Evidence map›Paper›PMID 34996462›Full record

SynthesisParticle and fibre toxicology2022

Exposure to silicates and systemic autoimmune-related outcomes in rodents: a systematic review.

Lisa M F Janssen, Manosij Ghosh, Frauke Lemaire, K Michael Pollard, Peter H M Hoet

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Particle and fibre toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 4% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Effect of Age on Xenobiotic-Induced Autoimmunity.bioRxiv : the preprint server for biology · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. 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

5 authors at 3 institutions in 2 countries.

Lisa M F JanssenLaboratory of Toxicology, Unit of Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
Manosij GhoshLaboratory of Toxicology, Unit of Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
Frauke LemaireLaboratory of Toxicology, Unit of Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
K Michael PollardDepartment of Molecular Medicine, Scripps Research, La Jolla, CA, 92037, USA.
Peter H M HoetLaboratory of Toxicology, Unit of Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium. peter.hoet@kuleuven.be.ORCID 0000-0002-0292-6603
KU Leuven · BEDepartment of Public Health · USScripps Institution of Oceanography · US

Funding

The Genetics of Silica-Induced AutoimmunityR01ES029581 · NIEHS · SCRIPPS RESEARCH INSTITUTE, THE · PI POLLARD, KENNETH MICHAEL · 2018 to 2022
$2.2M
Modeling xenobiotic-induced autoimmunity using Collaborative Cross strains.R21ES031454 · NIEHS · SCRIPPS RESEARCH INSTITUTE, THE · PI POLLARD, KENNETH MICHAEL · 2020 to 2021
$488k
NIEHS NIH HHS R01 ES029581NIEHS NIH HHS R21 ES031454
6 · The paper itself

Abstract

backgroundAutoimmunity can result from the interplay between genetic background and effects of environmental and/or occupational exposure to hazardous materials. Several compounds, including silica dust, have been linked with systemic autoimmunity and systemic autoimmune diseases, based on epidemiological evidence. For asbestos, a strong link with systemic autoimmune diseases does not yet exist, however, several studies have documented features of autoimmunity following asbestos exposure. Even so, human studies are limited in their ability to identify and examine isolated exposures, making it difficult to demonstrate causation or to assess pathogenic mechanisms. Therefore, this systematic review examines the existing animal evidence regarding autoimmunity and exposure to silicates (silica and asbestos).

methodsPubMed and EMBASE were systematically searched for peer-reviewed studies examining systemic autoimmune disease-related outcomes after silicate exposure in rodents. Literature databases were searched up to September 2021 for studies written in English and where the full text was available. Search strings were established based on a PECO (Population, Exposure, Comparator, Outcome) format. After title, abstract, and full-text screening, thirty-four studies were identified for further analysis. Quality assessment through ToxR tool and qualitative analysis of the results was performed.

resultsAlthough there was significant heterogeneity in the included studies in terms of exposure protocol and genetic background of the rodent models used, it was noted that both genetic background and exposure to silicates [(crystalline) silica and asbestos] are highly relevant to the development of (sub-) clinical systemic autoimmune disease.

conclusionParallels were observed between the findings from the animal (this review) and human (epidemiological) studies, arguing that experimental animal models are valuable tools for examining exacerbation or development of autoimmune disease after silicate exposure. However, genetic background and synergism between exposures should be considered in future studies.

Indexed as

Occupational ExposureRodentiaAnimalsAutoimmunityDustSilicatesDustSilicatesAsbestosAutoimmunityEnvironmental exposureImmune-mediated diseasesMiceOccupational exposureRatRodentsSilicaSystemic autoimmunea diseases

Identifiers

PMID34996462
PMCPMC8739508
OpenAlexW4205138572

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.