Urban Air Pollution and Pathological Brain Aging: A Nationwide Twin Study in Men

大量证据表明，暴露在室外空气污染物中可能会加速认知老化。 来自动物模型的新数据也表明阿尔茨海默病(AD)的风险可能会增加。 以及暴露于交通相关空气污染物(陷阱)的相关痴呆症。诱捕表演的动物模型 强烈的神经毒性证据，但现有的关于TRAP对人脑老化的神经毒性作用的研究 重要知识差距：1)长期地址历史数据很少；2)晚些时候之前关于曝光影响的数据很少 生活；3)有限的认知数据，特别是轻度认知障碍(MCI)或AD；4)有限的神经成像 措施；5)没有检查潜在的混杂早期生活因素：6)对老年人的研究主要是 7)需要更好地了解基因与环境的相互作用。项目2，建立在NIA的基础上- 资助的越南时代纵向老龄化双胞胎研究(Vetsa；R01 AG018386和AG022381)，适用于 解决这些差距。它包括维萨1号(n=1291)和维萨2号55-66岁的男性双胞胎，年龄在51-60岁 1205例。Vetsa是一个来自49个州的地理多样化的队列，在Trap中提供了很大的变异性 曝光。受试者每人有10-12小时的神经心理、心理社会和健康/医学数据 时间点：545和447分别在Vetsa 1和2进行结构磁共振成像(MRI)。我们 将通过收集1993年以来的住宅历史数据并对其进行地理编码，并与 环境暴露核心C，创建陷阱的累积指数。然后，我们将能够直接解决 差距2-7。捕集器的特征将是环境中NO2(一种气体替代品)的估计水平， PM2.5(柴油尾气颗粒物的标志)的元素碳(EC)成分和预测的来源分布 PM2.5。Vetsa受试者的年龄是在晚年之前检验陷阱效应的理想年龄。我们研究了 目的：目的1.评估陷阱对脑结构/功能的影响：主要影响。我们预测陷阱 暴露将与较高的AD相关脑信号评分、脑低灌注(平行)相关 鼠标计划4)，以及白质高信号。接触陷阱将与认知能力较差有关 功能和更大的认知能力随着时间的推移而下降。目标2.评估陷阱对认知和心理健康的影响 脑老化：调解。我们将考察陷阱和认知的具体测量之间的联系 重点关注情景记忆、执行功能和处理速度，以及其通过特定的调节 大脑测量。脑微结构的弥散张量成像(DTI)指标在 先前的研究。我们将检查内侧颞叶和额叶的灰质和白质的平均弥散率。 地区。目的3.研究基因与环境(GE)的相互作用。3A)我们假设不利的陷阱 对大脑和认知功能下降的影响将因载脂蛋白E-ε4和AD的多基因风险评分而不同， 炎性处理和tau代谢/处理。3b)我们将使用MZ对内差异分析 作为阐明遗传和环境影响如何协同工作的另一种方法。

Substantial evidence indicates that exposure to outdoor air pollutants may accelerate cognitive aging. Emerging data from animal models also point to a possible increase in the risk of Alzheimer's disease (AD) and related dementias with exposure to traffic-related air pollutants (TRAP). Animal models of TRAP show strong evidence of neurotoxicity, but existing studies of neurotoxic effects of TRAP on human brain aging have important knowledge gaps: 1) little long-term address history data; 2) little data on exposure effects before late life; 3) limited data on cognition, particularly mild cognitive impairment (MCI) or AD; 4) limited neuroimaging measures; 5) no examination of potential confounding early-life factors: 6) studies of older adults mostly on women; and 7) need for better understanding of gene-environment interactions. Project 2, built on the NIA- funded longitudinal Vietnam Era Twin Study of Aging (VETSA; R01 AG018386 & AG022381), is ideal for addressing these gaps. It includes male twins ages 51-60 at VETSA 1 (n=1291) and 55-66 at VETSA 2 (n=1205). VETSA is a geographically-diverse cohort from 49 states, offering great variability in TRAP exposure. Subjects have 10-12 hours of neuropsychological, psychosocial, and health/medical data at each timepoint; 545 and 447 have structural magnetic resonance imaging (MRI) at VETSA 1 and 2, respectively. We will address gap #1 by collecting and geocoding residential history data back to 1993, and in conjunction with Environmental Exposures Core C, create cumulative indices of TRAP. We will then be able to directly address gaps 2-7. TRAP will be characterized by the estimated ambient levels of NO2 (a gaseous surrogate), elemental carbon (EC) component of PM2.5 (a marker of diesel exhaust particle), and predicted source profiles of PM2.5. The age of VETSA subjects is ideal for examining TRAP effects before late life. We examine the following aims: Aim 1. Assess TRAP effects on brain structure/function: Main effects. We predict TRAP exposure will be associated with higher AD-related brain signature scores, cerebral hypoperfusion (paralleling Mouse Project 4), and white matter hyperintensities. TRAP exposure will be associated with poorer cognitive function and greater cognitive decline over time. Aim 2. Assess the impact of TRAP on cognitive and brain aging: Mediation. We will examine associations between TRAP and specific measures of cognition with a focus on episodic memory, executive function, and processing speed, as well its mediation by specific brain measures. Diffusion tensor imaging (DTI) indices of brain microstructure have not been examined in prior studies. We will examine mean diffusivity in both grey and white matter in medial temporal and frontal regions. Aim 3. Examine gene-environment (GE) interaction. 3a) We hypothesize that adverse TRAP effects on brain and cognitive decline will differ as a function of APOE-ε4, and polygenic risk scores for AD, inflammatory processing, and tau metabolism/processing. 3b) We will use MZ within-pair difference analysis as another approach to shed light on how genetic and environmental influences work in tandem.