Genetic Modulations of Morbidity Compression: A Population-Based Study

 描述(申请人提供)：在过去的一个世纪里，人类的寿命稳步增长。然而，有很大的不确定性，关于这在多大程度上伴随着发病率的压缩。鉴于目前医疗保健费用的急剧上升，特别是生命最后6个月的费用，这个问题对社会具有深远的重要性。全国长期护理调查(NLTCS)是一项以联邦医疗保险为基础的美国65岁以上人口样本，始于1982年，在1984、1989、1994、1999和2004年进行了纵向跟踪，与1982-2009年的联邦医疗保险索赔和重要统计数据以及符合条件的联邦医疗补助文件(即2004-2007年MAX文件)相关联，并补充了1999-2009年的MDS和OASIS文件。1982-1994年NLTCS首次报告了通过NLTCS人群的日常生活能力(ADL)和工具性ADL(IADL)得分评估的功能健康的重大改善。1999年的NLTCS大大扩大了其范围，在2000-2002年选择了1,877名参与者和869名兄弟姐妹进行补充数据收集，产生了639份血液(仅限参与者)和2,078份口腔拭子样本(参与者和兄弟姐妹)，用于基因研究。此外，在参与生物监测样本的1,808名NLTCS参与者中，有1,345人在2004年NLTCS时还活着，1,183人接受了重新评估。共有1,031名参与者最初年龄在85岁以上(429人)或在2000-2010年后续行动期间达到85岁(602人)，截至2010年截止日期，共有717人仍然健在。生物样本目前提供了13,303人年的随访数据，其中5,098人年的年龄在85岁以上。我们建议利用这种独特的基于人群的样本、其相关的功能数据、相关联的Medicare/Medicaid索赔数据和DNA样本，来量化发病率压缩的不同程度，并测试体质遗传因素有助于调节这些不同的健康寿命/寿命比率的假设。我们将首先讨论长寿、合并症、功能健康(ADL/IADL)和生理和认知功能衰退之间的联系(目标1)。然后，我们将对639个血液样本和2078个口腔拭子样本进行SNP阵列分析，以获取和评估广泛的遗传信息(目标2)。我们将评估长期健康寿命的表型与两个高度相关的耦合基因网络--胰岛素/IGF1信号转导(包括。FOXO3a和IGFR)和mTOR途径--与不同物种的衰老和长寿有关(目标3)。然后，鉴于已发表的全基因组杂合性与心血管健康的关联(Campbell等人，2007年)，我们将寻求这种关联与发病率压缩程度(目标4)。此外，考虑到项目数据的科学价值，我们将使用CMS、NIA和Duke IRB批准的协议，发布额外年份的去识别CMS数据(AIM 5)和来自我们的SNP阵列分析的去识别版本的基因/表型数据(AIM 6)。我们将使用来自健康和退休研究(HRS)的数据，采用可比较的表型和基因类型测量方法以及相关的CMS数据来复制/验证我们的结果。

 DESCRIPTION (provided by applicant): Human longevity steadily increased over the past century. There is great uncertainty, however, regarding the extent to which this was accompanied by the compression of morbidity. Given current dramatic increases in health care costs, especially costs during the last 6 months of life, this question is of profound importance t society. The National Long Term Care Survey (NLTCS) is a Medicare-based sample of the U.S. population aged 65+ initiated in 1982 with longitudinal follow-up in 1984, 1989, 1994, 1999, and 2004, with complete linkage to Medicare claims and vital statistics data for 1982-2009, and for eligible participants to Medicaid files (i.e., the 2004-2007 MAX files), supplemented with the 1999-2009 MDS and OASIS files. The 1982-1994 NLTCS produced the first reported major improvements of functional health as assessed by Activities of Daily Living (ADL) and Instrumental ADL (IADL) scores within the NLTCS population. The 1999 NLTCS substantially expanded its scope by selecting 1,877 participants and 869 siblings for supplemental data collection in 2000- 2002, yielding 639 blood (participants only) and 2,078 buccal swab (participants and siblings) samples for genetic studies. Moreover, of the 1,808 NLTCS participants contributing to the biospecimen sample, 1,345 were alive at the 2004 NLTCS and 1,183 were re-assessed. A total of 1,031 participants were age 85+ initially (429) or attained age 85 during the 2000-2010 follow-up period (602), with a total of 717 still alive as of the cutof date in 2010. The biospecimen sample currently provides 13,303 person-years of follow-up data, with 5,098 person-years above age 85. We propose to utilize this unique population-based sample, its associated functional data, linked Medicare/Medicaid claims data, and DNA samples, to quantitate variable degrees of the compression of morbidity and to test the hypothesis that constitutional genetic factors contribute to the modulation of these differential ratios of healthspans/lifespans. We will first address the connections between longevity, co-morbidity, functional health (ADL/IADL), and declines of physiological and cognitive functions (Aim 1). We will then conduct SNP array analysis of 639 blood and 2,078 buccal swab samples to obtain and assess a wide range of genetic information (Aim 2). We will assess associations of phenotypes of long healthy life with candidate polymorphisms within two highly relevant coupled gene networks-Insulin/IGF1 signaling (incl. FOXO3A and IGFR) and mTOR pathways-linked to aging and longevity across different species (Aim 3). Then, given published associations of genome-wide heterozygosity with cardiovascular health (Campbell et al., 2007), we will seek such associations with degrees of morbidity compression (Aim 4). Also, given the scientific value of the project data, we will release additional years of de-identified CMS data (Aim 5) and de- identified versions of the genotypic/phenotypic data derived from our SNP array analysis (Aim 6), using CMS, NIA, and Duke IRB approved protocols. We will replicate/validate our results using data from the Health and Retirement Study (HRS), employing comparable phenotypic and genotypic measures and linked CMS data.