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阿尔茨海默病进展过程中额叶皮层的共表达网络分析。

Co-expression network analysis of frontal cortex during the progression of Alzheimer's disease.

机构信息

Department of Translational Neuroscience, Michigan State University, Grand Rapids, MI 49503, USA.

Bioinformatics and Biostatistics Core, Van Andel Research Institute, Grand Rapids, MI 49503, USA.

出版信息

Cereb Cortex. 2022 Nov 9;32(22):5108-5120. doi: 10.1093/cercor/bhac001.

Abstract

Mechanisms of Alzheimer's disease (AD) and its putative prodromal stage, amnestic mild cognitive impairment (aMCI), involve the dysregulation of multiple candidate molecular pathways that drive selective cellular vulnerability in cognitive brain regions. However, the spatiotemporal overlap of markers for pathway dysregulation in different brain regions and cell types presents a challenge for pinpointing causal versus epiphenomenal changes characterizing disease progression. To approach this problem, we performed Weighted Gene Co-expression Network Analysis and STRING interactome analysis of gene expression patterns quantified in frontal cortex samples (Brodmann area 10) from subjects who died with a clinical diagnosis of no cognitive impairment, aMCI, or mild/moderate AD. Frontal cortex was chosen due to the relatively protracted involvement of this region in AD, which might reveal pathways associated with disease onset. A co-expressed network correlating with clinical diagnosis was functionally associated with insulin signaling, with insulin (INS) being the most highly connected gene within the network. Co-expressed networks correlating with neuropathological diagnostic criteria (e.g., NIA-Reagan Likelihood of AD) were associated with platelet-endothelium-leucocyte cell adhesion pathways and hypoxia-oxidative stress. Dysregulation of these functional pathways may represent incipient alterations impacting disease progression and the clinical presentation of aMCI and AD.

摘要

阿尔茨海默病(AD)及其假定的前驱阶段,遗忘型轻度认知障碍(aMCI)的机制涉及多个候选分子途径的失调,这些途径导致认知大脑区域的选择性细胞易损性。然而,不同脑区和细胞类型中途径失调标志物的时空重叠给确定特征性疾病进展的因果变化和偶发变化带来了挑战。为了解决这个问题,我们对从临床诊断为无认知障碍、aMCI 或轻度/中度 AD 的死者的额皮质样本(布罗德曼 10 区)中定量的基因表达模式进行了加权基因共表达网络分析和 STRING 互作网络分析。选择额皮质是因为该区域在 AD 中相对长期参与,这可能揭示与疾病发病相关的途径。与临床诊断相关的共表达网络与胰岛素信号相关,胰岛素(INS)是网络中连接度最高的基因。与神经病理学诊断标准(例如,NIA-Reagan AD 可能性)相关的共表达网络与血小板-内皮-白细胞细胞黏附途径和缺氧-氧化应激相关。这些功能途径的失调可能代表影响疾病进展和 aMCI 和 AD 临床表现的初始改变。

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