生长激素缺乏症儿童静息态网络的变化。

IF 2.4 3区 医学 Q3 NEUROSCIENCES
Ju-Rong Ding, Chenyu Feng, Hui Zhang, Yuan Li, Zhiling Tang, Qiang Chen, Xin Ding, Mei Wang, Zhongxiang Ding
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引用次数: 0

摘要

目的 生长激素缺乏症(GHD)是指部分或完全缺乏生长激素。身材矮小和生长缓慢是 GHD 患者的特征。以往的神经影像学研究表明,GHD可能会导致患者出现认知和行为障碍。静息态网络(RSN)是大脑中表现出同步活动的区域,与我们的认知和行为密切相关。因此,本研究旨在通过研究RSNs的变化,探讨GHD患儿的认知和行为异常。方法 收集了 26 名 GHD 儿童和 15 名健康对照者的静息态 fMRI(rs-fMRI)数据。采用独立成分分析法从 rs-fMRI 数据中识别出七个 RSN。使用双样本 t 检验估计 RSN 的组间差异。相关分析用于研究差异区域与临床指标之间的关联。结果 与健康对照组相比,GHD患儿在显著性网络(SN)、默认模式网络(DMN)、语言网络(LN)和感觉运动网络(SMN)方面存在显著差异。此外,GHD患儿的右侧后顶叶回与促肾上腺皮质激素(ACTH)呈负相关,而左侧前顶叶下回与胰岛素样生长因子1(IGF-1)呈正相关。结论 这些结果表明,RSN 的改变可能是 GHD 儿童认知和行为异常的原因,如运动功能下降、语言退缩、焦虑和社交焦虑。这些发现为揭示 GHD 儿童的病理生理机制提供了神经影像学支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Changes in Resting-State Networks in Children with Growth Hormone Deficiency.

Purpose: Growth hormone deficiency (GHD) refers to the partial or complete lack of growth hormone. Short stature and slow growth are characteristic of patients with GHD. Previous neuroimaging studies have suggested that GHD may cause cognitive and behavioral impairments in patients. Resting-state networks (RSNs) are regions of the brain that exhibit synchronous activity and are closely related to our cognition and behavior. Therefore, the purpose of the current study was to explore cognitive and behavioral abnormalities in children with GHD by investigating changes in RSNs. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data of 26 children with GHD and 15 healthy controls (HCs) were obtained. Independent component analysis was used to identify seven RSNs from rs-fMRI data. Group differences in RSNs were estimated using two-sample t-tests. Correlation analysis was employed to investigate the associations among the areas of difference and clinical measures. Results: Compared with HCs, children with GHD had significant differences in the salience network (SN), default mode network (DMN), language network (LN), and sensorimotor network (SMN). Moreover, within the SN, the functional connectivity (FC) value of the right posterior supramarginal gyrus was negatively correlated with the adrenocorticotropic hormone and the FC value of the left anterior inferior parietal gyrus was positively correlated with insulin-like growth factor 1. Conclusions: These results suggest that alterations in RSNs may account for abnormal cognition and behavior in children with GHD, such as decreased motor function, language withdrawal, anxiety, and social anxiety. These findings provide neuroimaging support for uncovering the pathophysiological mechanisms of GHD in children. Impact statement Children with growth hormone deficiency (GHD) generally experience cognitive and behavioral abnormalities. However, there are few neuroimaging studies on children with GHD. Moreover, prior research has not investigated the aberrant brain function in patients with GHD from the perspective of brain functional networks. Therefore, this study employed the independent component analysis method to investigate alterations within seven commonly observed resting-state networks due to GHD. The results showed that children with GHD had significant differences in the salience network, default mode network, language network, and sensorimotor network. This provides neuroimaging support for revealing the pathophysiological mechanisms of GHD in children.

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来源期刊
Brain connectivity
Brain connectivity Neuroscience-General Neuroscience
CiteScore
4.80
自引率
0.00%
发文量
80
期刊介绍: Brain Connectivity provides groundbreaking findings in the rapidly advancing field of connectivity research at the systems and network levels. The Journal disseminates information on brain mapping, modeling, novel research techniques, new imaging modalities, preclinical animal studies, and the translation of research discoveries from the laboratory to the clinic. This essential journal fosters the application of basic biological discoveries and contributes to the development of novel diagnostic and therapeutic interventions to recognize and treat a broad range of neurodegenerative and psychiatric disorders such as: Alzheimer’s disease, attention-deficit hyperactivity disorder, posttraumatic stress disorder, epilepsy, traumatic brain injury, stroke, dementia, and depression.
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