Plasma Abeta isoform concentrations in cognitively impaired patients at risk for amyloidosis

项目总结/摘要 长期以来，人类阿尔茨海默病（AD）的研究一直受到以下事实的阻碍， AD的绝对诊断只能通过尸检后的脑病理学评估来确定。更 最近，成像剂已经变得可用，其允许直接成像AD的两个标志 （淀粉样蛋白斑和tau蛋白缠结）。然而，这些显像剂昂贵， 用于常规诊断的侵入性。对低成本的基于血液的诊断测定的需求从未被忽视。 更大C2 N Diagnostics一直在开发基于质谱的检测方法， 自2007年以来，生物流体中的β肽。β淀粉样蛋白的样品净化、纯化以及 质谱分析仪器使得可靠地定量人体内的β淀粉样蛋白成为可能 血浆样本来自华盛顿大学兰德尔·贝特曼博士实验室的初步数据显示 血浆中两种淀粉样β肽的比例可以预测血浆中淀粉样斑块的存在。 个脑袋这项技术可能会彻底改变AD诊断领域，当在 2017年7月阿尔茨海默氏症协会国际会议上，这一发现被宣布为“迄今为止 会议的最大新闻”由AD临床研究的关键意见领袖之一。具体目标 该SBIR快速通道应用程序的目的是在分析和临床上验证C2 N的血浆检测试剂盒， 用于预测脑淀粉样变性的诊断测试。

PROJECT SUMMARY/ABSTRACT For a long time, the study of Alzheimer’s disease (AD) in humans has been hampered by the fact that absolute AD diagnosis could only be ascertained by assessment of brain pathology upon autopsy. More recently, imaging agents have become available that allow direct imaging of the two hallmarks of AD (amyloid plaques and tau tangles) in living humans. However, these imaging agents are expensive and invasive for use in routine diagnostics. The need for low-cost blood based diagnostic assays has never been greater. C2N Diagnostics has been developing mass spectrometry based assays that investigate amyloid beta peptides in biofluids since 2007. Recent advances in sample cleanup, purification of amyloid beta, and mass spectrometry instrumentation have made it possible to reliably quantify amyloid beta in human plasma samples. Preliminary data from Dr. Randall Bateman’s laboratory at Washington University shows that the ratio of two amyloid beta peptides in plasma can predict the presence of amyloid plaques in the brain. This technology could revolutionize the field of AD diagnostics, and when presented at the Alzheimer’s Association International Conference in July 2017, this discovery was pronounced as “by far the biggest news of the meeting” by one of the key opinion leaders in AD clinical research. The specific aims of this SBIR Fast-Track application are to analytically and clinically validate C2N’s plasma assay for use as a diagnostic test for predicting brain amyloidosis.