Systems Control of Normal Aging and Alzheimer's Disease

阿尔茨海默氏病（AD）是最常见的痴呆形式，在美国影响超过500万人。 States.绝大多数病例是迟发性AD（LOAD）的结果，其发作具有广泛的变异性， 在人群中的进展和严重程度。我们认为，正常的衰老和AD记忆衰退导致 从共同的分子途径;因此，我们预计，遗传因素的识别和 正常衰老的潜在机制将为AD的干预提供可行的靶点。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异质性的阻碍， 退化性变化，人类群体中可能存在的众多环境混乱，以及 在临床前和/或早期阶段从人类获得分子和功能数据的困难 疾病遗传参考组，例如小鼠的BXD组，模拟了遗传复杂性的一部分。 同时控制环境因素。我们将使用BXD面板来识别 遗传因素和机制，修改的发病和严重程度的记忆衰退。我们将测量 在我们的BXD小组中，他们的寿命（6，12和18个月）的记忆功能，并执行随后的遗传 连锁作图，以鉴定与疾病进展相关的基因组区域。我们假设 多种基因变异通过改变海马蛋白的表达来调节记忆力下降 因此，我们还将定量评估海马体中的蛋白质水平， 在认知衰退中表现出极端变化的BXD菌株中的寿命（即易感和弹性菌株; 底部和顶部10%）。将选择候选风险和保护因素进行正常情况下的功能确认 使用序列数据的衰老和AD小鼠模型，来自年龄匹配品系的现有海马mRNA， 以及大量的生物信息学资源。初步研究表明，参与表达 调节神经元兴奋性的海马膜蛋白（例如，Hp 1bp 3、Trpc 3）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，在本发明中， 将通过操纵基因序列测试多达5个新的候选基因（与Hp 1bp 3、Trpc 3一起），或 分别使用基因组编辑构建体或siRNA的病毒递送进行表达，并测量效果 使用已建立的AD模型，对AD的认知衰退、神经生理学变化和神经病理学标志物进行研究， 相关的小鼠模型和年龄匹配的对照。新的遗传因素和机制的鉴定 记忆力下降的研究将是发展机械治疗和 个性化的基因疗法，可以维持老年人的认知功能。的识别 预测性遗传变异或神经生理学生物标志物也将具有巨大的潜力， 为AD患者的早期检测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.