Evidence map›Paper›PMID 35217808›Full record

ReviewJournal of exposure science & environmental epidemiology2022

Approaches to incorporate extracellular vesicles into exposure science, toxicology, and public health research.

Celeste K Carberry, Deepak Keshava, Alexis Payton, Gregory J Smith, Julia E Rager

Abstract readReview
In one paragraph

Review in Journal of exposure science & environmental epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. From Hypoxia to Bone: Reprogramming the Prostate Cancer Metastatic Cascade.International journal of molecular sciences · 2025
    Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. 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

5 authors.

Celeste K CarberryDepartment of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Deepak KeshavaThe Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Alexis PaytonDepartment of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Gregory J SmithCurriculum in Toxicology and Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Julia E RagerDepartment of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jrager@unc.edu.

Funding

UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel · 2001 to 2026
$36.3M
The UNC Chapel Hill Superfund Research Program (UNC-SRP)P42ES031007 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Rebecca Fry · 2020 to 2026
$22.2M
Integrative chemical-biological profiling to determine primary drivers of wildfire smoke-induced toxicityR21ES031740 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JASPERS, ILONA, RAGER, JULIA · 2020 to 2021
$418k
NIEHS NIH HHS P30 ES010126NIEHS NIH HHS P42 ES031007NIEHS NIH HHS R21 ES031740
6 · The paper itself

Abstract

Extracellular vesicles (EVs) represent small, membrane-enclosed particles that are derived from parent cells and are secreted into the extracellular space. Once secreted, EVs can then travel and communicate with nearby or distant cells. Due to their inherent stability and biocompatibility, these particles can effectively transfer RNAs, proteins, and chemicals/metabolites from parent cells to target cells, impacting cellular and pathological processes. EVs have been shown to respond to disease-causing agents and impact target cells. Given that disease-causing agents span environmental contaminants, pathogens, social stressors, drugs, and other agents, the translation of EV methods into public health is now a critical research gap. This paper reviews approaches to translate EVs into exposure science, toxicology, and public health applications, highlighting blood as an example due to its common use within clinical, epidemiological, and toxicological studies. Approaches are reviewed surrounding the isolation and characterization of EVs and molecular markers that can be used to inform EV cell-of-origin. Molecular cargo contained within EVs are then discussed, including an original analysis of blood EV data from Vesiclepedia. Methods to evaluate functional consequences and target tissues of EVs are also reviewed. Lastly, the expanded integration of these approaches into future public health applications is discussed, including the use of EVs as promising biomarkers of exposure, effect, and disease. IMPACT STATEMENT: Extracellular vesicles (EVs) represent small, cell-derived structures consisting of molecules that can serve as biomarkers of exposure, effect, and disease. This review lays a novel foundation for integrating EVs, a rapidly advancing molecular biological tool, into the field of public health research including epidemiological, toxicological, and clinical investigations. This article represents an important advancement in public health and exposure science as it is among the first to translate EVs into this field.

Indexed as

Extracellular VesiclesPublic HealthBiomarkersHumansBiomarkersHealth Studies, Epidemiology, Exposomics, New Approach Methodologies (NAMs), Biomonitoring

Identifiers

PMID35217808
PMCPMC9402811

What OpenQuestion holds

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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.