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亨廷顿病 zQ175DN 小鼠模型静息状态共激活模式变化及其预测能力的纵向研究。

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease.

机构信息

Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium.

µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium.

出版信息

Sci Rep. 2023 Jun 23;13(1):10194. doi: 10.1038/s41598-023-36812-y.

Abstract

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.

摘要

亨廷顿病 (HD) 是一种神经退行性疾病,由亨廷顿基因中扩展的(≥40)谷氨酸编码 CAG 重复引起,导致纹状体和皮质神经元的功能障碍和死亡。尽管该疾病的遗传特征和临床症状已得到更好的了解,但大脑的功能结构变化,尤其是在临床症状明显之前的变化,尚未得到充分和一致的描述。在这项研究中,我们使用静息态功能磁共振成像 (RS-fMRI) 技术,试图在 3、6 和 10 个月大的杂合子 (HET) zQ175 delta-neo (DN) 小鼠模型中发现大脑的功能变化。该小鼠模型表现出随年龄恶化的分子、细胞和电路改变。该模型在 6 和 10 个月大时出现运动功能障碍。具体来说,我们进行了纵向研究,以研究共同激活模式 (CAPs) 的变化,这些变化是构成静息态网络 (RSNs) 的大脑活动的瞬态状态。在 10 个月的时间点,CAP 时间特性的变化最为明显;与野生型小鼠相比,两个相互关联的 CAP 的持续时间减少,这两个 CAP 的特征是默认模式网络 (DMLN) 的同时共同激活和外侧皮质网络 (LCN) 的同时去激活,以及反之亦然。在 CAP 期间,以不同大脑区域的激活水平来衡量的 CAP 空间特性在所有三个年龄组中都发生了变化,并且在 6 个月和 10 个月大时变得更加明显。然后,我们评估了 CAP 指标区分 HET 动物与对照的交叉验证预测能力。在所有三个年龄段,CAP 的空间特性的分类准确率均显著高于随机水平,在 6 个月和 10 个月大时的准确率达到 80%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc7a/10290061/e326c458133c/41598_2023_36812_Fig1_HTML.jpg

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