DS-ARC: A Remote Digital Cognitive Assessment for Down Syndrome-Associated Alzheimer's Disease

项目总结 唐氏综合征-认知动态研究(DS-ARC)研究将开发和验证 专门为唐氏综合症风险参与者设计的基于智能手机的数字认知评估 综合征相关性阿尔茨海默病(DS-AD)。我们将与伦敦、巴塞罗那、慕尼黑、 和哥德堡在不同的文化和语言中开发和验证这一方法。几乎所有人 唐氏综合症患者的阿尔茨海默病(AD)生物标志物水平在他们 都是30多岁或40多岁，尽管并不是所有人都表现出AD的症状。它处于症状前期和早期 DS-AD的症状阶段，深入了解认知变化是至关重要的，作为治疗 阻止、减缓或预防疾病的干预措施主要集中在这些关键时期。通常情况下，预防试验 在AD人群中的观察性研究通过标准的“桌面”纸和铅笔测试来评估认知。 但这些传统方法有几个缺点。首先，业绩受日复一日的影响 压力、疲劳、睡眠模式和情绪的波动。其次，测试在以下环境中进行 与日常生活中依赖认知发挥作用的地方是根本不同的。最后，通过设计， 认知能力通常是在每年或每半年延长的测试会议中以“一次性”的方式进行评估。 DS-ARC研究将通过开发基于智能手机的评估解决方案来解决这些困难 特别适用于唐氏综合症患者。此方法使用测量“猝发”设计。 在为期一周的时间里，参与者每天在智能手机上完成几次非常简短的认知测试 同时生活在它们的自然环境中。测试不是集中在这些测量中的一种，而是 一周的平均，以提供一个分数，捕捉和正常化自然变异性和戏剧性 提高了可靠性。我们对常染色体显性遗传性和散发性AD的原始ARC评估的研究 展示与AD生物标记物的非凡可靠性和牢固的关系，同时降低成本和 繁重的临床评估。这项研究分为两个阶段：两年的发展阶段和三年的发展阶段 验证阶段。在开发阶段，我们将改编一个名为 认知动态研究(ARC)应用程序，用于DS-AD研究。这将包括迭代试行 心理测量学和任务开发、焦点小组和用户体验测试的测试流程，以解决 DS-AD人群的可访问性和兼容性问题，以及准备情况审计，以确保DS- ARC APP符合临床试验应用的严格遵从性指南。在第二阶段，参与者完成DS- 每6个月进行一次ARC评估，并完成AD的标准临床、认知和血液测试 每年一次的生物标志物。我们假设DS-ARC评估是可访问的、敏感的和可靠的 DS-AD认知改变的指标，并将与AD生物标志物和疾病阶段相关 除了常规的临床评估外，还有更多的信息。

PROJECT SUMMARY The Down Syndrome – Ambulatory Research in Cognition (DS-ARC) study will develop and validate a smartphone-based digital cognitive assessment designed specifically for participants at risk for Down syndrome-associated Alzheimer’s disease (DS-AD). We will partner with sites in London, Barcelona, Munich, and Gothenburg to develop and validate this approach in different cultures and languages. Nearly all individuals with Down syndrome have elevated levels of Alzheimer’s disease (AD) biomarkers by the time they are in their 30s or 40s, though not all show symptoms of AD. It is during the pre-symptomatic and early symptomatic stages of DS-AD that an in-depth understanding of cognitive changes is crucial, as therapeutic interventions to stop, slow, or prevent disease are focused on these critical periods. Typically, prevention trials and observational studies in AD populations assess cognition with standard “table top” paper and pencil tests. But these conventional methods have several drawbacks. First, performance is influenced by day to day fluctuations in stress, fatigue, sleep patterns, and mood. Second, the testing takes place in environments that are fundamentally different from where cognition is relied upon to function in daily life. Finally, by design, cognition is typically assessed in “one-shot” in extended testing sessions on an annual or semiannual basis. The DS-ARC study will address these difficulties by developing a smartphone-based assessment solution adapted specifically for individuals with Down syndrome. This approach uses a measurement “burst” design in which participants complete very brief cognitive tests on their smartphones several times per day for one week while living in their natural environments. Instead of focusing on one of these measurements, tests are averaged across the week to provide a score that captures and normalizes natural variability and dramatically increases reliability. Studies of our original ARC assessments in autosomal dominant and sporadic AD demonstrate extraordinary reliability and strong relationships with AD biomarkers, while reducing costly and burdensome in-clinic evaluations. The study has two phases: a 2-year development phase and a 3-year validation phase. In the development phase, we will adapt an existing smartphone application called the Ambulatory Research in Cognition (ARC) app for use in DS-AD studies. This will include an iterative pilot testing process for psychometrics and task development, focus groups and user experience testing to address accessibility and compatibility concerns for DS-AD populations, and readiness audits to ensure that the DS- ARC app meets strict compliance guidelines for clinical trial applications. In Phase 2, participants complete DS- ARC assessments every 6 months and complete standard clinical, cognitive, and blood tests for AD biomarkers annually. We hypothesize that DS-ARC assessments are accessible, sensitive, and reliable indicators of cognitive change in DS-AD and will exhibit associations with AD biomarkers and disease stage over and above those of conventional in-clinic assessments.