Assess Neural Circuits and Subtypes Underlying Dimensions of Neuropsychiatric Symptoms in Alzheimer's Disease

项目摘要 神经精神症状(NPS)通常见于轻度认知障碍或 阿尔茨海默病(AD)痴呆。这些症状在AD病程中影响高达97%的患者 可能会导致认知功能加速下降和转化为痴呆症。尽管付出了无数的努力 一直致力于研究NPS的病因学，这是AD痴呆NPS背后的神经生物学基础 目前仍不清楚。迫切需要推进对这些症状的机械性理解，这是 对于早期发现和及时干预以防止AD进展至关重要。越来越多的证据表明 这种不同的NPs基本上是重叠的，与不同大脑网络中的功能障碍有关。 因此，从维度上评估NPS及其相关的电路级故障将提供重要的 有助于加深我们对神经回路参与神经递质表达的理解。为回应这一事件 根据PAR-20-159的指南，该项目的总体目标是评估神经回路并确定 痴呆NPS基本维度的神经生理亚型(即亚型)。我们假设 神经回路的不同模式将反映NPS领域的潜在维度，从临床前到 严重的阿尔茨海默病，并相互作用以定义可预测临床症状的神经生理亚型 以及AD进展的速度。在目标1中，我们将识别可解释的神经回路和关联的潜伏期 使用稀疏多变量相关分析的NPS领域的维度。在目标2中，我们将确定 神经生理亚型在NPS维度指导下的统计聚类法 电路特性。我们将进一步评估和解释神经生物学意义和临床 这些维度和子类型背后的相关性。将制定拟议的方法，并 通过评估来自两个独立队列(OASIS-3和ADNI)的静息状态功能磁共振进行评估 总共有1800多名受试者。项目的成功成果将使人们更好地了解 NPS背后的神经生物学机制及其临床意义，形成了一条有希望的新途径 有可能指导NPS的干预，更好地管理AD进展，从而为 阿尔茨海默病的精准医学之路。

Project Abstract Neuropsychiatric symptoms (NPS) are commonly observed in individuals with mild cognitive impairment or Alzheimer’s disease (AD) dementia. These symptoms affect up to 97% of patients during the course of AD and may cause accelerated declines in cognitive functions and conversion to dementia. Though numerous efforts have been devoted to investigating the etiology of NPS, the neurobiological basis underlying NPS in AD dementia remains unclear. There is an urgent need to advance the mechanistic understanding of these symptoms, which is crucial for early detection and timely intervention to prevent AD progression. Increasing evidence has indicated that differential NPS overlap substantially and are relevant to dysfunctions in distinctive brain networks. Assessing NPS dimensionally and their associated circuit-level dysfunctions would therefore provide significant benefits to deepen our understanding of neural circuits involved in the expression of NPS. In response to the guidelines of the PAR-20-159, the overall objective of the project is to assess neural circuits and identify neurophysiological subtypes (i.e., subtypes) underlying dimensions of NPS in dementia. We hypothesize that distinct patterns of neural circuits will reflect latent dimensions of NPS domains that span from preclinical to severe AD dementia, and interact to define neurophysiological subtypes that are predictive of clinical symptoms and the rate of AD progression. In Aim 1, we will identify interpretable neural circuits and the linked latent dimensions of NPS domains using a sparse multivariate correlation analysis. In Aim 2, we will identify neurophysiological subtypes using statistical clustering with guidance from the NPS dimension-associated circuitry characteristics. We will further evaluate and interpret the neurobiological meanings and clinical relevance underlying these dimensions and subtypes. The proposed approaches will be developed and evaluated by assessing resting-state functional MRI from two independent cohorts (OASIS-3 and ADNI) with more than 1,800 subjects in total. Successful outcomes of the project will lead to an improved understanding of the neurobiological mechanism underlying NPS and its clinical relevance, form a promising new avenue to potentially guide the intervention of NPS and better the management of AD progression, and hence pave the way towards precision medicine of AD dementia.