Neural network and immune cell dysfunctions in Alzheimer's disease pathogenesis

阿尔茨海默病发病机制中的神经网络和免疫细胞功能障碍

• 批准号: 10077445
• 负责人: Lennart Mucke
• 金额: $ 47.25万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10077445
• 关键词: Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease patient; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-Protein; Amyloid beta-Protein Precursor; Antiepileptic Agents; Biological Markers; Brain; Brain region; Cells; Chemicals; Cognitive deficits; Data; Development; Disease; Disease Progression; Electroencephalography; Epilepsy; Excitatory Neurotoxins; Functional disorder; Genes; Genetic; Histopathology; Human; Human Amyloid Precursor Protein; Immune; Immune System Diseases; Immune response; Immune system; Immunologic Markers; Impaired cognition; Impairment; Inflammation Mediators; Inflammatory; Injury; Knock-in; Knock-in Mouse; Knowledge; Learning; Levetiracetam; Light; Link; Mediating; Memory; Microglia; Missense Mutation; Modeling; Molecular; Morphology; Mouse Protein; Mus; Mutation; Myeloid Cells; Nerve Degeneration; Neurofibrillary Tangles; Neuronal Dysfunction; Neurons; Pathogenesis; Pathogenicity; Pathologic; Pathology; Patients; Peripheral; Peripheral Blood Mononuclear Cell; Persons; Plasma; Predisposition; Prevention; Research; Research Project Summaries; Risk; Role; Seizures; Senile Plaques; Solid; Synapses; TREM2 gene; Testing; Therapeutic; Time; Transgenic Mice; Variant; abeta accumulation; base; brain abnormalities; brain cell; cytokine; density; genetic variant; genome wide association study; immune activation; improved; mouse model; network dysfunction; neural circuit; neural network; novel; novel therapeutics; peripheral blood; pre-clinical; preservation; radiological imaging; reduce symptoms; response; risk variant; synaptic function; targeted treatment; tau Proteins; transcriptome; transcriptomics

PROJECT SUMMARY Research on Alzheimer’s disease (AD) has strongly focused on pathological alterations detectable by histopathology or radiological imaging such as plaques and tangles. However, drug treatments targeting these alterations have not slowed cognitive decline in AD patients despite clear evidence for target engagement in the brain. Efforts to discover biomarkers for AD have also focused primarily on neuropathological alterations. To pursue novel directions and fill important knowledge gaps in the field, this proposal focuses on functionally relevant neural network abnormalities that likely underlie cognitive deficits and could promote neurodegeneration and AD progression through diverse mechanisms, including dysfunction of microglia, the innate immune cells of the brain. Previously, we found subclinical epileptic activity in patients with AD and in related mouse models. In the patients, the extent of such network abnormalities predicted cognitive decline. In the mouse models, prevention or reversal of the network dysfunction improved survival and reduced cognitive deficits. More recently obtained preliminary data suggest a novel pathogenic link between network and immune cell dysfunction. Suppressing epileptic activity reduced microglial activation in mice with elevated amyloid-b (Ab) levels in the brain. Knock-in mice with microglial dysfunction, induced by a human immune gene variant that increases AD risk, had increased and prolonged epileptic activity after challenge with an excitotoxin. Nonconvulsive epileptic activity in mice with Ab accumulation in the brain correlated with levels of specific inflammatory mediators in plasma. Based on these intriguing findings, we propose to test the novel and unifying hypothesis that aberrant neural network activity and immune dysfunction engage in a vicious cycle that promotes synaptic loss, the likeliest cause of cognitive decline in AD. Conceivably, either of these components can initiate the cycle, possibly at different times in different patients and in response to diverse triggers, including injury-induced surges in amyloid-b (Ab) or tau levels and aging-related alterations. Which of the components is triggered first may depend on a person’s genetics, including genes affecting microglial functions. We will use AD-related mouse models to begin to test these hypotheses at the preclinical level. Specifically, we will determine whether (1) suppression of neural network abnormalities reduces aberrant microglial activation and preserves synaptic density, (2) network dysfunction and synaptic deficits are reflected by immune markers in peripheral blood, and (3) microglial dysfunction contributes to aberrant network activity and synaptic loss. The proposed studies will help delineate the role of immune cells in AD-related network dysfunction and synaptic impairment. They may also identify potential new biomarkers, such as EEG signatures and peripheral blood alterations, and could help identify therapeutic strategies to modulate immune cell activities that may ultimately benefit patients with AD and people at risk of developing this disorder.

项目概要 阿尔茨海默病 (AD) 的研究重点关注可通过以下方式检测到的病理改变： 然而，组织病理学或放射学成像，例如斑块和缠结，针对这些的药物治疗。 尽管有明确的证据表明 AD 患者的目标参与度有所改变，但这些改变并没有减缓 AD 患者的认知能力下降。 发现 AD 生物标志物的努力也主要集中在神经病理学改变上。 追求新颖的方向并填补该领域的重要知识空白，该提案侧重于功能 相关的神经网络异常可能导致认知缺陷并可能促进神经退行性变 AD 的进展通过多种机制进行，包括小胶质细胞的功能障碍，小胶质细胞是人体的先天免疫细胞。 此前，我们在 AD 患者和相关小鼠模型中发现了亚临床癫痫活动。 在小鼠模型中，这种网络异常的程度预示着患者的认知能力下降。 最近，预防或逆转网络功能障碍可以提高生存率并减少认知缺陷。 获得的初步数据表明网络和免疫细胞功能障碍之间存在新的致病联系。 抑制癫痫活动可减少淀粉样蛋白-b (Ab) 水平升高的小鼠的小胶质细胞活化 敲入小鼠的小胶质细胞功能障碍是由人类免疫基因变异引起的，该变异会增加 AD 的发生。 风险，在使用非惊厥性癫痫药物后，癫痫活动增加且延长。 大脑中抗体积累的小鼠的活动与特定炎症介质的水平相关 基于这些有趣的发现，我们建议测试异常的新颖且统一的假设。 神经网络活动和免疫功能障碍陷入恶性循环，促进突触损失， 可以想象，这些因素中的任何一个都可能引发 AD 认知能力下降。 在不同患者的不同时间以及对不同触发因素的反应，包括损伤引起的激增 淀粉样蛋白-b (Ab) 或 tau 蛋白水平以及与衰老相关的变化可能取决于哪个成分首先被触发。 我们将使用 AD 相关的小鼠模型来研究一个人的遗传学，包括影响小胶质细胞功能的基因。 具体来说，我们将在临床前水平上开始检验这些假设，以确定是否（1）抑制。 神经网络异常减少异常的小胶质细胞激活并保留突触密度，(2) 网络 外周血中的免疫标记物反映了功能障碍和突触缺陷，以及（3）小胶质细胞 功能障碍会导致网络活动异常和突触丢失。拟议的研究将有助于描述。 他们还可能确定免疫细胞在 AD 相关网络功能障碍和突触损伤中的作用。 潜在的新生物标志物，例如脑电图特征和外周血改变，可以帮助识别 调节免疫细胞治疗活动的策略可能最终使 AD 患者和人类受益 有患这种疾病的风险。