Defining the Healthy Aging Phenotype

描述(由申请人提供)：夏威夷寿命研究将集中一个由遗传学、流行病学、行为和生物人口学科学家组成的多学科团队，使用创新的方法进行二次数据分析。我们将使用现有的人类纵向数据和来自火奴鲁鲁心脏计划(HHP)40多年数据集的样本，这些数据来自世界上最长寿、最健康的少数民族之一。这项研究将重点研究健康老龄化在整个生命周期内的功能特征，并确定使人们能够健康地活到特殊年龄的生物学和行为因素。我们的研究直接支持了NIA改善美国老年人健康和福祉的使命。虽然“成功”、“健康”或“有效”衰老等术语描述了一种慢性病最少的衰老模式，但人们对这种衰老的功能(生理、认知、心理社会)特征知之甚少。因此，我们将1)确定生活在美国男性队列寿命表上5%以上的特殊幸存者(ES)的“健康老龄化”表型的患病率；2)确定与中年或老年早期的胰岛素/IGF-1相关的生物、行为和/或心理社会危险因素是否预测ES表型；3)确认并扩展我们的初步发现，即在进化上保守的代谢途径中，胰岛素/IGF-1信号通路中的基因变异(SNPs)与ES表型相关；以及4)通过应用生物统计学方法来检测和量化ES生命过程中的差异，这些方法使用发病率/死亡率的时间事件数据。为了实现这些目标，我们将在这一独特的数据集中进行基因分析，并将通过使用日本SNP数据库(JSNP)的SNP基因分型来补充这些分析。对健康衰老机制的更大研究将有助于我们理解保护性遗传和环境特征是如何导致健康衰老和特殊生存的。如果发现的遗传和/或环境特征有很大可能延缓或减少增加疾病和残疾易感性的与年龄有关的变化，将对我们通过延缓或预防与年龄有关的疾病实现健康晚年的能力产生重大影响。

DESCRIPTION (provided by applicant): The Hawaii Lifespan Study will focus a multidisciplinary team of genetic, epidemiological, behavioral and biodemographic scientists on the use of innovative approaches for secondary data analysis. We will use existing human longitudinal data and specimens from the 40+ year Honolulu Heart Program (HHP) dataset from one of the longest-lived, healthiest, minority populations in the world. This study will focus on functional characteristics of healthy aging over the lifespan and identify biological and behavioral factors that enable people to survive to exceptional ages in good health. Our study directly supports NIA's mission to improve the health and well-being of older Americans. While terms such as "successful", "healthy" or "effective" aging describe a paradigm of aging with minimal chronic disease, the functional (physical, cognitive, psychosocial) characteristics of such aging are poorly understood. Therefore, we will 1) determine the prevalence of the "healthy aging" phenotype for exceptional survivors (ES) who have lived to the upper 5% of the U.S. male cohort life table; 2) determine whether biological, behavioral, and/or psychosocial risk factors linked to insulin/IGF-1 in midlife or early elder life predict ES phenotypes; 3) confirm and extend our preliminary findings that gene variants (SNPs) in evolutionarily conserved metabolic pathways in the insulin/IGF-1 signaling pathway are associated with ES phenotypes; and 4) detect and quantify differences in the life course pathway to ES by applying biodemographic methods that use time to event data for morbidity/mortality. To accomplish these goals we will conduct genetic analyses in this unique dataset and will complement these analyses through SNP genotyping using the Japanese SNP database (JSNP). A greater research effort on the mechanisms of healthy aging will help us understand how protective genetic and environmental traits lead to healthy aging and exceptional survival. Discovery of genetic and/or environmental traits that have significant potential to delay or minimize the age-related changes that increase vulnerability to disease and disability would have a dramatic impact on our ability to achieve healthy old age by delaying or preventing age-associated disease.