Neuroanatomical associations with the factor structure underlying neuropsychiatric symptoms in Alzheimer's disease

我们建议利用一个基于因素的方法来分类神经精神症状（神经精神症状）在一个数据驱动的 的方式，并确定与不同的认知因素相关的大脑网络，在200名参与者中， 轻度阿尔茨海默病（AD）。迫切需要开发ADRD中的抗抑郁药的改进治疗方法。 目前的药物治疗是50年前开发的，通常无效， 具有严重的副作用，包括增加死亡率。基于神经解剖学的治疗，如TMS 和经颅直流电刺激（tDCS）治疗脑梗死是有希望的，但他们的发展一直是 由于我们缺乏对ADRD中神经解剖学基础的了解而受到阻碍。拟建项目 试图利用目前NIH资助的研究项目和精神病学评估工具， 为弥补这一知识差距，应：1。以数据驱动的方式测量和分类数据; 2. 确定神经学确定的神经因子与特定大脑网络之间的关联; 3. 比较一种新的简短的数据驱动的测量，两个常用的测量，使用神经， 解剖学黄金标准这些调查以前没有进行过。我们的研究对象将是 从一项正在进行的NIH资助的基于社区的队列研究中招募，AD严重程度的预测因素 研究（AG 007370）和哥伦比亚记忆和行为障碍诊所。对于拟议项目，我们 将在一次横断面管理中执行以下测量：结构、DTI和静息 BOLD MRI; DSM-5研究版或SCID-5-RV的结构化临床访谈;以及自我和 DSM 5 Cross-Cutting Psychiatric Symptom Measure或“Cross-Cutting Measure”。SCID- 5-RV是一种标准化的临床精神病学访谈，几十年来一直在开发，以评估非常大范围的 精神症状，以可靠，有效和心理测量学上合理的方式。跨部门措施是一项 有效的，可靠的，简短的，自适应的工具，旨在评估精神病理学的所有主要领域， 心理测量特性它可以在线管理。已经发现有少数因素 是SCID检测到的精神病诊断的基础，包括内在化、外在化和精神病 因素涉及腹内侧前额叶皮层（vmPFC）和杏仁核的网络受损， 与内化因子相关，腹外侧PFC（vlPFC）与外化因子相关， 后扣带皮层（PCC）与精神病因素。我们将评估的因素结构， SCID-5-RV，并在sMRI、DTI和fMRI上确定与这些因素相关的脑网络。我们将 比较横切测量与神经精神量表和老年抑郁量表， 神经解剖学的黄金标准这些调查可以改善我们对环境的测量和理解。 的神经解剖学基础，并提供了新的数据驱动的测量方法和治疗目标， 在ADRD的神经解剖学治疗的临床试验中，如TMS和tDCS。

We propose to utilize a factor-based approach to classify Neuropsychiatric Symptoms (NPS) in a data-driven manner, and to determine the brain networks associated with different NPS factors, in 200 participants with mild Alzheimer’s disease (AD). There is a crucial need to develop improved treatments for NPS in ADRD. Current pharmacological treatments for NPS were developed 50 years ago, are often inefficacious, and can have serious adverse effects including increased mortality. Neuroanatomically-based treatments such as TMS and transcranial direct current stimulation (tDCS) for NPS are promising, but their development has been hampered by our lack of knowledge about the neuroanatomical bases of NPS in ADRD. The proposed project attempts to leverage current NIH-funded research programs and assessment tools developed in psychiatric settings to address this knowledge gap by: 1. Measuring and classifying NPS in a data-driven manner; 2. Determining the associations between empirically-determined NPS factors and specific brain networks; 3. Comparing a novel brief data-driven measure of NPS to two commonly used NPS measures using a neuro- anatomic gold-standard. These investigations have not been previously performed. Our subjects will be recruited from one ongoing NIH-funded study of a community-based cohort, the Predictors of Severity in AD study (AG007370), and the Columbia Memory and Behavioral Disorders Clinic. For the proposed project, we will perform the following measures in a single cross-sectional administration: Structural, DTI, and resting BOLD MRI; The Structured Clinical Interview for DSM-5 Research Version or SCID-5-RV; And the self- and informant-based DSM 5 Cross-Cutting Psychiatric Symptom Measure or “Cross-Cutting Measure”. The SCID- 5-RV is a standardized clinical psychiatric interview developed over decades to assess a very large range of psychiatric symptoms in a reliable, valid, and psychometrically sound manner. The Cross-Cutting Measure is a valid, reliable, brief, adaptive instrument designed to assess all major domains of psychopathology with good psychometric properties. It can be administered on-line. A small number of factors have been found to underlie psychiatric diagnoses detected by the SCID, including Internalizing, Externalizing, and Psychosis factors. Damage to networks involving the ventromedial prefrontal cortex (vmPFC) and amydgala is associated with the Internalizing factor, the ventrolateral PFC (vlPFC) with the Externalizing factor, and the posterior cingulate cortex (PCC) with the Psychosis factor. We will assess the factor structure of NPS on the SCID-5-RV and determine the brain networks associated with these factors on sMRI, DTI, and fMRI. We will compare the Cross-Cutting Measure to the Neuropsychiatric Inventory and Geriatric Depression Scale using a neuroanatomic gold standard. These investigations could improve our measurement and understanding of the neuroanatomical bases of NPS and provide novel data-driven measures of NPS and treatment targets for use in clinical trials of neuroanatomically-based treatments for NPS in ADRD such as TMS and tDCS.