An acoustofluidic device for diagnosing preclinical Alzheimer's disease

摘要 阿尔茨海默氏病（AD）是一种致残性的晚期神经退行性疾病，影响约550万人 在美国，大约有10%的人口年龄在65岁以上。早期症状 疾病包括近期记忆障碍、语言表达困难和行为改变 包括抑郁情绪。随着时间的推移，症状逐渐恶化，最终导致痴呆症和丧失 身体功能。目前还没有敏感的、客观的诊断试验用于AD的早期诊断， 医生很难正确筛查这种疾病，也无法诊断出可能呈阳性的患者。 AD.虽然在AD的医学成像方面已经取得了进展，但是它们极其昂贵并且具有有限的应用前景。 诊断准确性。近年来，神经元来源的外泌体（30-150 nm的细胞外囊泡）已经被用于治疗神经元疾病。 成为诊断AD的有前途的生物标志物。在循环中发现的神经元来源的外泌体可以提供 这是一种简单的、非侵入性的监测中枢神经系统健康的方法。越来越多的证据 提示神经元来源的外泌体可能通过帮助扩散而在AD的病理学中起着至关重要的作用。 异常的，潜在的致病的，错误折叠的蛋白质遍布大脑。初步研究表明 通过分析神经元来源的外泌体及其分子货物的数量， 可以与健康对照以及患有其他神经系统疾病的患者区分开来。而 研究人员在鉴定神经元来源的外泌体蛋白和RNA方面取得了进展， 围绕外泌体的分离和分析的研究已经阻止了它们作为AD的生物标志物的广泛使用。 目前，没有能够同时分离和分析的市售产品 神经元来源的外泌体。该SBIR项目的目标是克服现有AD的局限性 诊断技术，并通过开发和商业化解决市场上未满足的需求， 自动化、高纯度、高产率、生物相容性外泌体分离和精确的AD生物标志物检测， 声流体（即，声学与流体力学的融合）分离与电化学检测 技术.在第一期工程的工作中，我们成功地证明了 所提出的用于AD诊断的外泌体分离和分析装置通过满足或超过目标值 成功的衡量标准中确定的四个关键参数中的每一个。在第二阶段，我们的商业化 活动将提高声流控芯片的性能，开发独立的，β测试准备 原型，并与最终用户验证其性能。凭借其自动化、速度、精度等优势， 和准确性，所提出的声流体技术有可能大大简化和革命性的 AD的诊断结果将是一个高度敏感的液体活检，将提供全面的分子 特征，从而显著提高诊断准确性，超过现有方法，并提供更深入的 对疾病的病理生理学的深入了解。

Abstract Alzheimer’s disease (AD) is a crippling, terminal neurodegenerative illness that affects an estimated 5.5 million people in the United States and approximately 10% of the population over the age of 65. Early symptoms of the disease include impairment in recent memory, difficulties with expressive language, and behavioral changes including depressed mood. Symptoms gradually worsen over time, ultimately leading to dementia and a loss of bodily functions. Currently there is no sensitive, objective diagnostic test for the early diagnosis of AD, making it difficult for physicians to properly screen for the disease and failing to diagnose patients that may be positive for AD. While advances have been made in medical imaging for AD, they are extremely costly and have limited diagnostic accuracy. In recent years, neuron-derived exosomes (30-150 nm extracellular vesicles) have emerged as a promising biomarker for diagnosing AD. Neuron-derived exosomes found in circulation can provide a simple, non-invasive means of monitoring the health of the central nervous system. Accumulating evidence suggests that neuron-derived exosomes may play a crucial role in the pathology of AD by helping to spread abnormal, potentially disease-causing, misfolded proteins throughout the brain. Preliminary studies have shown that by analyzing the number of neuron-derived exosomes and their molecular cargo, early-stage AD patients can be distinguished from healthy controls, as well as patients with other neurological diseases. While researchers have made progress in identifying neuron-derived exosomal proteins and RNAs, difficulties surrounding the isolation and analysis of exosomes have prevented their widespread use as a biomarker for AD. Currently, there are no commercially available products capable of simultaneously isolating and analyzing neuron-derived exosomes. The objective of this SBIR project is to overcome the limitations of existing AD diagnostic technologies and address the unmet needs in the market by developing and commercializing an automated, high-purity, high-yield, biocompatible exosome isolation and accurate AD biomarker detection using acoustofluidic (i.e., the fusion of acoustics and fluid mechanics) separation and electrochemical detection technologies. During our work on the Phase I project, we successfully demonstrated the utility and feasibility of the proposed exosome isolation and analysis device for AD diagnosis by meeting or exceeding the target values for each of the four key parameters identified in the Measures of Success. In Phase II, our commercialization activities will improve the performance of the acoustofluidic chips, develop self-contained, beta-testing-ready prototypes, and validate their performance with end users. With its advantages in automation, speed, precision, and accuracy, the proposed acoustofluidic technology has the potential to greatly simplify and revolutionize the diagnosis of AD. The result will be a highly sensitive liquid biopsy that will provide a comprehensive molecular signature for AD, thus significantly improving diagnostic accuracy past existing methods and providing deeper insight in the pathophysiology of the disease.