Browse
Submit Data
Databases
API
Help

Dataset Information

23 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gene expression signatures that predict radiation exposure in mice and humans.

ABSTRACT:

Background

The capacity to assess environmental inputs to biological phenotypes is limited by methods that can accurately and quantitatively measure these contributions. One such example can be seen in the context of exposure to ionizing radiation.

Methods and findings

We have made use of gene expression analysis of peripheral blood (PB) mononuclear cells to develop expression profiles that accurately reflect prior radiation exposure. We demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1,000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from nonirradiated samples with an accuracy of 90%, sensitivity of 85%, and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and nonirradiated human patients with an accuracy of 77%, sensitivity of 82%, and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated that are highly predictive of different levels of radiation exposure in mice and humans.

Conclusions

We suggest that this approach, with additional refinement, could provide a method to assess the effects of various environmental inputs into biological phenotypes as well as providing a more practical application of a rapid molecular screening test for the diagnosis of radiation exposure.

SUBMITTER: Dressman HK

PROVIDER: S-EPMC1845155 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Gene expression signatures that predict radiation exposure

Project description:This SuperSeries is composed of the SubSeries listed below.

2007-03-01 | GSE6874 | GEO

Gene expression signatures that predict radiation exposure

Project description:This SuperSeries is composed of the following subset Series: GSE6871: Gene expression signatures that predict radiation exposure (human) GSE6873: Gene expression signatures that predict radiation exposure (mouse) Keywords: SuperSeries Refer to individual Series

2010-06-12 | E-GEOD-6874 | biostudies-arrayexpress

Gene expression signatures that predict radiation exposure (mouse)

2007-03-01 | GSE6873 | GEO

Gene expression signatures that predict radiation exposure (human)

2007-03-01 | GSE6871 | GEO

Gene expression signatures that predict radiation exposure (mouse)

Project description:Gene expression analysis of peripheral blood leukocytes (PB MNCs) to develop expression profiles that accurately reflect prior radiation exposure. Keywords: Comparative, exposure dosage, C57BI6 Murine Irradiation Studies We have made use of gene expression analysis of peripheral blood mononuclear cells (PB MNCs) to develop expression profiles that accurately reflect prior radiation exposure. Importantly, we demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from non-irradiated samples with an accuracy of 90%, sensitivity of 85% and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and non-irradiated human patients with an accuracy of 77%, sensitivity of 82% and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated which are highly predictive of different levels of radiation exposure in mice and humans. Mouse Dataset only

2010-06-11 | E-GEOD-6873 | biostudies-arrayexpress

Blood gene expression signatures predict exposure levels.

Project description:To respond to potential adverse exposures properly, health care providers need accurate indicators of exposure levels. The indicators are particularly important in the case of acetaminophen (APAP) intoxication, the leading cause of liver failure in the U.S. We hypothesized that gene expression patterns derived from blood cells would provide useful indicators of acute exposure levels. To test this hypothesis, we used a blood gene expression data set from rats exposed to APAP to train classifiers in two prediction algorithms and to extract patterns for prediction using a profiling algorithm. Prediction accuracy was tested on a blinded, independent rat blood test data set and ranged from 88.9% to 95.8%. Genomic markers outperformed predictions based on traditional clinical parameters. The expression profiles of the predictor genes from the patterns extracted from the blood exhibited remarkable (97% accuracy) transtissue APAP exposure prediction when liver gene expression data were used as a test set. Analysis of human samples revealed separation of APAP-intoxicated patients from control individuals based on blood expression levels of human orthologs of the rat discriminatory genes. The major biological signal in the discriminating genes was activation of an inflammatory response after exposure to toxic doses of APAP. These results support the hypothesis that gene expression data from peripheral blood cells can provide valuable information about exposure levels, well before liver damage is detected by classical parameters. It also supports the potential use of genomic markers in the blood as surrogates for clinical markers of potential acute liver damage.

| S-EPMC2084322 | biostudies-literature

Blood RNA signatures predict recent tuberculosis exposure in mice, macaques and humans.

Project description:Tuberculosis (TB) is the leading cause of death due to a single infectious disease. Knowing when a person was infected with Mycobacterium tuberculosis (M.tb) is critical as recent infection is the strongest clinical risk factor for progression to TB disease in immunocompetent individuals. However, time since M.tb infection is challenging to determine in routine clinical practice. To define a biomarker for recent TB exposure, we determined whether gene expression patterns in blood RNA correlated with time since M.tb infection or exposure. First, we found RNA signatures that accurately discriminated early and late time periods after experimental infection in mice and cynomolgus macaques. Next, we found a 6-gene blood RNA signature that identified recently exposed individuals in two independent human cohorts, including adult household contacts of TB cases and adolescents who recently acquired M.tb infection. Our work supports the need for future longitudinal studies of recent TB contacts to determine whether biomarkers of recent infection can provide prognostic information of TB disease risk in individuals and help map recent transmission in communities.

| S-EPMC7547102 | biostudies-literature

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans.

Project description:Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures.We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively.We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

| S-EPMC2271127 | biostudies-literature

Specific, Durable and Accurate Gene Expression Signatures of Radiation Response in Mice and Humans

2008-11-29 | GSE10640 | GEO

Gene expression signatures of radiation exposure in peripheral white blood cells of smokers and non-smokers.

Project description:PurposeThe issue of potential confounding factors is critical to the development of any approach to radiation biodosimetry, and has not been fully addressed for gene expression-based approaches.Materials and methodsAs a step in this direction, we have investigated the effect of smoking on the global radiation gene expression response in ex vivo-irradiated peripheral blood cells using microarray analysis. We also evaluated the ability of gene expression signatures to predict the radiation exposure level of ex vivo-exposed samples from smokers and non-smokers of both genders.ResultsWe identified eight genes with a radiation response that was significantly affected by smoking status, and confirmed an effect of smoking on the radiation response of the four and a half LIM domains 2 (FHL2) gene using quantitative real-time polymerase chain reaction. The performance of our previously defined 74-gene signature in predicting the radiation dose to samples in this study was unaffected by differences in gender or smoking status, however, giving 98% correct prediction of dose category. This is the same accuracy as that found in the original study from which the signature was derived, using different donors.ConclusionThe results support the development of peripheral blood gene expression as a viable strategy for radiation biodosimetry.

| S-EPMC3580190 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data