Evidence map›Paper›PMID 35551477›Full record

ArticleInternational archives of occupational and environmental health2022

Realistic biomarkers from plasma extracellular vesicles for detection of beryllium exposure.

Raju S R Adduri, Ravikiran Vasireddy, Margaret M Mroz, Anisha Bhakta, Yang Li, Zhe Chen, Jeffrey W Miller, Karen Y Velasco-Alzate, Vanathi Gopalakrishnan, Lisa A Maier and 2 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International archives of occupational and environmental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Metabolomics and proteomics in occupational medicine: a comprehensive systematic review.Journal of occupational medicine and toxicology (London, England) · 2024
    Review
  2. Review
  3. Article
  4. 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

12 authors at 5 institutions in 1 country.

Raju S R AdduriDepartment of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA.
Ravikiran VasireddyDepartment of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA.
Margaret M MrozDepartment of Medicine, National Jewish Health, Denver, CO, USA.
Anisha BhaktaDepartment of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA.
Yang LiDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Zhe ChenDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Jeffrey W MillerDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Karen Y Velasco-AlzateDepartment of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA.
Vanathi GopalakrishnanDepartment of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Lisa A MaierDepartment of Medicine, National Jewish Health, Denver, CO, USA.
Li LiDepartment of Medicine, National Jewish Health, Denver, CO, USA.
Nagarjun V KonduruDepartment of Cellular and Molecular Biology, University of Texas Health Science Center at Tyler, Tyler, TX, TX75708, USA. Nagarjun.KonduruVenkata@uthct.edu.ORCID 0000-0001-6709-7511
The University of Texas Health Science Center at Tyler · USNational Jewish Health · USThe University of Texas Southwestern Medical Center · USHarvard University · USUniversity of Pittsburgh · US

Funding

Colorado Clinical and Translational Sciences InstituteUL1TR001082 · NCATS · UNIVERSITY OF COLORADO DENVER · PI SOKOL, RONALD J. · 2013 to 2017
$48.0M
T Cells in Beryllium Sensitization and DiseaseP01ES011810 · NIEHS · UNIVERSITY OF COLORADO DENVER · PI FONTENOT, ANDREW P. · 2002 to 2013
$14.0M
Exposure in Epigenetic Regulation of Immune Response in CBDR01ES023826 · NIEHS · NATIONAL JEWISH HEALTH · PI MAIER, LISA A, YANG, IVANA V · 2015 to 2019
$2.3M
The immunoregulatory role of Alveolar Macrophages in Chronic Beryllium DiseaseR01ES025722 · NIEHS · NATIONAL JEWISH HEALTH · PI LI, LI · 2016 to 2020
$1.8M
Lipoprotein Corona Fingerprints: Implications for Pulmonary Clearance and Toxicity of Engineered NanoparticlesR00ES025813 · NIEHS · UNIVERSITY OF TEXAS HLTH CTR AT TYLER · PI KONDURU VENKATA, NAGARJUN · 2019 to 2021
$747k
Functional Genomics Approach to the Role of the JAK/STAT and MAPK Pathway in CBDK01ES020857 · NIEHS · UNIVERSITY OF COLORADO DENVER · PI LI, LI · 2011 to 2013
$382k
NCATS NIH HHS UL1 TR001082NIEHS NIH HHS K01 ES020857NIEHS NIH HHS P01 ES011810NIEHS NIH HHS R00 ES025813NIEHS NIH HHS R01 ES023826NIEHS NIH HHS R01 ES025722
6 · The paper itself

Abstract

purposeExposures related to beryllium (Be) are an enduring concern among workers in the nuclear weapons and other high-tech industries, calling for regular and rigorous biological monitoring. Conventional biomonitoring of Be in urine is not informative of cumulative exposure nor health outcomes. Biomarkers of exposure to Be based on non-invasive biomonitoring could help refine disease risk assessment. In a cohort of workers with Be exposure, we employed blood plasma extracellular vesicles (EVs) to discover novel biomarkers of exposure to Be.

methodsEVs were isolated from plasma using size-exclusion chromatography and subjected to mass spectrometry-based proteomics. A protein-based classifier was developed using LASSO regression and validated by ELISA.

resultsWe discovered a dual biomarker signature comprising zymogen granule protein 16B and putative protein FAM10A4 that differentiated between Be-exposed and -unexposed subjects. ELISA-based quantification of the biomarkers in an independent cohort of samples confirmed higher expression of the signature in the Be-exposed group, displaying high predictive accuracy (AUROC = 0.919). Furthermore, the biomarkers efficiently discriminated high- and low-exposure groups (AUROC = 0.749).

conclusionsThis is the first report of EV biomarkers associated with Be exposure and exposure levels. The biomarkers could be implemented in resource-limited settings for Be exposure assessment.

Indexed as

BerylliumExtracellular VesiclesBiomarkersHumansMass SpectrometryProteomicsBerylliumBiomarkersBerylliumBiomarkerBiomonitoringExposure assessmentExtracellular vesicles

Identifiers

PMID35551477
PMCPMC9489591
OpenAlexW4280553948

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.