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

ABSTRACT: The 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.As 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.We 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.The results support the development of peripheral blood gene expression as a viable strategy for radiation biodosimetry.

SUBMITTER: Paul S

PROVIDER: S-EPMC3580190 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

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

Paul Sunirmal S Amundson Sally A SA

International journal of radiation biology 20110801 8

<h4>Purpose</h4>The 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.<h4>Materials and methods</h4>As 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 ...[more]

PMID: 21801107

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Project description:The human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value < 0.05) between Acinetobacter, Serratia, Streptococcus and Bacillus inferred abundances and Modified Medical Research Council (mMRC) dyspnea score. Current smoking status was associated (q < 0.05) with Acinetobacter, Serratia and Cutibacterium abundance. All 12 taxa investigated were associated with at least one white blood cell distribution variable. Abundance for nine of the 12 taxa was associated with sex, and seven of the 12 taxa were associated with race. Host-microbiome interaction analysis revealed clustering of genera associated with mMRC dyspnea score and smoking status, through shared links to several host pathways. This study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between systemic microbial signatures and lung-related phenotypes may inform novel interventions and aid understanding of the systemic effects of smoking.

Dataset Information

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

Publications

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

Similar Datasets

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