Evidence map›Paper›PMID 29879226›Full record

SynthesisPloS one2018

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review.

Jerome Lacombe, Chao Sima, Sally A Amundson, Frederic Zenhausern

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

48 citing papers in PubMed, 98 citations in OpenAlex.

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  12. Modeling the Effects of Protracted Cosmic Radiation in a Human Organ-on-Chip Platform.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
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  19. Transcriptomics for radiation biodosimetry: progress and challenges.International journal of radiation biology · 2023
    Review
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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

4 authors at 4 institutions in 1 country.

Jerome LacombeCenter for Applied NanoBioscience and Medicine, University of Arizona, Phoenix, Arizona, United States of America.ORCID 0000-0003-0383-6332
Chao SimaCenter for Bioinformatics and Genomic Systems Engineering, Texas A&M Engineering Experiment Station, College Station, TX, United States of America.
Sally A AmundsonCenter for Radiological Research, Columbia University Medical Center, New York, NY, United States of America.
Frederic ZenhausernCenter for Applied NanoBioscience and Medicine, University of Arizona, Phoenix, Arizona, United States of America.
Columbia University Irving Medical Center · USTexas A&M Engineering Experiment StationTranslational Genomics Research Institute · USUniversity of Arizona · US

Funding

Sample Engineering CoreU19AI067773 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FORNACE, ALBERT J · 2005 to 2024
$105.4M
NIAID NIH HHS U19 AI067773
6 · The paper itself

Abstract

purposeTo compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry.

methodsEligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability.

results24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman's correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden's index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker.

conclusionGene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results.

Indexed as

Radiation, IonizingBiomarkersCarrier ProteinsGene Expression RegulationHumansNuclear ProteinsOX40 LigandRadiation InjuriesRadiometryRNA-Binding ProteinsBiomarkersCarrier ProteinsNuclear ProteinsOX40 LigandRNA-Binding ProteinsTNFSF4 protein, humanZMAT3 protein, human

Identifiers

PMID29879226
PMCPMC5991767
OpenAlexW2806560179

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.