Effect of Genetic, Individual & Neighborhood Factors on Telomere Length

描述（由申请人提供）：现为一名进入流行病学学位论文阶段的博士生申请此培训补助金。候选人立志成为老龄化研究领域的杰出独立科学家。她将在博士期间把100%的时间投入到这项研究中。她在论文阶段的实践训练，加上精心挑选的课程，旨在使她成为使用先进统计方法来定义个体和邻近因素，遗传变异和端粒长度之间关系的专家。这种双重训练方法将为她未来的研究做准备，研究与衰老相关的分子标记，以及社区环境和遗传学在健康差异和衰老中的作用。在整个获奖过程中，她将受到行为学、地理空间分析、衰老结果、遗传学、分子标记和生物统计学方面的资深专家的指导。以端粒长度衡量的细胞衰老过程，可能是在生命周期中多种因素的复杂相互作用下发生的。本文提出的研究目标是利用代生物标志物端粒长度更好地解释细胞衰老的复杂、多因素性质。我们将采用多层次的统计方法，包括在现有的多种族老年男性纵向队列中确定影响端粒长度的个体水平（目标1）和社区水平因素（目标2）以及端粒遗传变异和端粒长度之间的关系（目标3）。据报道，端粒长度与遗传变异、个人危险行为（吸烟、体重指数）和社会人口统计学变量（个人的种族、性别、社会地位）之间存在关联。然而，社区层面的因素（社会孤立、结构性衰退、暴力等）是老龄化研究的一个重要考虑因素，因为它们与年龄相关的疾病有关，对可能长期生活在不利社区的老年人尤其重要。这是第一个解释多种因素对端粒长度的集体影响的研究。使用线性回归和反向回归，申请人将基线端粒长度（由T/S比率定义）建模为连续变量，具有个体水平测量，并选择单独输入的邻近因素作为自变量，使用p值0.20作为纳入的阈值。分析将按种族重复分层。当评估邻域变量对端粒长度的影响时，将考虑聚类和多重共线性。为了测试遗传单倍型在邻近环境中的影响，我们将使用多变量分析来模拟目标1和目标2中确定的端粒长度和协变量向量。如果基因或个体风险因素在某些社区环境中更深刻地影响端粒长度，这种性质的研究是至关重要的。本研究将建立一个概念模型的基础，可作为未来老龄化研究的基础。

DESCRIPTION (provided by applicant): This training grant is being sought by a PhD student entering the dissertation phase of her degree in Epidemiology. The candidate aspires to become a leading independent scientist in the field of aging research. She will devote 100% of her time to this research for the duration of her PhD. Her hands-on training during her dissertation phase, coupled with carefully selected courses, are designed to make her expert in the use of advanced statistical methods to define associations between individual and neighborhood factors, genetic variants, and telomere length. This dual training approach will prepare her for future studies investigating molecular markers associated with aging and the role neighborhood environment and genetics play in health disparities and aging. Throughout this award, she will be mentored by senior experts in behavior, geospatial analyses, aging outcomes, genetics, molecular markers and biostatistics. The process of cellular aging, as measured by telomere length, likely occurs through the complex interactions of multiple factors over the lifespan. The goal of the research proposed here is to better explain the complex, multifactorial nature of cellular aging using a surrogate biomarker, telomere length. We will undertake a multilevel statistical approach that includes identifying individual-level (Aim 1) and neighborhood- level factors (Aim 2) that affect telomere length and the relationship between telomere genetic variants and telomere length (Aim 3), in an existing multi-ethnic longitudinal cohort of older men. Associations have been reported between telomere length and genetic variants, individual risk behaviors (smoking, body mass index) and sociodemographic variables (an individual's race, sex, social status). However, neighborhood level factors (social isolation, structural decline, violence, etc) represent an important consideration for aging studies since they have been associated with age-related disease and are particularly relevant for older adults, who may live in unfavorable neighborhoods for long time periods. This is the first study to account for the collective effects of multiple factors on telomere length. Using linear regression and backward regression, the applicant will model baseline telomere length (defined by T/S ratio) as a continuous variable, with individual level measures, and select neighborhood factors entered separately as independent variables, using a p-value of 0.20 as the threshold for inclusion. Analyses will be repeated stratifying by race. Clustering and multicollinearity will be considered when assessing the effect of neighborhood variables on telomere length. In order to test the effects of genetic haplotypes in the neighborhood context, we will use multivariable analysis to model telomere length and a vector of covariates identified in Aims 1 and 2. Studies of this nature are critical if genes or individual risk factors affect telomere length more profoundly in certain neighborhood settings. This study will build the foundations of a conceptual model that can be used as the basis for future studies on aging.