Evidence map›Paper›PMID 25963628›Full record

ArticleBMC medical genomics2015

Radiation dose-rate effects on gene expression for human biodosimetry.

Shanaz A Ghandhi, Lubomir B Smilenov, Carl D Elliston, Mashkura Chowdhury, Sally A Amundson

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 1 pooled it
8.7field-weighted citation impact, top 2% 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

62 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Secondary Neoplasms After Hematopoietic Cell Transplant for Sickle Cell Disease.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
    Article
  9. Review
  10. Review
  11. The NIAID/RNCP Biodosimetry Program: An Overview.Cytogenetic and genome research · 2023
    Review
  12. Article
  13. Article
  14. Transcriptomics for radiation biodosimetry: progress and challenges.International journal of radiation biology · 2023
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

2 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Shanaz A GhandhiCenter for Radiological Research, Columbia University, VC11-237, 630 West 168th Street, New York, NY, 10032, USA. sg2423@cumc.columbia.edu.
Lubomir B SmilenovCenter for Radiological Research, Columbia University, VC11-237, 630 West 168th Street, New York, NY, 10032, USA. lbs5@cumc.columbia.edu.
Carl D EllistonCenter for Radiological Research, Columbia University, VC11-237, 630 West 168th Street, New York, NY, 10032, USA. CElliston@maimonidesmed.org.
Mashkura ChowdhuryCenter for Radiological Research, Columbia University, VC11-237, 630 West 168th Street, New York, NY, 10032, USA. mc3102@columbia.edu.
Sally A AmundsonCenter for Radiological Research, Columbia University, VC11-237, 630 West 168th Street, New York, NY, 10032, USA. saa2108@cumc.columbia.edu.
Columbia University · US

Funding

Sample Engineering CoreU19AI067773 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FORNACE, ALBERT J · 2005 to 2024
$105.4M
NIAID NIH HHS U19 AI067773NIAID NIH HHS U19AI067773
6 · The paper itself

Abstract

backgroundThe effects of dose-rate and its implications on radiation biodosimetry methods are not well studied in the context of large-scale radiological scenarios. There are significant health risks to individuals exposed to an acute dose, but a realistic scenario would include exposure to both high and low dose-rates, from both external and internal radioactivity. It is important therefore, to understand the biological response to prolonged exposure; and further, discover biomarkers that can be used to estimate damage from low-dose rate exposures and propose appropriate clinical treatment.

methodsWe irradiated human whole blood ex vivo to three doses, 0.56 Gy, 2.23 Gy and 4.45 Gy, using two dose rates: acute, 1.03 Gy/min and a low dose-rate, 3.1 mGy/min. After 24 h, we isolated RNA from blood cells and these were hybridized to Agilent Whole Human genome microarrays. We validated the microarray results using qRT-PCR.

resultsMicroarray results showed that there were 454 significantly differentially expressed genes after prolonged exposure to all doses. After acute exposure, 598 genes were differentially expressed in response to all doses. Gene ontology terms enriched in both sets of genes were related to immune processes and B-cell mediated immunity. Genes responding to acute exposure were also enriched in functions related to natural killer cell activation and cell-to-cell signaling. As expected, the p53 pathway was found to be significantly enriched at all doses and by both dose-rates of radiation. A support vectors machine classifier was able to distinguish between dose-rates with 100 % accuracy using leave-one-out cross-validation.

conclusionsIn this study we found that low dose-rate exposure can result in distinctive gene expression patterns compared with acute exposures. We were able to successfully distinguish low dose-rate exposed samples from acute dose exposed samples at 24 h, using a gene expression-based classifier. These genes are candidates for further testing as markers to classify exposure based on dose-rate.

Indexed as

AdultBloodDose-Response Relationship, RadiationFemaleHumansMaleMiddle AgedOligonucleotide Array Sequence AnalysisRadiometryReproducibility of ResultsTranscriptome

Identifiers

PMID25963628
PMCPMC4472181
OpenAlexW2101839601

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.