Effect of Genetic, Individual & Neighborhood Factors on Telomere Length

描述（由申请人提供）：此培训补助金正在寻求由博士生进入她的学位在流行病学的论文阶段。候选人渴望成为老龄化研究领域的领先独立科学家。她将在博士期间投入100%的时间进行这项研究。她在论文阶段的实践培训，加上精心挑选的课程，旨在使她在使用先进的统计方法来定义个人和邻里因素，遗传变异和端粒长度之间的关联专家。这种双重训练方法将为她未来的研究做好准备，研究与衰老相关的分子标记物，以及邻里环境和遗传学在健康差异和衰老中的作用。在整个奖项中，她将由行为，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高级专家指导。 细胞衰老的过程，如端粒长度所测量的，可能是通过生命周期中多种因素的复杂相互作用而发生的。这项研究的目的是使用替代生物标志物端粒长度来更好地解释细胞衰老的复杂性和多因素性。我们将采取多层次的统计方法，包括确定影响端粒长度的个体水平（目标1）和邻域水平因素（目标2）以及端粒遗传变异与端粒长度之间的关系（目标3），在现有的多种族纵向队列老年男性。端粒长度与遗传变异、个体风险行为（吸烟、体重指数）和社会人口变量（个体的种族、性别、社会地位）之间存在关联。然而，社区水平的因素（社会隔离，结构性衰退，暴力等）代表了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，特别是与老年人有关，他们可能长期生活在不利的社区。这是第一个解释多种因素对端粒长度的集体影响的研究。使用线性回归和后向回归，申请方将基线端粒长度（由T/S比定义）建模为连续变量，采用个体水平测量，并选择单独输入的邻域因子作为自变量，使用p值0.20作为入选阈值。分析将按种族重复分层。当评估邻近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域背景下的影响，我们将使用多变量分析来建模端粒长度和目标1和2中确定的协变量向量。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，则这种性质的研究至关重要。这项研究将建立一个概念模型的基础，可以作为未来研究的基础上老化。

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.