Browsing by Subject "Blood Cells"

Now showing 1 - 3 of 3
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    A translatable predictor of human radiation exposure.
    (PLoS One, 2014) Lucas, Joseph; Dressman, Holly K; Suchindran, Sunil; Nakamura, Mai; Chao, Nelson J; Himburg, Heather; Minor, Kerry; Phillips, Gary; Ross, Joel; Abedi, Majid; Terbrueggen, Robert; Chute, John P
    Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.
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    Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients.
    (BMC Med Genomics, 2011-03-28) Elashoff, Michael R; Wingrove, James A; Beineke, Philip; Daniels, Susan E; Tingley, Whittemore G; Rosenberg, Steven; Voros, Szilard; Kraus, William E; Ginsburg, Geoffrey S; Schwartz, Robert S; Ellis, Stephen G; Tahirkheli, Naheem; Waksman, Ron; McPherson, John; Lansky, Alexandra J; Topol, Eric J
    BACKGROUND: Alterations in gene expression in peripheral blood cells have been shown to be sensitive to the presence and extent of coronary artery disease (CAD). A non-invasive blood test that could reliably assess obstructive CAD likelihood would have diagnostic utility. RESULTS: Microarray analysis of RNA samples from a 195 patient Duke CATHGEN registry case:control cohort yielded 2,438 genes with significant CAD association (p < 0.05), and identified the clinical/demographic factors with the largest effects on gene expression as age, sex, and diabetic status. RT-PCR analysis of 88 CAD classifier genes confirmed that diabetic status was the largest clinical factor affecting CAD associated gene expression changes. A second microarray cohort analysis limited to non-diabetics from the multi-center PREDICT study (198 patients; 99 case: control pairs matched for age and sex) evaluated gene expression, clinical, and cell population predictors of CAD and yielded 5,935 CAD genes (p < 0.05) with an intersection of 655 genes with the CATHGEN results. Biological pathway (gene ontology and literature) and statistical analyses (hierarchical clustering and logistic regression) were used in combination to select 113 genes for RT-PCR analysis including CAD classifiers, cell-type specific markers, and normalization genes.RT-PCR analysis of these 113 genes in a PREDICT cohort of 640 non-diabetic subject samples was used for algorithm development. Gene expression correlations identified clusters of CAD classifier genes which were reduced to meta-genes using LASSO. The final classifier for assessment of obstructive CAD was derived by Ridge Regression and contained sex-specific age functions and 6 meta-gene terms, comprising 23 genes. This algorithm showed a cross-validated estimated AUC = 0.77 (95% CI 0.73-0.81) in ROC analysis. CONCLUSIONS: We have developed a whole blood classifier based on gene expression, age and sex for the assessment of obstructive CAD in non-diabetic patients from a combination of microarray and RT-PCR data derived from studies of patients clinically indicated for invasive angiography. CLINICAL TRIAL REGISTRATION INFORMATION: PREDICT, Personalized Risk Evaluation and Diagnosis in the Coronary Tree, http://www.clinicaltrials.gov, NCT00500617.
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    Early hematopoietic effects of chronic radiation exposure in humans.
    (Health Phys, 2010-09) Akleyev, Alexander V; Akushevich, Igor V; Dimov, Georgy P; Veremeyeva, Galina A; Varfolomeyeva, Tatyana A; Ukraintseva, Svetlana V; Yashin, Anatoly I
    The major goal of this study is to investigate and quantitatively describe the nature of the relationship between the characteristics of chronic exposure to ionizing radiation and specific patterns of hematopoiesis reduction. The study is based on about 3,200 hemograms taken for inhabitants of the Techa riverside villages over the years 1951-1956, i.e., the period characterized by a gradual decrease in dose rates. The mean cumulative red bone marrow dose was 333.6 + or - 4.6 mGy. The approach to statistical analyses involved both empirical methods and modeling (generalized linear models and logistic regressions). The results of the analyses highlighted a gradual increase in the frequency of cytopenias with dose rate. The impact of exposure on hematopoiesis reduction patterns was found to be more substantial than that of age and health status. Dose rates resulting in a two-fold increase in the frequency of cytopenias have been estimated.