Mechanisms of sleep deficiency and effects on brain injury and neurocognitive functions among older blacks

项目摘要 翻译研究显示阿尔茨海默病(AD)发病机制与 睡眠/昼夜节律的扰乱重新引起了人们对这句格言的兴趣：睡眠是大脑的，是大脑的，是 大脑‘。相对于睡眠良好的成年人，那些表现出睡眠不足(SD)的人，定义为睡眠不良 呼吸暂停和/或昼夜节律失调有更大的AD风险(OR=1.55)，认知能力下降(OR=1.68)，或 临床前AD(OR=3.78)。由于SD是在AD过程的早期观察到的，它构成了 预防。尽管在描述睡眠的机制和功能方面取得了成功，但一个关键的差距 仍在阐明支持黑人睡眠差异的因素，以更大的阿尔茨海默病风险为标志 负担。黑人也承受着更大的睡眠负担，这从主要的SD的较高患病率中得到了证明。 指数，这与血管风险增加、炎症、脑损伤和认知障碍有关。 多学科团队将在多层次上利用创新的动态和地理空间建模 描述精神障碍的心理社会和环境决定因素及其可能影响的框架 老年黑人的大脑健康。我们将利用纽约大学睡眠差异工作组的成功， 由具有衰老研究、翻译睡眠和昼夜节律科学专业知识的研究人员组成，大脑 健康、健康差距、地理空间和多层次动态建模。我们将利用社交网络 我们社区指导委员会的资金和资产将从传统学校招收504名黑人(60-75岁) 和非传统场所来捕捉学习终点。我们将调查以下目标：1) 确定心理社会(社会/情感支持、情绪、歧视、态度)和环境 (家庭[密度、噪音、空气质量、光线和温度]、社会经济地位、社会资本、 邻里[建成环境])与可持续发展相关的因素；2)评估可持续发展对 脑损伤标志物(同型半胱氨酸、神经营养因子、胶质纤维酸性蛋白、牛磺酸和淀粉样蛋白-β肽)及其对神经认知功能的影响 (使用临床前阿尔茨海默病认知复合量表的注意力、语言、记忆和执行功能 和跟踪测试)。血管风险(肥胖、血压、血脂和血糖/糖化血红蛋白)和 炎症(IL-6、IL-10和肿瘤坏死因子-α)将被加权；3)表征风险增加的黑人 SD使用贝叶斯机器学习建模，并通过基于代理的建模进行预测 心理社会和环境变化的融合将导致可持续发展负担的减轻和相关 随着时间的推移(5年、10年和20年)老年黑人的大脑健康状况。调查小组将使用小说 家用数字记录仪、创新的脑健康生物标志物、地理空间分析和动态 系统建模以描述SD的机制并描绘其在解释中的潜在作用 观察到老年黑人大脑健康标志物的差异。

Project Summary Translational studies showing a mechanistic interplay between Alzheimer’s disease (AD) pathogenesis and sleep/circadian disruption has renewed interest in the maxim ‘sleep is of the brain, by the brain, and for the brain’. Relative to adults sleeping well, those exhibiting sleep deficiency (SD), defined as poor sleep, sleep apnea, and/or circadian misalignment, have greater AD risk (OR=1.55), cognitive decline (OR=1.68), or preclinical AD (OR=3.78). Since SD is observed early in the course of AD, it constitutes a prime target for prevention. Notwithstanding successes in delineating the mechanisms and functions of sleep, a critical gap remains in elucidating factors undergirding sleep disparities among blacks, marked by a greater AD risk burden. Blacks also shoulder a greater sleep burden as evidenced by a higher prevalence of the main SD indices, which are linked to increased vascular risks, inflammation, brain injury, and cognitive impairment. The multi-disciplinary team will utilize innovative dynamic and geospatial modeling in a multi-level framework to delineate the psychosocial and environmental determinants of SD and its putative effects on the brain health of older blacks. We will leverage the success of the NYU Sleep Disparity Workgroup, comprising investigators with expertise in aging research, translational sleep and circadian sciences, brain health, health disparities, and geospatial and multi-level dynamic modeling. We will leverage the social capital and assets of our Community Steering Committee to enroll 504 blacks (60-75 years) from traditional and non-traditional venues to capture study endpoints. We will investigative the following aims: 1) To ascertain the psychosocial (social/emotional support, mood, discrimination, attitudes) and environmental (household [density, noise, air quality, light, and temperature], socioeconomic position, social capital, neighborhood [built environment]) factors that are associated with SD; 2) To assess effects of SD on markers of brain injury (Hcy, NFL, GFAP, Tau & Amyloid-β peptides) and on neurocognitive functions (attention, language, memory, and executive function using the Preclinical Alzheimer Cognitive Composite and Trail Making Test). The contributions of vascular risk (obesity, BP, lipid, and glucose/HbA1C) and inflammation (IL-6, IL-10, and TNF-α) will be weighted; 3) To characterize blacks who are at increased risk of SD using Bayesian machine-learning modeling and forecast through Agent-Based modeling which amalgamation of psychosocial and environmental changes will lead to a reduced SD burden and related brain health profile among older blacks over time (5, 10, & 20 yrs.). The investigative team will use novel home-based digital recorders, innovative brain health biomarkers, geospatial analytics and dynamic systems modeling to describe the mechanisms of SD and delineate their potential role in explaining observed disparities in markers of brain health of older blacks.