Validating remote digital assessments for familial frontotemporal dementia

验证家族性额颞叶痴呆的远程数字评估

• 批准号: 10448922
• 负责人: Adam Mark Staffaroni
• 金额: $ 237.14万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10448922
• 关键词: 3-Dimensional; Accelerometer; Adult; Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Assessment tool; Behavioral; Biological Markers; Brain Health Registry; C9ORF72; COVID-19 pandemic; Cellular Phone; Clinical; Clinical Trials; Clinical dementia rating scale; Cognitive; Cognitive aging; Collaborations; Data; Data Set; Dementia; Detection; Development; Disease; Disease Progression; Early Diagnosis; Enrollment; Family; Frontotemporal Dementia; Funding; Future; Genes; Geography; Goals; Gold; Health; Human; Impaired cognition; Individual; Lead; Light; Longevity; MAPT gene; Magnetic Resonance Imaging; Measurement; Measures; Methods; Molecular Abnormality; Monitor; Motor; Mutation; Natural History; Nerve Degeneration; Neurodegenerative Disorders; Neurologic; Neuropsychological Tests; Neuropsychology; Observational Study; Outcome Measure; PGRN gene; Parents; Parkinson Disease; Participant; Pathogenicity; Persons; Plasma; Prognosis; Psychometrics; Rare Diseases; Recommendation; Research; Research Personnel; Research Priority; Response Latencies; Sampling; Severities; Severity of illness; Site; Symptoms; Testing; Therapeutic; Training; Travel; United States National Institutes of Health; Validation; Visit; Visuospatial; Work; arm; autosomal dominant mutation; biomarker development; brain magnetic resonance imaging; cerebral atrophy; clinical predictors; cohort; digital; effective therapy; follow-up; healthy aging; improved; innovation; kindred; mobile application; motor disorder; mutation carrier; neurofilament; new therapeutic target; novel; online registry; predictive modeling; prognostication; recruit; remote grading; research study; smartphone Application; standard measure; therapeutic development; treatment effect

PROJECT SUMMARY/ABSTRACT Frontotemporal Dementia (FTD) is a fatal neurodegenerative disease that presents with behavioral, cognitive, or motor dysfunction and has no effective treatments. About 20-30% of cases are familial (fFTD), caused by autosomal dominant mutations. Increasing numbers of novel therapeutics targeting these genetic abnormalities are entering clinical trials. A major barrier to fFTD therapeutic development is the lack of clinically meaningful outcome measures that can be easily collected and are sensitive to treatment effects at early stages of disease. Because fFTD is rare, participants are geographically dispersed and travel is another recruitment barrier for in-person clinical trials. To facilitate more inclusive clinical trials, investigators from the ARTFL/ LEFFTDS Longitudinal FTD (ALLFTD) consortium partnered with Datacubed Health to develop a novel smartphone application that enables remote testing of executive and motor functioning, domains affected early in fFTD. The goal of this proposal is to validate these innovative remote smartphone assessments for early detection, longitudinal monitoring, and prognostication of fFTD symptoms. To achieve this goal, the project will recruit two separate but related cohorts. The first is a cross-sectional cohort of 1,000 cognitively and functionally intact adults from across the lifespan enrolled through a collaboration with the NIH-funded Brain Health Registry (BHR). BHR participants will take the smartphone tests and online BHR clinical measures. The BHR cohort will be used to develop psychometrically robust composite scores and will be used to validate the scores in a healthy aging cohort. The second arm is a longitudinal clinical validation cohort of 400 participants from kindreds with known pathogenic fFTD mutations who will be recruited through the ALLFTD consortium, including 100 symptomatic and 150 presymptomatic fFTD mutation carriers and 150 noncarrier family controls. Participants in this cohort will complete the digital app assessments every six months for three years, along with comprehensive, annual in-person visits conducted through the parent ALLFTD study. Aim 1 will investigate the cross-sectional construct validity of the app composite scores by testing for associations with gold-standard measures of neuropsychological functioning, disease severity, and biomarkers of neurodegeneration. Aim 1 will also test whether the composites can detect early cross-sectional deficits in presymptomatic fFTD. Aim 2 will study the utility of these smartphone measures for longitudinal tracking of fFTD disease progression, and Aim 3 investigates whether these measures predict future clinical progression. If successful, this project will yield a scalable digital assessment tool for early detection, prognosis, and disease monitoring that could lead to more inclusive and powerful fFTD trials. Furthermore, as changes in executive and motor function are ubiquitous in neurological and aging cohorts, this app has broad applicability to study cognitive aging and associated conditions such as Alzheimer’s disease and related dementias.

项目总结/摘要 额颞叶痴呆（FTD）是一种致命的神经退行性疾病，表现为行为，认知， 或运动功能障碍，并且没有有效的治疗方法。大约20-30%的病例是家族性的（fFTD），由 常染色体显性突变越来越多的针对这些遗传异常的新疗法 正在进入临床试验。fFTD治疗开发的一个主要障碍是缺乏有临床意义的 结果指标，可以很容易地收集，并在早期阶段的治疗效果敏感 疾病由于fFTD很少见，参与者在地理上分散，旅行是另一种招募方式 人临床试验的障碍。为了促进更具包容性的临床试验，来自ARTFL/ LEFFTDS纵向FTD（ALLFTD）联盟与Datacubed Health合作开发了一种新的 智能手机应用程序，可以远程测试执行和运动功能，早期受影响的领域 在fFTD中。该提案的目标是验证这些创新的远程智能手机评估， fFTD症状的检测、纵向监测和诊断。为了实现这一目标，该项目将 招募两个独立但相关的群体。第一组是1,000名认知和 通过与美国国立卫生研究院资助的大脑研究所合作， 健康登记处。BHR参与者将进行智能手机测试和在线BHR临床测量。的 BHR队列将用于开发心理测量学上稳健的综合评分，并将用于验证 在健康老龄化队列中的得分。第二组是400名参与者的纵向临床验证队列 来自通过ALLFTD联盟招募的已知致病性fFTD突变的激酶， 包括100例症状性和150例症状前fFTD突变携带者和150例非携带者家族对照。 该队列中的参与者将在三年内每六个月完成一次数字应用程序评估，沿着 通过母研究ALLFTD进行全面的年度亲自访视。目标1将 通过测试与以下因素的关联，调查应用程序综合评分的横断面结构效度： 神经心理功能、疾病严重程度和 神经变性Aim 1还将测试复合材料是否能检测到早期的横截面缺陷， 症状前fFTD。目标2将研究这些智能手机措施在纵向跟踪 fFTD疾病进展，目的3研究这些指标是否可预测未来的临床进展。 如果成功，该项目将产生一个可扩展的数字评估工具，用于早期检测，预后， 疾病监测，可能导致更具包容性和强大的fFTD试验。此外，由于 执行和运动功能在神经和衰老人群中普遍存在，该应用程序具有广泛的适用性 研究认知老化和相关的疾病，如阿尔茨海默病和相关的痴呆症。