IgA drugs to treat dysbiosis is not progressing. In this review, the advantages of therapeutic IgA antibodies and the problems for their development will be discussed.

Indexed as

AnimalsBacteriaDysbiosisGastrointestinal MicrobiomeHost-Pathogen InteractionsHumansImmunoglobulin AImmunomodulating AgentsInflammatory Bowel DiseasesIntestinesSpecies SpecificityImmunoglobulin AImmunomodulating Agentspolymeric IgAgut microbiotaIgAmucosal immunity

Identifiers

PMID34492105
PMCPMC8499904
OpenAlexW3196322211

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.