Down Syndrome: Toward Optimal Trajectories and Health Equity using Medicaid Analytic eXtract (DS -TO-THE-MAX)

项目摘要 唐氏综合征（DS）是21号染色体的一种三体，是智力低下最常见的遗传原因。 残疾，曾经是一种儿童很少看到成年的情况。1950年，估计 DS患者的平均预期寿命为26岁，死亡时的中位年龄为4岁。与 改善对DS合并症的识别和治疗，如先天性心脏病 在缺陷方面，2010年估计的中位预期寿命为53岁（死亡时的中位年龄为58岁）。 现在有一个庞大而多样化的人口与DS在所有年龄谁是迫切需要的解决方案 以及治疗医学问题的方法，这在60年前是不可想象的。两个高利息的条件 这往往预示着其他疾病，极大地损害生活质量，并导致过早死亡， 阻塞性睡眠呼吸暂停（OSA）和痴呆。阻塞性睡眠呼吸暂停综合征是一种发作性的睡眠状态的崩溃， 导致睡眠期间通气减少或缺乏的气道， 有DS的人DS中21号染色体的三倍化与 淀粉样前体蛋白，是加速痴呆症和阿尔茨海默氏症发展的关键 疾病即使不是死亡的近端原因，在尸检中，几乎所有的老年人 患有DS的人有β淀粉样斑块和神经纤维缠结，这意味着阿尔茨海默病。更 需要了解这些情况的原因、过程以及社会决定因素的影响 以及由此导致的过早死亡，尤其是临床DS样品通常把握度不足， 缺少有色人种的参与者。为了满足美国国立卫生研究院的指示， 唐氏综合症项目和国家研究所在整个生命周期中共同发生的疾病 老龄化的优先事项，我们建议创造唐氏综合症：走向最佳轨迹和健康 使用Medicaid Analytic eXtract（DS-TO-THE-MAX）的公平性。DS-TO-THE-MAX将识别 回顾性纵向队列，包括10年来> 100，000例DS成人和> 4，000，000例无DS成人 年的Medicaid Analytic eXtract数据以及双重登记者的额外Medicare数据。我们的创新 在于DS样本的数量级大于过去的工作，健康的社会决定因素 框架，以及新的机器学习和定量偏差分析方法。我们将完成两个 目的：1）评估阻塞性睡眠呼吸暂停、痴呆和 死亡率2）使用机器学习来识别阻塞性睡眠呼吸暂停、痴呆和 mortality.该项目的结果将加强DS的流行病学和公共卫生基础 研究和人口一级的干预。在建立DS-TO THE MAX队列和评估风险时， 弹性，社会决定因素，我们将有一个重要的大数据集，以补充临床研究， 致力于使DS长寿、健康和自主生活的人群。

PROJECT ABSTRACT Down syndrome (DS), a trisomy of chromosome 21 and the most common genetic cause of intellectual disability, was once a condition in which children would rarely see adulthood. In 1950, the estimated mean life expectancy for a person with DS was 26 years and median age at death was 4 years. With improvements in recognition and treatment of co-occurring conditions of DS, such as congenital heart defects, the estimated median life expectancy in 2010 was 53 years (median age at death was 58). There is now a large and diverse population with DS across all ages who are in dire need of solutions and treatments for medical issues that were inconceivable 60 years ago. Two conditions of high interest that often presage other morbidity, greatly harm quality of life, and lead to premature mortality are obstructive sleep apnea (OSA) and dementia. OSA is an episodic sleep-state collapse of the upper airway which results in reduction or lack of ventilation during sleep and is prevalent in more than half of people with DS. The triplication of chromosome 21 in DS is associated with an overproduction of the amyloid precursor protein and is pivotal to the accelerated development of dementia and Alzheimer's disease. Even when not the proximal cause of death, in post-mortem autopsy nearly all older adults with DS have beta amyloid plaques and neurofibrillary tangles that signify Alzheimer's disease. More needs to be known about causes, course, and the impact of social determinants on these conditions and resulting premature mortality, especially as clinical DS samples are often under powered and often lack participants of color. To meet the directives of the National Institutes of Health's Investigation of Co-occurring conditions across the lifespan in Down syndrome project and the National Institute on Aging's priorities we propose to create Down Syndrome: Towards Optimal Trajectories and Health Equity using Medicaid Analytic eXtract (DS-TO-THE-MAX). DS-TO-THE-MAX will identify a retrospective longitudinal cohort of >100,000 adults with DS and >4,000,000 adults without DS from 10 years of Medicaid Analytic eXtract data plus additional Medicare data for dual enrollees. Our innovation lies in a DS sample orders of magnitude larger than past work, a social determinants of health framework, and novel machine learning and quantitative bias analysis methods. We will complete two aims: 1) Assess epidemiology and social determinants of obstructive sleep apnea, dementia, and mortality 2) Use machine learning to identify risk algorithms for obstructive sleep apnea, dementia, and mortality. The results of this project will strengthen the epidemiologic and public health basis for DS research and population level intervention. In building the DS-TO THE MAX cohort and assessing risk, resilience, social determinants we will have a vital big data set to complement clinical research and work toward the population with DS living long, healthy, and self-determined lives.