Evidence map›Paper›PMID 19349959›Full record

ArticleNature2009

Genetic analysis of radiation-induced changes in human gene expression.

Denis A Smirnov, Michael Morley, Eunice Shin, Richard S Spielman, Vivian G Cheung

Abstract read
In one paragraph

Article in Nature, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers.

0numbers the graph read from it
0cells of the map it votes in
122citing 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

122 citing papers in PubMed.

  1. Trial
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  8. Elevated Serum SERPINE2 Levels are Linked to Impaired Renal Function in Patients with Type 2 Diabetes Mellitus.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Article
  9. Article
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62 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.

Denis A SmirnovHoward Hughes Medical Institute, USA.
Michael Morley
Eunice Shin
Richard S Spielman
Vivian G Cheung

Funding

Genome-wide analysis of genetic variation and expression.R01GM081930 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI CHEUNG, VIVIAN G · 2007 to 2010
$3.2M
Genetics of individual variation in response to radiation exposureR01ES015733 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI CHEUNG, VIVIAN G · 2007 to 2011
$2.3M
Howard Hughes Medical InstituteNIEHS NIH HHS R01 ES015733NIGMS NIH HHS R01 GM081930
6 · The paper itself

Abstract

Humans are exposed to radiation through the environment and in medical settings. To deal with radiation-induced damage, cells mount complex responses that rely on changes in gene expression. These gene expression responses differ greatly between individuals and contribute to individual differences in response to radiation. Here we identify regulators that influence expression levels of radiation-responsive genes. We treated radiation-induced changes in gene expression as quantitative phenotypes, and conducted genetic linkage and association studies to map their regulators. For more than 1,200 of these phenotypes there was significant evidence of linkage to specific chromosomal regions. Nearly all of the regulators act in trans to influence the expression of their target genes; there are very few cis-acting regulators. Some of the trans-acting regulators are transcription factors, but others are genes that were not known to have a regulatory function in radiation response. These results have implications for our basic and clinical understanding of how human cells respond to radiation.

Indexed as

Gene Expression ProfilingToxicogeneticsAllelesB-LymphocytesCaspasesCell LineChromosomes, HumanGene Expression RegulationGene Knockdown TechniquesGenetic LinkageGenetic VariationGenome, HumanGenotypeHumansPhenotypePolymerase Chain ReactionCaspasesTranscription Factors

Identifiers

PMID19349959
PMCPMC3005325

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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.