Identifying Digital Phenotypes of Risk for Alzheimer's Disease and Related Dementias Among Hispanics/Latinos

项目总结 拉美裔/拉丁裔患阿尔茨海默病和相关痴呆的风险增加(ADRD) 与非西班牙裔白人相比。虽然造成这种差距的因素还没有被很好地理解，但增加了 拉美裔/拉丁裔的心血管疾病风险可能是一个促成因素。病理性的 ADRD的变化在临床症状显现之前几年就开始了，干预措施最有可能 在ADRD的早期阶段提供利益。迫切需要开发工具来检测最早的 ADRD的表现，特别是在西班牙裔，他们在较早的年龄就出现了ADRD的症状，但 与其他组相比，被诊断为疾病更晚期的患者。各种行为显示了 ADRD的临床前阶段，包括睡眠、步速和体力活动等。最新创新 在移动技术中，现在提供了新的方法来被动地收集、跟踪和分析这些行为 不引人注意的，当一个人参与他们的日常生活时。我们的初步工作表明，该技术的应用 从智能手机和可穿戴设备被动收集数字健康数据的机器学习模型 有轻度认知障碍和无轻度认知障碍的区分者，主要是非西班牙裔，准确率为85% 白色样本。在NIA健康差异研究框架的指导下，我们建议利用人工智能 智能(AI)驱动的分析和洞察，以及消费电子产品中随时可用的传感器 (智能手机、手腕可穿戴设备)，以识别ADRD风险的数字生物标记物，重点是血管 在拉美裔/拉丁裔中，对痴呆症的贡献。扩大对拉美裔/拉丁裔的现有队列研究 居住在南加州的这项拟议研究有三个主要目标：目标1涉及确定数字 综合被动移动传感技术在西班牙裔(N=300；年龄50-70岁)中ADRD风险的特征 源自智能手机和手腕可穿戴设备的功能，以及机器学习方法。ADRD风险将 根据认知状况和心血管疾病风险负担(糖尿病、高胆固醇血症、高血压、肥胖、 吸烟)，并将纳入载脂蛋白E(载脂蛋白E-ε4)和基于血浆的AD生物标志物，以进一步 ADRD风险分类。目标2调查ADRD风险数字签名和目标3的性别差异 考察社会文化因素(例如，语言使用、文化适应)对这些签名的影响。我们还将 研究数字数据特征的变化是否预测在一段时间内的纵向神经认知变化 在有和没有ADRD风险的西班牙裔美国人中生活了三年。在一家著名的研究机构内 作为ADRD研究和工程创新的先锋，拟议的研究包括一项多学科的 团队拥有这一尖端提案的所有方面的专业知识。认识到一个社区的价值- 参与研究的方法，我们已经与社区利益攸关方合作，以确保我们的 向西班牙裔社区学习。我们的工作可能使ADRD的早期发现发生革命性变化，并减少ADRD 通过开发一种低负担、低成本的方法来确定拉美裔美国人中的ADRD风险，可以减少差异。

PROJECT SUMMARY Hispanics/Latinos are at increased risk for developing Alzheimer’s disease and related dementias (ADRD) compared to non-Hispanic Whites. While factors underlying this disparity are not well understood, increased cardiovascular disease (CVD) risk among Hispanics/Latinos is likely to be a contributory factor. Pathological changes of ADRD begin years before clinical symptoms become evident and interventions are most likely to confer benefit in the earliest stages of ADRD. There is a pressing need to develop tools to detect the earliest manifestations of ADRD, particularly in Hispanics, who develop symptoms of ADRD at earlier ages, yet are diagnosed at more advanced disease stages than other groups. A variety of behaviors show changes in the preclinical stages of ADRD, including sleep, gait speed, and physical activity, among others. Recent innovations in mobile technology now offer novel ways to collect, track, and analyze these behaviors passively and unobtrusively, as a person engages in their daily life. Our preliminary work demonstrated that the application of machine learning models to passively-collected digital health data from smartphones and wearables differentiated persons with and without mild cognitive impairment with 85% accuracy in a primarily non-Hispanic White sample. Guided by the NIA Health Disparities Research Framework, we propose to leverage artificial intelligence (AI)-powered analytics and insights, coupled with readily available sensors in consumer electronics (smartphones, wrist-worn wearables), to identify digital biomarkers of ADRD risk, with a focus on vascular contributions to dementia, among Hispanics/Latinos. Augmenting an existing cohort study of Hispanics/Latinos residing in Southern California, the proposed study has three principal aims: Aim 1 involves determining digital signatures of ADRD risk among Hispanics (N=300; aged 50-70 years) using integrated passive mobile sensing features, derived from smartphones and wrist-worn wearables, and machine learning methods. ADRD risk will be defined by cognitive status and CVD risk burden (diabetes, hypercholesterolemia, hypertension, obesity, smoking) and will also incorporate apolipoprotein E (APOE-ε4) and plasma-based AD biomarkers for further classification of ADRD risk. Aim 2 investigates sex differences in digital signatures of ADRD risk and Aim 3 examines the impact of sociocultural factors (e.g., language use, acculturation) on these signatures. We will also investigate whether changes in digital data features predict longitudinal neurocognitive change over a span of three years in a subset of Hispanics with and without ADRD risk. Housed within a renowned research institution at the vanguard of ADRD research and engineering innovations, the proposed study includes a multidisciplinary team with expertise across all aspects of this cutting-edge proposal. Recognizing the value of a community- engaged research approach, we have partnered with community stakeholders to ensure the relevance of our study to the Hispanic community. Our work could revolutionize early detection of ADRD and reduce ADRD disparities by developing a low burden, low-cost approach to identify ADRD risk among Hispanics.