Rapid Low-Cost Paper-based Biodosimetry that reveals individual organ injuries

快速低成本纸基生物剂量测定可揭示个体器官损伤

• 批准号: 10349434
• 负责人: JOSHUA LABAER
• 金额: $ 41.01万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10349434
• 关键词: Acute; Address; Affect; Animals; Arizona; Biological; Biological Markers; Biological Models; Blood; Bone Marrow; Categories; Cells; Collaborations; Collection; Coupled; Data Analyses; Data Set; Development; Devices; Diagnostic tests; Dose; Drops; Ensure; Exposure to; Future; Gene Chips; Gene Expression; Gene Expression Profiling; Genes; Genetic Transcription; Genomic approach; Health Personnel; Hour; Human; Individual; Injury; Ionizing radiation; Laboratories; Literature; Lymphocyte; Lymphocyte Count; Lymphocyte Depletion; Measures; Medical; Methods; Modeling; Mus; Normal Range; Nuclear Accidents; Nucleic Acid Amplification Tests; Organ; Paper; Patients; Population; Probability; RNA; Radiation; Radiation Accidents; Radiation Dose Unit; Radiation Injuries; Radiation Tolerance; Radiation exposure; Radiation-Induced Gene Expression; Resource-limited setting; Resources; Risk; Sampling; Specificity; Techniques; Technology; Terrorism; Testing; Therapeutic Intervention; Time; Tissues; Triage; Universities; Work; Zika Virus; base; biodosimetry; biomarker panel; classification algorithm; cohort; cost; design; experience; human model; improved; in vivo; in vivo Model; next generation sequencing; novel strategies; organ injury; peripheral blood; personalized diagnostics; point of care; point of care testing; population based; predictive marker; radiation absorbed dose; response; screening; specific biomarkers; tool

Abstract: Increasing threats of nuclear accidents and/or terrorism have triggered an urgent need for the ability to confirm and quantify absorbed radiation doses in a large population exposed to an unknown amount of unintended radiation. An effective triage method has the potential to save thousands of lives. To best utilize the available resources, stepwise triage recommends first using a point-of-care (POC) test that distinguishes between the non-exposed and the exposed population, followed by an assessment of those exposed using high throughput quantitative analysis methods to estimate their absorbed doses of radiation. The ideal POC test will predict acute and delayed radiation injuries to major organs, like bone marrow. To estimate the absorbed dose, biodosimetry measures host biological responses to ionizing radiation. The expression of specific genes alters based on the dose of radiation. Here we use the expression levels of these radiation-responsive genes as biomarkers of exposure to radiation. Previously, we used genomic approaches coupled with an in vivo NHP model to identify many radiation responsive genes and develop a high throughput laboratory test to detect and quantify absorbed dose of radiation within 7 days of post exposure. A new analysis of these data reveals a subset of biomarkers that distinguish exposed from non-exposed individuals. Moreover, one of the hallmarks of radiation exposure is a rapid decay in the total number of lymphocytes. This new panel of biomarkers can quantitatively predict a significant drop in the lymphocyte count at 7 days post exposure, only 24 hours post exposure. We also have technology for converting our gene expression assays into a low-cost paper-based POC test, compatible with screening a large population. By combining our capabilities and currently available biomarkers, we intend to develop a low-cost POC test that; 1) identifies individuals exposed to unintended radiation; 2) qualitatively classifies individuals based on their absorbed dose of radiation; 3) predicts the risk of serious bone marrow injury by calculating their future day 7 lymphocyte counts on day 1. We will execute our project study plan in three steps. First, we will select the best subset of biomarkers by analyzing gene expression data sets and curating literature. Second, we will adapt our paper-based, low-cost, POC test to the critical expression levels of these markers. Finally, we will validate our test and biomarkers using independent unknown samples.

抽象的： 日益增加的核事故威胁和/或恐怖主义引发了迫切需要 能够确认和量化暴露于一个大量的吸收辐射剂量 未知量的意外辐射。有效的分类方法有可能节省 成千上万的生命。为了最好地利用可用的资源，逐步分类建议首先 使用分区（POC）测试，该测试区分了未暴露和暴露的测试 人口，然后对使用高通量定量暴露的人进行评估 分析方法以估计其吸收的辐射剂量。理想的POC测试将预测 重大器官（如骨髓）急性和延迟辐射损伤。估计 吸收的剂量，生物测量法测量对电离辐射的生物学反应。这 特定基因的表达根据辐射剂量改变。在这里我们使用该表达式 这些辐射响应基因的水平是暴露于辐射的生物标志物。之前， 我们使用了基因组方法与体内NHP模型结合的基因组方法来识别许多辐射 反应性基因并开发高通量实验室测试以检测和量化吸收 暴露后7天内的辐射剂量。对这些数据的新分析揭示了子集 区分暴露于非暴露个人的生物标志物。而且，之一 辐射暴露的标志是淋巴细胞总数的快速衰减。这个新 生物标志物面板可以定量预测7时淋巴细胞计数的显着下降 暴露后天数，暴露后仅24小时。我们还拥有转换我们的技术 基因表达测定在低成本的基于纸张的POC测试中，与筛选A兼容 人口众多。通过结合我们的功能和目前可用的生物标志物，我们打算 开发低成本POC测试； 1）确定暴露于意外辐射的人； 2） 定性地根据个人吸收的辐射剂量对个人进行分类； 3）预测风险 通过计算其未来第7天的淋巴细胞计数，严重的骨髓损伤。 将分三个步骤执行我们的项目学习计划。首先，我们将选择最佳子集 生物标志物通过分析基因表达数据集和策展文献。第二，我们会的 将我们的基于纸张的低成本POC测试适应这些标记的临界表达水平。 最后，我们将使用独立的未知样品验证我们的测试和生物标志物。