Systems Control of Normal Aging and Alzheimer's Disease

阿尔茨海默病(AD)是痴呆症最常见的形式，在美国有500多万人受到影响 各州。绝大多数病例是迟发性阿尔茨海默病(负荷)的结果，其发病具有很大的变异性， 在整个人口中的进展和严重性。我们假设正常衰老和AD记忆衰退的结果 从共同的分子途径；因此，我们预计遗传因素和 正常衰老的机制将为干预AD提供可行的靶点。身份识别 人类遗传风险因素和机制的研究在很大程度上受到已知的 退化的变化，人类队列中可能存在的众多环境混乱，以及 在临床前和/或早期阶段难以从人类获得分子和功能数据 疾病。遗传参照组，如小鼠的BXD组，模拟了一部分遗传复杂性 在控制环境因素的同时，对人口数量进行控制。我们将使用BXD面板来确定 改变记忆衰退开始和严重程度的遗传因素和机制。我们将衡量 我们的BXD面板在其寿命(6、12和18个月)中具有记忆功能，并执行后续的遗传 连锁作图，以确定与疾病进展相关的基因组区域。我们假设 多个基因变体通过改变海马区蛋白的表达来调节记忆减退 对记忆是必要的，所以我们还将定量评估 在认知衰退方面表现出极端变异的BXD品系的寿命(即敏感和有弹性的品系； 最低和最高10%)。将选择候选风险和保护因素在正常情况下进行功能验证 使用序列数据建立衰老和阿尔茨海默病小鼠模型，来自年龄匹配品系的现有海马区mRNA， 和大量的生物信息学资源。初步研究表明，候选人参与表达 调节神经元兴奋性的海马膜蛋白(如HP1BP3，TRPC3)有助于 认知老化的个体差异，也可能影响AD的发展和进展。因此， 最多5个新的候选基因(与HP1BP3，TRPC3一起)将通过操纵基因序列或 分别使用基因组编辑构建体或siRNA的病毒传递进行表达，并测量其效果 阿尔茨海默病认知功能减退、神经生理改变及神经病理标志物的研究 相关的小鼠模型和年龄匹配的对照。新的遗传因素和遗传机制的鉴定 记忆力减退将是发展基于机械的治疗方法和 个性化的基因疗法将维持老年人的认知功能。身份的鉴定 预测性遗传变异或神经生理学生物标记物也将具有巨大的潜力 为AD患者的早期发现和更有效的治疗提供生物标志物。

Alzheimer’s disease (AD), the most common form of dementia, affects over five million people in the United States. A vast majority of cases are the result of late-onset AD (LOAD), which has a wide variability in onset, progression, and severity across the population. We posit that normal aging and AD memory decline result from common molecular pathways; therefore, we expect that the identification of genetic factors and mechanisms underlying normal aging will provide feasible targets for intervention against AD. The identification of genetic risk factors and mechanisms in humans has been impeded largely by the known heterogeneity of degenerative changes, the numerous environmental confounds that can exist in human cohorts, and the difficulty in obtaining molecular and functional data from humans at the preclinical and/or early stages of disease. Genetic reference panels, such as the BXD panel of mice, model a portion of the genetic complexity of human populations while controlling for environmental factors. We will use the BXD panel in order to identify genetic factors and mechanisms that modify the onset and severity of memory decline. We will measure memory function in our BXD panel across their lifespan (6, 12, and 18 mo) and perform subsequent genetic linkage mapping in order to identify genomic areas that correlate to disease progression. We hypothesize that multiple gene variants modulating memory decline do so by altering expression of hippocampal proteins necessary for memory, so we will also quantitatively evaluate protein levels in the hippocampus across the lifespan in BXD strains that exhibit extreme variation in cognitive decline (i.e. susceptible and resilient strains; bottom and top 10%). Candidate risk and protective factors will be selected for functional validation in normal aging and AD mouse models using sequence data, existing hippocampal mRNA from age-matched strains, and numerous bioinformatics resources. Pilot studies suggest candidates involved in expression of hippocampus membrane proteins that modulate neuronal excitability (e.g. Hp1bp3, Trpc3) contribute to individual differences in cognitive aging, and may also impact the development and progression of AD. Thus, up to 5 novel candidate genes (alongside Hp1bp3, Trpc3) will be tested by manipulating gene sequence or expression using viral delivery of genome editing constructs or siRNA, respectively, and measuring the effect on cognitive decline, neurophysiological changes and neuropathological markers of AD using established AD- related mouse models and age-matched controls. The identification of novel genetic factors and mechanisms of memory decline will be a critical first step toward the development of both mechanistic-based treatments and personalized gene therapies that would maintain cognitive function in elderly humans. The identification of predictive genetic variants or neurophysiological biomarkers would also have the tremendous potential to provide biomarkers for earlier detection and more effective treatment in AD patients.