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、相互作用和认知能力下降摘要：阿尔茨海默病(AD)是一种具有潜在广泛的环境和遗传风险因素的异质性疾病。长期的临床前认知衰退伴随着神经病理学的积累，并先于AD的发病。要找到导致认知衰退和功能障碍的多种途径，需要一种结合了流行病学和遗传学的多方面方法。流行病学的作用对于确定可能降低AD风险的可改变因素至关重要；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应激相关的基因。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的相互作用，也很少有基因在全基因组关联研究中被复制。相反，Gwas已经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和阿尔茨海默病有关。我们建议研究AD风险基因、炎症途径基因、环境风险因素之间的相互作用，以及它们对认知功能下降的联合影响。这种相互作用可以解释AD流行的一部分，但目前尚不清楚。健康和退休研究(HRS)的纵向数据，加上最近发布的来自超过11,000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一个理想的机会。使用潜在轨迹模型，我们将基于随时间推移的认知测试表现来定义个体组。利用随机森林，我们将研究认知轨迹与AD风险基因、炎症基因、环境因素以及它们之间的相互作用之间的关系。这种方法，结合复杂的方法，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，因为它们影响认知衰退的速度。

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.