Use of microfluidics in determining hemostatic phenotypes

描述（由申请人提供）：出血和血栓性疾病具有显著的表型变异性。在过去十年中，对这些疾病的分子基础的理解取得了重要进展；然而，观测到的变异性的很大一部分仍然是未知的。由于出血过多是一个重要的医学问题，具有令人印象深刻的发病率和死亡率，发现新的出血生物标志物可能对公共卫生产生非常重大的影响。目前用于诊断出血性疾病的检测方法存在局限性，特别是在轻度至中度出血的识别和止血系统常见变异的区分方面。此外，定量临床出血是极其困难的。因此，需要一种具有高灵敏度和特异性的方法。我们建议开发一种高通量微流分析方法来量化健康个体和有出血性疾病个体血液样本中的血小板粘附、聚集和纤维蛋白沉积。这项研究将代表迄今为止临床环境中最大的微流控分析。我们将这些分析的结果与当前临床和实验室测量的出血表型相关联。我们的长期目标是开发一种高度敏感和特异性的方法来确定出血性疾病患者的止血潜力。

DESCRIPTION (provided by applicant): Bleeding and thrombotic disorders are characterized by significant phenotypic variability. Over the last decade important advances have been made in the understanding of the molecular basis of these disorders; however a large portion of the observed variability remains unknown. Since excessive bleeding represents a significant medical issue with impressive morbidity and mortality, discovering new biomarkers of bleeding could have a very significant public health impact. Current assays for the diagnosis of bleeding disorders have limitations, particularly for the identification of mild to moderate bleeding and the discrimination of common variations in the hemostatic system. Also, quantifying clinical bleeding is extremely difficult. Therefore, a method that shows high sensitivity and specificity is highly desirable. We propose to develop a high-throughput microfluidic flow assay to quantify platelet adhesion, aggregation and fibrin deposition in blood samples of healthy individuals and individuals with established bleeding disorders. This study will represent the largest analysis to date of microfluidic assays in the clinical setting. We will correlate the results of these assays with current clinical and laboratory measures of bleeding phenotypes. It is our long term goal to develop a highly sensitive and specific method to determine the hemostatic potential of individuals with bleeding disorders. PUBLIC HEALTH RELEVANCE: It important to understand why some people bleed more than others. Currently, there are no methods that can accurately predict this problem. We are trying to develop a system where we can diagnose bleeding disorders and eventually predict risk for bleeding for example during surgery.