Genes, environments, interactions, and cognitive decline in the HRS

描述（由申请人提供）：HRS项目中的基因、环境、相互作用和认知下降总结：阿尔茨海默病（AD）是一种异质性疾病，具有潜在的广泛的环境和遗传风险因素。在AD发病之前，伴随着神经病理学的积累，会有一个很长的认知能力下降的临床前阶段。导航认知能力下降和功能障碍的许多途径需要一个多方面的方法，结合流行病学和遗传学。流行病学的作用是确定可改变的因素，可能降低AD的风险是至关重要的;遗传学在AD中的作用已被证明是非常复杂的。早期的研究确定了炎症途径中的基因和与压力相关的基因。虽然这些基因中的一些已经显示出环境相互作用的证据，但很少有人研究AD中的相互作用，也很少有人在全基因组关联研究（GWAS）中复制。相反，GWAS产生了影响相对较小的风险基因，其中许多与认知能力下降以及AD有关。我们建议研究AD风险基因，炎症途径基因，环境风险因素及其对认知能力下降的综合影响之间的相互作用。这种相互作用可以解释目前无法解释的AD患病率的一部分。健康与退休研究（HRS）的纵向数据加上新发布的来自11，000多名65岁及以上参与者的GWA数据，为以强有力的方式研究这些关联提供了理想的机会。使用潜在轨迹模型，我们将根据随着时间的推移的认知测试表现来定义个人群体。使用随机森林，我们将研究认知轨迹与AD风险基因，炎症基因，环境因素及其相互作用之间的关联。这种方法结合了复杂的方法，将使我们能够更详细地研究基因、环境及其相互作用之间的相互关系，因为它们影响认知能力下降的速度。

DESCRIPTION (provided by applicant): Genes, environments, interactions, and cognitive decline in the HRS Project Summary: Alzheimer's disease (AD) is a heterogeneous disease with a potentially wide range of contributing environmental and genetic risk factors. A long pre-clinical period of cognitive decline accompanies the accumulation of neuropathology and precedes the onset of AD. Navigating the many pathways to cognitive decline and dysfunction requires a multifaceted approach that incorporates both epidemiology and genetics. The role of epidemiology is crucial for identifying modifiable factors that may reduce AD risk; the role of genetics in AD has proven to be very complex. Early studies identified genes in the inflammatory pathways and genes associated with stress. Although some of these genes have shown evidence of environmental interactions, few have been investigated for interactions in AD and few have been replicated in genome wide association studies (GWAS). Instead, GWAS have yielded risk genes with relatively small effects, many of which have been tied to cognitive decline as well as AD. We propose to study interactions between AD risk genes, genes from the inflammatory pathway, environmental risk factors, and their combined influence on cognitive decline. Such interactions could explain a portion of AD prevalence that is currently unexplained. The Health and Retirement Study (HRS) longitudinal data coupled with newly released GWA data from over 11,000 participants age 65 and older provides an ideal opportunity to study these associations in a powerful way. Using latent trajectory models, we will define groups of individuals based on cognitive test performance over time. Using random forests, we will study the associations between cognitive trajectories and AD risk genes, inflammation genes, environmental factors, and their interactions. This approach, combining complex methods, will allow us to study in greater detail the interrelationships between genes, environments, and their interactions as they influence the rate of cognitive decline.